More than Logistic

Quality Cycles Improvement

2008-05-31T21:47:00.001-07:00

One particular section of the model deserves a closer look in the discussion of quality cycles. The flow of information in the upper left quadrant of the model changes depending on the type of quality improvement process involved. Two quality improvement terms borrowed from the Japanese are particularly relevant to this topic. The terms and their definitions are:
Hoshin:
A breakthrough innovation or dramatic change in level of performance. The Hoshin concept was developed in Japan to communicate company policy to everyone in the organization. Hoshin's primary benefit is to focus activity on the key things necessary for success. Japanese Deming Prize winners credit Hoshin as being a key contributor to their business success. Progressive US companies, like Hewlett-Packard and Xerox, have also adopted Hoshin as their strategic planning process. Hoshin plans, therefore, map out a framework for substantial increases in performance.
Kaizen:
Kaizen is the Japanese term for continuous improvement. It refers both to a statistical/quantitative evaluation of process performance and an adaptive framework of organizational values and beliefs that focuses workers and management alike on zero defects. Kaizen plans lay out an ongoing refinement process.
Hoshin and Kaizen, along with a Plan-Do-Check-Act (PDCA) cycle, will be used to describe the previously mentioned information flows and demonstrate the quality improvement cycles.
1. Breakthrough Innovation (Hoshin) Cycle
When Cp <=4/3, an unstable process is indicated and a major innovative change, or Hoshin, is suggested. A Hoshin could also be considered even when a process is stable. For a business firm to maintain its competitive edge and/or increase revenue, it may be necessary to initiate a Hoshin cycle for a process that is already at a high sigma level of quality. Figure 8 depicts the information flow within the model when a jump in productivity or level of performance is desired.
Through the use of the MBM component, a simulation of the physical layer is created so that the effects of altering process variables may be analyzed. It is probable that numerous simulations will be executed with differing variables until a path representing the breakthrough is discovered. At this point, the results of the simulation are implemented in the actual system with feedback flowing back through the management element for monitoring and adjustment. It may take a process several cycles to stabilize and begin the Kaizen cycles.

2. Continuous Improvement (Kaizen) Cycle
Generally speaking, when Cp >4/3 for a process, that process is considered stable [Mizuno, 1988]. Figure 9 depicts the information flow for Kaizen continuous improvement cycles. In this situation, feedback from the physical layer is monitored by the management component . Input from the MIS and DSS assist managers in making incremental improvements to the business processes.

3. PDCA Quality Cycles
In this view of quality improvement cycles, the upper and lower PDCA cycles of Figure 10 correspond to Hoshin and Kaizen respectively. For illustrative purposes we will assume an unstable process as a starting point and follow it through the 8 steps of this process improvement procedure [Eddlestone, 1992].
Beginning at the Plan element of the upper cycle, the steps are as follows:
Develop process innovation/breakthrough plans.
Implement plans.
Check impact on capability
Act on results (decision point). If Cp >4/3 , process has stabilized. Go to plan element of lower PDCA (Kaizen) cycle.
Develop process improvement plans.
Implement plans.
Check process variation.
Act on results (decision point). If Cp <=4/3 , process is now unstable. Go to plan element of upper PDCA (Hoshin) cycle.
4. A Simplified Example of Process Improvement
For the purpose of demonstrating a series of quality improvement cycles, the output of a modeling simulation under development at North Carolina State University will be presented1. It is beyond the scope of this paper to provide an in-depth description of the theory and formulae that form the basis of this simulation. The information provided here is for illustrative purposes only. The simulation requires variable values to be input for certain business competencies. The inputs are a decimal number ranging from 0 to 1and represent the percentage level of a particular competency. Of interest to this example are:
Information Technology Competencies: The business firm's level of competency in utilizing information technology. For this example, the variable has values of IT=0.45, IT=0.5, and IT=1.0.
Mission Critical Competencies: These are the core competencies vital to the success of critical business processes. This variable has values of MC=0.85, MC=0.5, and MC=1.0.
Learning Competency: The ability to incorporate learning from the changes to a business process. This variable has a value of L=0.5 for all three simulation runs.
The simulation scenario portrayed here is that of a major pharmaceutical company that has decided it must reduce the mean time for drug-to-market delivery. The delivery time units are in days and the company is seeking a reduction in mean delivery time from approximately 4000 to 2000 days over a period of four years.
Notice that the process is starting at a current level of six sigma. In essence, the trailing end of the distribution curve for longer delivery times is cut off. When the sigma level is recalculated under these conditions the result is that sigma = 3.
In the simulation, the start of each major Hoshin cycle corresponds with the beginning of a year. Four cycles are depicted within each major Hoshin cycle; each of these corresponds to a 3 month period (one quarter). During the period of four cycles (1 year), sigma builds from sigma =3 back to sigma = 6. Figure 11 is a graphic depiction of the simulation output for the mean delivery times over a period of four years. Each line on the graph represents the mean delivery time as impacted by the differing competency values.

The simulation shows that significant drops in mean delivery time occur at the beginning of each major Hoshin cycle. The values associated with business competencies also have a measurable effect on achieving the company goal. The main point here is that breakthrough innovation is a cyclic process with dependencies on business competency values.

1. Implementation of simulation model by T.L. Honeycutt and W.M. Waters, Department of Math, Science, and Technology Education

V. Conclusion
Quality improvement and information technology have an integral relationship in a business firm. The IT infrastructure is essential in tracking and monitoring the quality improvement process. The model of a business firm presented in this paper combines IT and quality improvement in an organized structure that exploits the synergy of the two concepts. Finally, the competency and quality of the management process carries more weight than the technology by which it is supported.

Introducing to the Six Sigma

2008-05-16T02:22:00.000-07:00

What is Six Sigma?

A. A really small number
B. Flavor of the month program
C. Current incarnation of TQM
D. None of the above

Foundations of Modern Management Philosophies
Edwards Deming’s 14 Points
Create constancy of purpose
Reject defects
Reject inspection
Use quality criteria to award business
Constantly improve
Modernize training
Modernize management
Drive out fear
Break down functional barriers
Eliminate targets & slogans
Eliminate numerical quotas
Remove barriers from hourly workers
Train vigorously
Create a supportive management structure

JBoseph Juran’s 10 Step
suild awareness of the need and opportunity for improvement
Set goals for improvement
Organize to reach the goals (have a plan and an organizational structure)
Provide training
Carry out projects to solve problems
Report progress
Give recognition
Communicate results
Keep score
Maintain momentum by making annual improvement part of the regular systems and processes of the organization

Six Sigma: A Modern Definition
Six Sigma is a philosophy that underlies efforts to improve business performance and customer satisfaction
Using facts and data to eliminate waste and variation
Eliminating activities that don’t add value
It’s more than statistics(much more)
Asking the right question
Questions managers should ask
Questions managers should answer

Using data
Using the right tools
Using the right process

Questions Managers Should Ask
What activities are you responsible for? Who is the owner of these processes? Who are the team members? How well does the team work together
Which processes have the highest priority for improvement? How did you come to this conclusion? Where is the data that led to this conclusion?
How is the process performed?
What are your process performance measures? How accurate and precise is your measurement system?
What are the customer-driven specifications for all of your performance measures? How good or bad is the current performance? Show me the data. What are the improvement goals for the process?
What are all the sources of variability in the process?
Which sources of variability do you control?
Are any of the sources of variability supplier-dependent? If so, what are they, who is the supplier, and what are we doing about it?
What are the key variables that affect the average and variation of the measures of performance?
What are the relationships between the measures of performance and the key variables?
Do any key variables interact?
What setting for the key variables will optimize the measures of performance?
For the optimal settings of the key variables, what kind of variability exists in the performance measures?
How much improvement has the process shown in the past 6 months?
How much time and money have your efforts saved or generated for the company?

Questions Managers Should Answer
What is your product or service and who are your customers?
What perception do your customers have of your product or service? How do you know?
Do you believe quality issues are important to your company? Why? Which ones?
What is the company’s current share of the total market? Can quality improvement efforts assist you in increasing the market share and/or increasing profits? How?
How many hours per week do you currently have scheduled that are devoted strictly to quality issues?
How often per week do you solicit feedback from the people you mange? What kind of feedback do you solicit?
What are the right quality-oriented questions managers need to ask their people? What methods pr tools can be used to answer them?
Are your people trained to successfully use the best quality improvement tools? What is your ROI for the training?
Do you have a SOP for documenting quality improvement efforts?
What barriers do your people face when trying to do quality improvement? What are you doing to remove these barriers?
What metrics are you evaluated on that relate to quality issues? Are you held accountable for these metrics? What are the specific improvement goals for these metrics?
How much waste does your company have? What is the cost of poor quality?
One year from now, what evidence will you have to show that you made a difference?

Use Data…..but KISS!
Measure of central tendency
mean
median
Measures of dispersion
range
sample variance
sample deviation

Use Tools…..the right tools
Quality Function Deployment (QFD)
Pareto
Histograms
Run Charts
Control Charts
Design of Experiments (DOE)
Scatter Diagrams
Process Flow Diagrams
Nominal Group Techniques
Teamwork

Distribution Requirements Planning

2008-05-16T02:19:00.000-07:00

Definitions

DRP “…for tying the physical distribution system to the manufacturing planning and control (MPC) system.”

A set of techniques that can improve the linkages of the demand from the marketplace and manufacturing ability.

Advantages of DRP
DRP connects current inventory and forecasts of field demand to manufacturing’s MPS and MRP.
DRP can anticipate future requirements in the field.
Match material supply to demand, match inventory to customer service requirements.
Increase the speed the firm can react to the marketplace
Provide savings by better aggregation of transportation and dispatching.

The Basics
Basic idea: Time-phased order planning (TPOP)
Independent at field location, based on inventory level
Basic objective: Build a period-by-period plan for distribution of goods that provides the minimum inventory required to meet demand and satisfy safety stocks
Required SKU-level data for DRP:
Current balance on hand (BOH)
Target safety stock
Recommended lot size
Replenishment lead time
Forecasts of demand by period

Using DRP
Consolidating demand and supply information
Using the tables for distribution
Distribution center operations
Transportation load planning
Using the tables for plant activities
Shipping schedules
Production planning

The Value of DRP
“Perhaps DRP’s greatest payoff … is from integrating records and information” (Vollman et al.: p. 756)
DRP summarizes and integrates demand information “from the field” to coordinate distribution and production decisions
In comparison to (s,Q) inventory system
Use (s,Q) if only objective is to minimize inventory level of a specific item at a specific location
Specific advantages of DRP over (s,Q)
DRP not restricted by stable demand assumption
DRP shows planned shipments and thereby allows for planned coordination
DRP allows integration of demand from all sources (e.g, forecasts plus actual orders plus service parts demand)
Note that DRP “approaches” (s,Q) with stable demand and small time buckets

Timing Picking Waves in a Warehouse

2008-05-06T21:46:00.000-07:00

Abstract
To facilitate eÆcient picking tours and worker supervision, warehouses often release
orders to workers in picking waves. The timing of these waves determines how long
orders sit in the queue waiting to be processed, and so provides some control over
average order cycle time. We show how to time picking waves in a warehouse to
minimize average order cycle time. We report on results at a warehouse in California,
which reduced average order cycle time by more than 25% after restructuring its picking
waves. We also argue that cycle time may not be the best metric for many distributors,
and propose a di_erent one based on the practices of a leading e-commerce distributor.
Keywords Warehousing, Distribution, Measurement and methodology, Personnel and shift scheduling

Background
Reducing cycle time in the supply chain means lower inventories and better response to
customers. As distribution _rms wring the last drops of ineÆciency out of their distribution channels, warehouses have focused on tightening up processes and reducing costs. Moreover, the need to satisfy increasingly demanding customers has led to new performance measures that will require even more emphasis on process optimization and cost cutting.
In the future, _rms will have to adapt to the world of e-commerce distribution: direct
customer orders via the Internet, precise order tracking, stringent performance measurement and even auction-based services. As many e-commerce retailers have found, customer satisfaction goes beyond the web experience to e_ective distribution and order delivery. The Internet has also bred the impatient customer, who expects delivery of products ordered on the web almost as quickly as the clicks it took to place the order. Firms are responding by
restructuring processes to reduce order cycle time in the warehouse. The thought is that
reduced order cycle time will improve customer service.
In the warehouse, one component of order cycle time is the time an order spends waiting
to be downloaded, or pulled, from the information system. Waiting time occurs because
work is not released to workers continuously, but rather in batches called picking waves.
Warehouses routinely use picking waves to improve the eÆciency of picking tours. When orders are batched, the _xed time that it takes to circumnavigate a picking area is amortized over more orders, thus reducing average cycle time; but if the batches are too large, cycletime goes up because orders wait excessively in the queue.
We investigate the e_ects of the number and timing of picking waves on average order
cycle time at a warehouse. We describe a simple model, which we solve with a genetic
algorithm, that _nds the optimal times to release work to the warehouse, given its speci_c
order arrival distribution. We report the use of the model at a large warehouse in California,which reduced average order cycle time by more than 25% after restructuring its pickingwaves. After presenting the results, we argue that minimizing cycle time in most cases is not the right objective. We present a superior objective and show how to modify our model to accommodate it.

Choosing picking waves
The test site for our study is a large, multi-warehouse complex (hereafter, \the warehouse")located in California, which supports customers throughout the United States and Asia.The warehouse handles all types of material, from pallet loads to individual piece parts, and employs several methods of storage and material handling, including block stacking, palletrack, man-aboard picking cranes, and mini-stackers.
Because the warehouse supports customers from such a geographically diverse region,
orders arrive throughout the 24-hour day. Customers order via an information system that
holds orders in a queue until the warehouse downloads, or pulls, them from the system. Oncethe orders are in the warehouse system, they are transmitted to handheld or mounted RFdevices maintained by the workers, creating a wave of orders. Workers then traverse their areas, picking orders into totes or onto pallets as appropriate. From the picking area, ordersmove to packing, then on to the shipping area, where workers sort them by customer andtransportation mode.
The number and timing of picking waves determine to some degree the cycle time for
orders, because they determine how long orders spend in the queue. The size of the wave
also determines how long a picking tour will be, which also a_ects cycle time.

Theory and practice
Why not release the work continuously? In theory, releasing the work in a continuous streamminimizes average order cycle time. Imagine that a new order arrives and is transmitted toa worker in an aisle at the moment he is about to pass the item's location.
Proposition 1 Passing over a pick always increases average order cycle time.
Proof Assume total travel in the aisle takes non-zero time s and there are n + 1 picks
remaining in an aisle, each of which takes time t. Assume, without loss of generality, that
we are considering whether or not to pick the next item in the aisle. Consider the average
cycle time delay experienced by all n + 1 items: if we pick the next item, then total delay ist for each of n items, and average delay is ntn+1; if we pass the next item and pick it on the3next tour, then total delay is at least s + nt for that item, and average cycle time delay is s+nt n+1 > nt n+1; therefore, average cycle time is greater if the pick is passed over. 2
Proposition 1 suggests that the optimal order picking strategy is to have workers circum-
navigate the warehouse continuously, picking orders as they appear on their handheld RF
devices. In practice, this is infeasible for a number of reasons. First, order pickers typically have other duties involving paperwork, cleaning, and stowing that are normally done be-tween picking waves. The wave structure allows supervisors to assign workers to other tasksbefore the next wave begins. Second, the warehouse management system must support thecontinuous feed, inserting and sorting orders appropriately as they arrive. (The warehouse management system at our test site was not con_gured to do this.) Third, workers could spend much more time traveling, especially during slow periods, thus wasting labor; that is, continuous picking minimizes cycle time, but at the expense of higher labor costs.What is the minimum time between waves? The answer depends on a number of things:the time required to circumnavigate each picking area, the time to pick an individual order, the order arrival pattern, and the amount of slack time needed by supervisors to accomplish other things with the workers. At the warehouse, managers suggested that picking waves separated by 2 hours were possible, but waves in consecutive hours were not.

The model
Consider a warehouse that receives orders continuously, but not necessarily uniformly, through-out every 24-hour cycle. Every hour the warehouse has an opportunity to release all orders in the queue to the warehouse, or it may delay until a future hour.
Assume that orders arrive to the warehouse every hour according to some distribution.
We seek a set of n picking waves that minimizes average order cycle time. Because total system throughput (orders/day) is _xed, we know by Little's Law that minimizing the average work in process inventory also minimizes the average cycle time.
Planning picking waves is similar to the well-studied production lot-sizing problem with
time-varying demand (see Nahmias, 1997, for a discussion of di_erent solution methodologies). In our case, inventory holding cost is simply one hour per unit per time period, but the notion of setup cost is di_erent. In the lot-sizing problem, one incurs a monetary setup cost each time a new lot is ordered. In our problem the warehouse incurs a _xed time penalty for each wave (in the form of a picking tour) that could prevent scheduling a wave in the next hour. We work around this issue by specifying the number of waves a priori. ( to be continued……………. )

Source : Kevin R. Gue Department of Systems Management
Naval Postgraduate School Monterey.

Bussiness preparation, not just make sure!

2008-05-02T02:02:00.000-07:00

Studi kelayakan sangat diperlukan oleh banyak kalangan, khususnya terutama bagi para investor yang selaku pemrakarsa, bank selaku pemberi kredit, dan pemerintah yang memberikan fasilitas tata peraturan hukum dan perundang-undangan, yang tentunya kepentingan semuanya itu berbeda satu sama lainya. Investor berkepentingan dalam rangka untuk mengetahui tingkat keuntungan dari investasi, bank berkepentingan untuk mengetahui tingkat keamanan kredit yang diberikan dan kelancaran pengembaliannya, pemerintah lebih menitik-beratkan manfaat dari investasi tersebut secara makro baik bagi perekonomian, pemerataan kesempatan kerja, dll.
Mengingat bahwa kondisi yang akan datang dipenuhi dengan ketidakpastian, maka diperlukan pertimbangan-pertimbangan tertentu karena didalam studi kelayakan terdapat berbagai aspek yang harus dikaji dan diteliti kelayakanya sehingga hasil daripada studi tersebut digunakan untuk memutuskan apakah sebaiknya proyek atau bisnis layak dikerjakan atau ditunda atau bahkan dibatalkan. Hal tersebut diatas adalah menunjukan bahwa dalam studi kelayakan akan melibatkan banyak tim dari berbagai ahli yang sesuai dengan bidang atau aspek masing-masing seperti ekonom, hukum, psikolog, akuntan, perekayasa teknologi dan lain sebagainya.
Dan studi kelayakan biasanya digolongkan menjadi dua bagian yang berdasarkan pada orientasi yang diharapkan oleh suatu perusahaan yaitu berdasarkan orientasi laba, yang dimaksud adalah studi yang menitik-beratkan pada keuntungan yang secara ekonomis, dan orientasi tidak pada laba (social), yang dimaksud adalah studi yang menitik-beratkan suatu proyek tersebut bisa dijalankan dan dilaksanakan tanpa memikirkan nilai atau keuntungan ekonomis.
Jadi pengertian studi kelayakan proyek atau bisnis adalah penelitian yang menyangkut berbagai aspek baik itu dari aspek hukum, sosial ekonomi dan budaya, aspek pasar dan pemasaran, aspek teknis dan teknologi sampai dengan aspek manajemen dan keuangannya, dimana itu semua digunakan untuk dasar penelitian studi kelayakan dan hasilnya digunakan untuk mengambil keputusan apakah suatu proyek atau bisnis dapat dikerjakan atau ditunda dan bahkan ditadak dijalankan.
Aspek yang terdapat pada studi kelayakan proyek atau bisnis yang terdiri dari berbagai aspek yang sudah disebutkan di atas antara lain :
1. Aspek hukum, Berkaitan dengan keberadaan secara legal dimana proyek akan dibangun yang meliputi ketentuan hukum yang berlaku termasuk :
a. Perijinan :
i) Izin lokasi :
• sertifikat (akte tanah), • bukti pembayaran PBB yang terakhir, • rekomendasi dari RT / RW / Kecamatan
ii) Izin usaha : • Akte pendirian perusahaan dari notaris setempat PT/CV atau berbentuk badan hukum lainnya.
• NPWP (nomor pokok wajib pajak), • Surat tanda daftar perusahaan, • Surat izin tempat usaha dari pemda setempat
• Surat tanda rekanan dari pemda setempat, • SIUP setempat, • Surat tanda terbit yang dikeluarkan oleh Kanwil Departemen Penerangan
2. Aspek sosial ekonomi dan budaya, Berkaitan dengan dampak yang diberikan kepada masyarakat karena adanya suatu proyek tersebut :
a. Dari sisi budaya, Mengkaji tentang dampak keberadaan peroyek terhadap kehidupan masyarakat setempat, kebiasaan adat setempat.
b. Dari sudut ekonomi, Apakah proyek dapat merubah atau justru mengurangi income per capita panduduk setempat. Seperti seberapa besar tingkat pendapatan per kapita penduduk, pendapatan nasional atau upah rata-rata tenaga kerja setempat atau UMR, dll.
c. Dan dari segi sosial , Apakah dengan keberadaan proyek wilayah menjadi semakin ramai, lalulintas semakin lancer, adanya jalur komunikasi, penerangan listrik dan lainnya, pendidikan masyarakat setempat.
Untuk mendapatkan itu semua dengan cara wawancara, kuesioner, dokumen, dll. Untuk melihat apakah suatu proyek layak atau tidak dilakukan dengan membandingkan keinginan investor atau pihak yang terkait dengan sumber data yang terkumpul.
3. Aspek pasar dan pemasaran, Berkaitan dengan adanya peluang pasar untuk suatu produk yang akan di tawarkan oleh suatu proyek tersebut : • Potensi pasar, • Jumlah konsumen potensial, konsumen yang mempunyai keinginan atau hasrat untuk membeli.
• Tentang perkembangan/pertumbuhan penduduk, • Daya beli, kemampuan konsumen dalam rangka membeli barang mencakup tentang perilaku, kebiasaan, preferensi konsumen, kecenderungan permintaan masa lalu, dll.
• Pemasaran, menyangkut tentang starategi yang digunakan untuk meraih sebagian pasar potensial atau pelung pasar atau seberapa besar pengaruh strategi tersebut dalam meraih besarnya market share.
4. Aspek teknis dan teknologi, Berkaitan dengan pemilihan lokasi proyek, jenis mesin, atau peralatan lainnya yang sesuai dengan kapasitas produksi, lay out, dan pemilihan teknologi yang sesuai.
5. Aspek manajemen, Berkaitan dengan manajemen pembangunan proyek dan operasionalnya.
6. Aspek keuangan, Berkaitan dengan sumber dana yang akan diperoleh dan proyeksi pengembaliannya dengan tingkat biaya modal dan sumber dana yang bersangkutan.

Anda boleh membuat studi kelayakan bisnis yang baik, antara lain dengan kriteria:
1. Usahanya bisa dijalankan. Lebih baik lagi kalau usaha itu sudah operasional.
2. Usaha itu menguntungkan. Lebih baik lagi kalau keuntungannya cukup besar.
3. Usaha itu membutuhkan modal sedikit. Lebih baik lagi tanpa modal.
4. Bagi hasilnya menarik hati pemilik modal
5. Lebih baik bila anda menjamin dana milik investor tidak hilang.

Secara umum tujuan penyusunan studi kelayakan, pada intinya adalah untuk mencari jawaban dari pertanyaan-pertanyaan berikut ini : (1) Apakah produk yang akan ditawarkan marketable atau tidak ?, (2) dari sisi produksi, apakah secara teknis dapat dilakukan dan sustainable ?, (3) dari sudut pandang manajemen, apakah bisnis tersebut efektif dan efisien ?, (4) ditinjau dari sisi hukum termasuk usaha yang legal atau illegal ? dan yang terakhir dari sisi keuangan, (5) apakah bisnis tersebut profitable atau tidak? Jika jawabannya adalah marketable, sustainable, efektif dan efisien, legal dan profitable, berarti bisnis tersebut LAYAK. Layak untuk dibiayai/diberikan kredit/didirikan/dan atau disetujui ijinnya.

Be Smart Worker.

2008-04-30T03:21:00.000-07:00

Menjadi Lebih Produktif
Apa yang terlintas di benak kita saat mendengar istilah kerja cerdas? Ada yang mengartikan bahwa kerja cerdas itu adalah sebuah model kerja di mana seseorang melakukan pekerjaan sedikit tapi hasilnya besar. Berangkat kerja tanpa terikat pada aturan atau jam kerja formal atau berbisnis jarang-jarang tetapi sekali mendapatkan untung, untungnya cukup untuk dinikmati berbulan-bulan atau cukup untuk sekian minggu ke depan.
Orang yang berpendapat demikian mungkin menganut teori Paretto yang 80/20 itu (The law of imbalance). Kalau merujuk teori ini, berarti 80 % penghasilan orang itu dihasilkan dari 20 % aktivitas kerja / bisnisnya. Aktivitasnya hanya 20 % tapi penghasilannya 80 %. Mungkin, karena orang seperti itu sudah lihai dalam membidik peluang, maka terwujudlah kerja cerdas dalam pengertian seperti di atas.
Terus terang, meski pengertian di atas sering saya dengar dalam pembicaraan, tetapi dalam prakteknya masih jarang saya lihat. Saya tidak tahu apakah Anda juga punya pengalaman seperti saya atau tidak. Yang kerap kita jumpai, kalau ada orang yang mendapatkan hasil banyak, orang itu juga bekerja banyak. Konon, Bill Gate yang dikenal orang pintar dan orang kaya, punya jam kerja yang jauh lebih banyak dibanding dengan karyawannya. Cuma bedanya, Bill Gate tidak merasakan pekerjaannya sebagai tekanan yang membebani.
Tak hanya Bill Gate saja. Di beberapa stasiun teve sekarang ini kerap ditayangkan sukses stori para pengusaha lokal, baik UKM atau Non-UKM. Sejauh saya mengikuti sampai saat ini memang saya belum pernah mendengar dari mereka yang mengatakan bahwa prestasi usahanya itu diciptakan dari model kerja cerdas dalam pengertian di atas. Yang sering mereka katakan justru adalah prinsip mendasar yang umumnya sudah diketahui banyak orang, misalnya: jujur, disiplin, bekerja keras, menjaga kepercayaan, dan semisalnya.
Terlepas apapun orang mengartikan kerja cerdas, tapi di sini kita akan membahas kerja cerdas dalam pengertian: bagaimana kita bisa menjadi lebih produktif dengan alokasi waktu kerja yang sama atau dengan menggunakan peralatan yang sama. Atau dalam pengertian: bagaimana kita bisa memproduksi solusi (barang atau jasa) yang lebih banyak atau lebih cepat dalam waktu yang sama dengan menggunakan peralatan yang sudah kita miliki.
Mungkin contoh beratnya bisa kita ambil dari hasil kerja Frederick W. Taylor pada tahun 1911. Seperti yang sudah jamak diketahui, Taylor adalah seorang insinyur yang bekerja di pabrik. Taylor tidak puas dengan produktivitas para pekerja yang sangat rendah kala itu. Melihat keadaan seperti itu, Taylor menawarkan revolusi mental yang kemudian dikenal dengan 4 prinsip manajemen.
Sebagai bahan perbandingan buat kita, Taylor menawarkan solusi antara lain:
a) Mengembangkan metode, konsep, atau ilmu pengetahuan tentang bagaimana mengerjakan pekerjaan dari pekerjaan itu atau memunculkan teori aplikasi yang terbaik dari pekerjaan yang dilakukan
b) Memilih dan melatih para pekerja dengan pertimbangan dan keputusan yang logis,
c) Menciptakan komunikasi yang sinergis antara manajemen dan pekerja
d) Pembagian kerja dan tanggung jawab yang tegas.
Berdasarkan kondisi dan situasi kontekstual kala itu, konon revolusi mental yang ditawarkan Taylor ini berhasil meningkatkan produktivitas pekerja sampai mencapai 200 %. Menggiurkan, bukan? Atas keberhasilan yang dicapai, Taylor kemudian diberi gelar Bapak Manajemen Ilmiah.
Contoh yang ringan bisa kita ambil dari kebiasaan sehari-hari. Ketika bicara produktivitas, pasti berbeda antara orang yang bekerja dengan target di kepalanya dan orang yang bekerja tanpa ada target di kepalanya. Pasti berbeda antara orang yang bekerja dengan mengembangkan tehnik dan orang yang bekerja dengan tanpa mengembangkan tehnik. Pasti berbeda antara orang yang bekerja dalam keadaan marah dan orang yang bekerja dalam keadaan happy. Pasti berbeda antara orang yang bekerja berdasarkan prioritas dan orang yang bekerja asal-asalan. Pasti berbeda antara orang yang bekerja dengan konsep dan orang yang bekerja tanpa konsep. Bahkan terkadang ada bedanya antara kita bekerja dengan menelpon orang lebih dulu dan bekerja lebih dulu baru menelpon orang. Ini contoh riil yang kita alami sehari-hari.
Intinya, seperti kata orang bijak, di semua pekerjaan di dunia ini ada rahasia Tuhan. Rahasia itu jika semakin kita gali tidak berarti semakin habis. Justru rahasia itu semakin bertambah. Bahkan rahasia itu tidak akan habis ditulis dengan tinta air laut. Ini terjadi dari mulai bagaimana seorang pelayan diskotik menuangkan minuman dari botol ke gelas dengan gayanya yang khas sampai ke bagaimana seorang arsitek merancang bangunan bertingkat. Tugas kita adalah sebetulnya menggali rahasia-rahasia itu sehingga kita bisa selalu meningkatkan produktivitas.
Dengan bertambahnya kemampuan untuk memproduksi solusi yang lebih besar dan lebih cepat, maka secara logis ini akan meningkatkan penghasilan kita. Soal berapa persennya dan kapan peningkatan hasil itu akan terwujud, ini urusan tehnis. Tapi prinsipnya kira-kira begitu.

Syarat menjadi lebih produktif
Beberapa syarat mental di bawah ini sebenarnya adalah tambahan dari yang sudah kita miliki berdasarkan pengalaman sehari-hari. Atau bahkan mungkin sebatas sebagai reminder (pengingat) atas hal-hal mendasar yang kerap kita lupakan dalam praktek. Nah, syarat mental yang perlu kita miliki untuk mencapai kerja cerdas dalam pengertian yang kita bahas di sini adalah:
Mengembangkan standar prestasi yang pas
Pas di sini artinya memiliki standar yang match atau sesuai dengan perkembangan kita hari ini. Seperti yang kita alami, jika standar yang kita patok itu terlalu rendah, biasanya produktivitas kita juga rendah. Tapi, jika terlalu tinggi atau terlalu banyak, biasanya malah bingung atau malah sedikit hasilnya. Karena itu ada yang menyarankan, little is more and more is little.
Dengan kata lain, supaya tetap produktif, berarti kita perlu memberi standar yang benar-benar pas dengan dinamika perkembangan kita. Jangan terlalu rendah atau jangan terlalu sedikit. Tapi, jangan juga terlalu tinggi atau jangan terlalu banyak.

Mengasah kreativitas
Kreatif atau tidak kreatif, pada akhirnya adalah masalah manajemen batin. Suasana atau fasilitas memang mendukung kreativitas, tapi jika batin ini tidak kreatif, fasilitas dan suasana itu tidak ada gunanya. Mengasah kreativitas ini bisa kita lakukan dengan menyediakan ruang untuk menemukan berbagai kemungkinan untuk menciptakan metode, cara atau tehnik baru yang lebih efektif dan lebih efisien dan yang membuat kita menjadi lebih produktif.
Soal apa bentuknya, bagaimana caranya dan lain-lain, ini urusan kita masing-masing. Ini mengingat, biasanya, the best tehnique is always not in the book. Tehnik, metode atau cara yang kita dapatkan dari orang lain atau dari buku, ini umumnya sebagai ?an aid? atau bantuan buat kita untuk melakukan discovery atau eksplorasi.

Menajamkan fokus
Produktivitas sangat erat hubungannya dengan soal fokus. Fokus, karena itu merupakan kekuatan. Contoh sepele, misalnya: jika kita melihat benda di depan mata tetapi pikiran kita tidak fokus, maka produktivitas penglihatan kita juga tidak bagus. Ini terjadi sampai ke hal-hal yang sangat mendasar dalam hidup manusia.
Jika seseorang memfokuskan pikirannya untuk melihat masalah, maka yang menjadi kesimpulan di batinnya adalah masalah. Sebaliknya, jika seseorang memfokuskan pikirannya untuk melihat peluang, maka yang menjadi kesimpulan di batinnya tentang dunia ini adalah peluang. Meski awalnya ini adalah soal kesimpulan di batin, tetapi pada tahapan tertentu akan mempengaruhi tindakan dan produktivitasnya.
Saking eratnya hubungan antara produktivitas dan fokus, teori manajemen sampai mengajarkan kita untuk membagi aktivitas menjadi:
a) prioritas
b) penting
c) mendesak
d) distraksi
Jika kita gagal membedakan antara prioritas dan distraksi (aktivtas yang tidak prioritas, tidak penting dan tidak mendesak), pasti fokus pikiran kita kacau. Kalau sudah kacau, produktivitas kita pun akan terancam.

Menggali Tacit knowledge
Istilah Tacit Knowledge ini bisa kita jumpai di naskah kerja Robert J. Stenberg, pakar Psikologi di Yale University. Ini adalah semacam pengetahuan spesifik tentang sesuatu yang diperoleh seseorang dari praktek. Tacit Knowledge ini punya ciri khas antara lain:
Pengetahuan itu adalah sebuah prosedur di dalam diri seseorang tentang bagaimana sesuatu harus dikerjakan
Pengetauan itu merupakah buah dari melakukan sesuatu, bukan buah dari diajar orang lain
Pengetahuan itu bersifat sangat pribadi
Seorang sopir yang sudah berpengalaman, pasti memiliki prosedur batin tentang bagaimana menjalankan kendaraan yang diajarkan oleh pengalamannya. Prosedur batin itu biasanya tidak dimiliki oleh seoran sopir yang baru lulus dari sekolah montir. Kita sering menyebutnya dengan istilah ?feeling? atau gerakan reflek, atau juga disebut beyond the technique.
Kaitannya dengan produktivitas di sini sangat jelas. Seorang sopir yang sudah bekerja dengan feeling tadi, pasti lebih produktif. Dia lebih tahan lama, lebih rileks, dan lebih cepat. Saya kira ilustrasi ini juga bisa kita terapkan dalam pekerjaan sehari-hari.

Menjaga harmonitas
Seperti juga alam raya ini, hidup kita akan produktif kalau hormonitasnya terjaga, serasi atau seimbang. Belajar dari praktek hidup, mayoritas penyakit yang merupakan ancaman produktivitas, entah itu penyakit jiwa atau raga, mulanya muncul dari pengabaian kecil (ignorance) yang kemudian menimbulkan ketidakhamonisan, atau ketidakseimbangan ke hampir seluruh wilayah hidup.
Contohnya adalah kurang tidur. Ketika kita kurang tidur, yang terjadi bukan hanya kita butuh tidur di siang hari sebagai pengganti waktu tidur yang telah kita gunakan untuk yang lain. Kurang tidur yang sudah sampai pada tingkat overdosis, bisa menganggu hubungan kita dengan pekerjaan, dengan orang lain, dan seterusnya, yang akhirnya mengakibatkan produktivitas rendah.

Perlindungan batin
Batin di sini, tidak bisa kita samakan dengan emosi. Melindungi batin, bukanlah melindungi emosi. Kalau konteksnya produktivitas, batin kita perlu dilindungi dari kotoran yang menganggu produktivitas. Biasanya, kotoran itu adalah masalah yang kita ciptakan sendiri secara tidak sengaja atau masalah yang didatangkan orang lain untuk kita ? yang tidak kita oleh menjadi vitamin batin. Maksudnya ? Kita sering mendengar ucapan, kritik atau pun pendapat orang lain yang tidak enak mengenai diri kita, cara kerja maupun hasil pekerjaan kita.
Kita bisa saja menganggapnya sebagai sampah yang mengotori batin dan harus dibuang, atau menanggapnya sebagai warning signal ? atas sesuatu di dalam diri yang perlu kita renungkan. Kalau kita mau belajar dan bertumbuh, mata batin kita lah yang harus menangkap ?kata-kata? yang ditujuan pada kita, bukan telinga kita. Mata batin, bisa melindungi kita dari self-denial (pengingkaran kenyataan diri). Kita bisa tutup telinga ? tapi tidak bisa menutup mata batin. Kejernihan suara batin bisa menuntun kita bekerja cerdas, kalau kita mau mendengar tuntutannya.
Apa mungkin kita sanggup membersihkan batin dari masalah untuk sekedar menjadi lebih produktif? Kalau konteksnya praktek hidup, maksudnya yang lebih tepat bukanlah bersih dalam arti tidak ada masalah atau lari dari masalah. Selain mustahil, pun juga ini malah tidak produktif. Maksudnya adalah menyelesaikan masalah secara sehat, benar, jujur dan proporsional. Kalau kita proporsional dalam memikirkan, bersikap dan bertindak, maka produktivitas kita tidak terganggu dengan masalah yang ada.
Jika kita sedikit-sedikit sakit hati atau terlalu memasukkan hati ulah orang lain, dan tidak menjadikannya ?obat pahit?, ini bisa mengganggu produktivitas. Batin kita akan bekerja untuk memikirkan orang lain dalam pengertian memikirkan yang tidak perlu, bukan memikirkan bagaimana memperbaiki dan mengembangkan diri, serta memproduksi solusi yang lebih banyak atau lebih cepat. Semoga bermanfaat !

Enrich your live everyday !

2008-04-30T03:20:00.000-07:00

Buddha pernah mengajarkan, ”Pekerjaanmu di dunia adalah untuk menemukan pekerjaan kamu dan lalu dengan sepenuh hati menyerahkan diri kepadanya. Hal ini berarti bahwa kita harus dapat menemukan apa yang menjadi pekerjaan kita yang sebenarnya. Pekerjaan apa yang benar-benar sesuai dengan kata hati kita. Jika kita sudah menemukan pekerjaan tersebut, kita harus sepenuhnya berdedikasi dan mencintai pekerjaan tersebut.
Lalu apa hubungan pekerjaan kita dengan kecerdasan spiritual kita? Apakah mereka yang bekerja memiliki kecerdasan spiritual yang lebih tinggi dibandingkan dengan mereka yang tidak bekerja? Apakah kecerdasan spiritual seseorang menentukan keberhasilannya dalam karier atau pekerjaannya?
Pekerjaan dapat menyediakan kesempatan untuk pertumbuhan spiritual dan diri pribadi, serta juga pertumbuhan hubungan dengan orang lain, pertumbuhan rasa percaya diri dan harga diri, pertumbuhan keuangan dan kesejahteraan. Apabila semua itu tidak tercapai, berarti kita sudah membuang banyak waktu dalam menjalani kehidupan kita.
Dalam penelitian yang dilakukan oleh Gay Hendrick dan Kate Ludeman terhadap 800-an manajer perusahaan yang mereka tangani selama 25 tahun, ditemukan kesimpulan yang cukup mengejutkan. Apabila Anda hendak mencari orang-orang dengan kecerdasan spiritual yang sangat tinggi, orang-orang suci sejati (the real mystics), Anda tidak akan menemukannya di gereja, masjid, pura, kuil, vihara; namun Anda akan menemukannya di korporasi-korporasi besar yang sukses.
Hasil penelitian yang dipublikasikan dalam sebuah buku yang berjudul the Corporate Mystics, menunjukkan bahwa pemimpin-pemimpin yang berhasil membawa perusahaannya ke puncak kesuksesan biasanya adalah orang-orang yang memiliki integritas, terbuka, mampu menerima kritik, rendah hati, mampu memahami orang lain dengan baik, terinspirasi oleh visi, mengenal dirinya sendiri dengan baik, memiliki spiritualitas yang nondogmatis, selalu mengupayakan yang terbaik bagi diri mereka sendiri maupun bagi orang lain. Para pemimpin yang sukses lebih mengamalkan nilai-nilai spiritual dibandingkan orang lain.
Mereka yang cerdas secara spiritual adalah mereka yang berhasil memberi makna dalam kehidupannya dengan bekerja. Selain contoh dari para CEO perusahaan besar di Amerika Serikat, contoh mengenai perjuangan Bunda Teresa, Mahatma Gandhi, Nelson Mandela adalah contoh bahwa bekerja bukan hanya sekedar rutinitas dan hal-hal yang bersifat teknis semata.
Bekerja adalah upaya kita untuk memberi makna pada kehidupan kita dan jalan menuju ke arah takdir atau misi hidup yang harus kita jalani.

Pekerjaan dan Jalan Hidup
Bagi sebagian besar orang, bekerja adalah beban. Kita mendengar ungkapan TGIF (Thank God It’s Friday), I Hate Monday, yang menunjukkan betapa kita merasa segan untuk memulai rutinitas pekerjaan hari demi hari. Pekerjaan bukanlah sesuatu yang kita tunggu-tunggu dan kita harapkan. Bekerja adalah sebagai beban yang harus kita pikul paling tidak lima hari dalam seminggu. Dengan pola pikir seperti ini, kita tidak akan pernah mencapai hal-hal terbaik dalam kehidupan kita. Bagi kita bekerja adalah sekedar mengumpulkan uang untuk kemudian kita nikmati. Entah itu makan di restauran yang enak, Happy Hours di Café, Bar, disko, karaoke, jalan-jalan ke luar negeri, belanja, pokoknya segala sesuatu yang sifatnya hadiah atas kerja keras kita.
Selain itu banyak orang berpikir bahwa bekerja adalah sekedar untuk mencari nafkah–sekedar untuk bertahan hidup. Padahal sesungguhnya bekerja adalah lebih dari sekedar mencari nafkah. Makna bekerja jauh lebih dalam dari sekedar itu semua. Bekerja adalah perwujudan misi atau keberadaan kita dalam tubuh manusia kita. Sebagai makhluk spiritual kita memiliki tugas atau maksud keberadaan kita di dunia. Jadi bekerja adalah kegiatan utama kita di dunia dan sebagai bagian penting dari perjalanan hidup kita untuk mencapai misi hidup dan takdir kita.
Oleh karena itu penting sekali bagi kita untuk menemukan pekerjaan yang sesuai dengan misi hidup kita. Pekerjaan yang dapat memberi kita perasaan istimewa, pekerjaan yang dapat memberi arti bagi kehidupan kita, pekerjaan yang kita cintai dan tekuni sepenuh hati. Ada banyak jenis pekerjaan yang mungkin pernah kita miliki atau lakukan, tetapi pasti hanya ada satu pola atau jalur yang akhirnya membawa kita kepada pencapaian misi hidup kita.
Dalam bukunya, Thick Face Black Heart, Chin-Ning Chu mengatakan bahwa kalau kita jujur terhadap pekerjaan yang ditugaskan kepada kita, maka takdir juga akan jujur kepada kita. Oleh karena itu, untuk menemukan misi dan tujuan hidup, kita harus mencintai pekerjaan kita. Namun, kita tidak dapat mencintainya sebelum kita memiliki sebuah pekerjaan. Jika sedang menganggur carilah pekerjaan meskipun itu paruh waktu (part-time). Apabila belum juga menemukan pekerjaan yang cocok, mungkin sudah saatnya mencoba usaha wiraswasta kecil-kecilan. Orang yang bekerja akan lebih percaya dan yakin pada dirinya sendiri untuk memenuhi seluruh kebutuhannya, dibandingkan orang yang terbiasa menyerahkan masalahnya kepada orang lain dan meminta belas kasihan.
Pekerjaan yang baik akan memberi kita sebuah kehidupan yang baik pula. Berkorban untuk menjadi yang terbaik yang bisa kita capai adalah suatu pernyataan cinta kepadanya. Sebagaimana yang dikatakan oleh Prabu Krishna dalam Bhagavad Gita:
Kalau Anda melakukan pengorbanan dalam melakukan tugas,
Anda tidak perlu melakukan apa-apa lagi.

Mengabdi pada tugas, orang mencapai kesempurnaannya.
Lebih jauh saya ingin mengatakan bahwa bekerja membuat kita menjadi lebih cerdas secara spiritual. Paling tidak kita memiliki perasaan menuju ke suatu tujuan (sense of purpose). Kita merasa bahwa kita memiliki arti baik bagi diri kita sendiri, bagi orang-orang yang kita cintai bahkan bagi bangsa dan umat manusia pada umumnya.
Pertanyaan yang sering muncul dalam pikiran kita adalah apakah pekerjaan saya saat ini sesuai dengan hati saya. Apakah yang saya jalani saat ini akan membawa saya kepada tujuan hidup, impian-impian dan misi hidup saya? Bagaimana saya tahu bahwa pekerjaan saya saat ini adalah yang terbaik dan paling pas buat kehidupan saya?
Untuk menjawab berbagai pertanyaan tersebut, saya ingin mengutip sebuah kutipan yang menjadi kutipan pembuka Bab 13 buku SQ: Connecting with Our Spiritual Intelligence karya Danah Zohar dan Ian Marshall, yang berbunyi: ”It is useless to waste your life on one path, especially if that path has no heart. Before you embark on a path, you ask the question: Does this path have a heart? If the answer is no, you will know it, and then you must choose another path. A path without heart is never enjoyable. You have to work hard even to take it. On the other hand, a path with heart is easy; it does not make you work at liking it.( Carlos Castaneda, The Teachings of Don Juan.)
Kutipan tersebut menunjukkan tanda atau indikator apakah pekerjaan kita adalah pekerjaan yang dapat menuntun kita kepada takdir kita atau tujuan hidup kita. Kuncinya adalah hati. Kita harus senantiasa bertanya: Apakah pekerjaanku saat ini memiliki hati? Apakah aku bekerja dengan hati?Apakah aku mencintai pekerjaanku? Apakah pekerjaanku ini akan membawaku kepada impian-impian dan tujuan hidupku? Apakah pekerjaan ini mendukung misi hidupku untuk menolong sesama? Jika jawabannya tidak, maka kita harus segera memilih jalan yang lain.
Dalam pandangan agama samawi (Yahudi, Kristen, Islam), manusia bekerja adalah karena kutukan dari Tuhan ketika manusia jatuh ke dalam dosa—ketika memakan buah pengetahuan baik dan buruk. Bekerja memang dapat diartikan sebuah keharusan bagi manusia karena setiap kita memiliki misi dalam keberadaan kita selama di dunia ini. Sebagai makhluk spiritual dalam wadag manusia, kita harus dapat menemukan jalan kehidupan (life path) yang harus kita jalani.
Jalan yang dimaksud di sini adalah menemukan makna hidup kita sendiri yang paling dalam, bertindak berdasarkan motivasi kita yang paling dalam, dan menjalankan tindakan tersebut demi keluarga dan orang-orang yang kita cintai, demi masyarakat-bangsa dan negara. Jalan kehidupan kita adalah pengembaraan kita dalam kehidupan sebagai manusia di dunia, hubungan kita, pekerjaan kita, tujuan dan impian kita, dan cara kita menjalani semua ini. Menurut Danah Zohar, dalam bukunya SQ: Connecting with Our Spiritual Intelligence, mengikuti jalan dengan kecerdasan spiritual, atau dengan hati, berarti bersikap teguh dan mengabdi.
Seseorang mungkin cukup beruntung telah dapat menemukan sebuah jalan hidup yang murni dengan hati ketika usianya masih muda. Namun tidak sedikit pula yang belum menemukan makna atau jalan hidupnya ketika usianya sudah menjelang senja. Tetapi sejarah membuktikan bahwa banyak sekali mereka yang mencapai makna hidupnya pada usia senja, sebagai contoh: Kolonel Sanders (Kentucky Fried Chicken), Ray Kroc (McDonalds), Michael Angelo (pelukis kubah Katedral Santo Petrus di Vatikan), Daniel Defoe (penulis buku Robinson Crusoe), dan masih banyak lagi.
Tujuan utama kita bekerja adalah menemukan makna dan merasakan getaran yang membimbing kita dalam mencapai takdir atau tujuan hidup kita.
Dalam beberapa episode kehidupan kita, seringkali kita berpikir benarkah jalan hidup yang saya lalui? Di sepanjang masa kehidupan, jalan spiritual utama seseorang sering berubah. Itu mungkin terjadi secara lambat laun, atau secara tiba-tiba ketika terjadi krisis setengah-baya (mid-life crisis) pada usia empat puluhan atau bahkan satu dasawarsa sesudahnya.
Menurut Danah Zohar dalam buku SQ: Connecting with our Spiritual Intelligence, tersebut Jika perubahan jalan spiritual utama kita adalah pergantian energi yang murni dan bukan semata-mata suatu episode traumatik, mungkin kita akan tetap bisa menerima dengan baik jalan kita yang sebelumnya sambil menambahkan dimensi-dimensi lain.
Saya sendiri menemukan jalan hidup ketika saya selesai menulis buku pertama. Menurut istilah Danah Zohar, saya menjalani jalan pengasuhan (nurturing), di mana misi hidup saya adalah untuk membimbing dan memberdayakan orang lain agar dapat menemukan potensi diri terbaiknya dan mencapai impian-impian mereka.
Melalui tulisan, buku, menjadi dosen, pembicara publik, saya mencoba mengaktualisasikan diri saya untuk mencapai misi hidup saya. Kemudian agar dapat menjangkau lebih banyak orang dan lebih cepat, saya dan sejumlah teman sejak awal tahun ini mulai membangun Q Society dengan cara pertumbuhan sel dan jaringan. Artinya saya membantu orang lain dalam sebuah kelompok kecil di mana setelah tiga bulan, setiap anggota kelompok akan dapat mulai membangun sebuah kelompok yang dipandunya.
Bekerja akhirnya haruslah menjadi sesuatu yang memberi makna pada kehidupan kita dan dapat membantu kita untuk mencapai impian-impian kita serta menuntun kita ke arah tujuan atau takdir kehidupan kita. Bekerja adalah sarana kita untuk mengamalkan misi hidup kita. Bekerja adalah tugas suci kita selama berada di dunia fana ini.
Sebagai makhluk spiritual, pekerjaan kita hanya satu yaitu bekerja untuk menjalankan misi hidup kita. Pekerjaan kita itulah cara kita untuk mewujudkan impian dan tujuan hidup kita. Pekerjaan kitalah yang akan membantu kita untuk bertumbuh secara spiritual.

Bekerja dengan Penuh Cinta
Ada sebuah kutipan yang menarik dalam wall paper komputer laptop saya yang berbunyi. ”There are many things that catch your eyes, but only a few that catch your heart. Pursue those.” Ada banyak hal yang menarik mata kita, tetapi sedikit sekali yang menarik hati kita. Kejarlah apa yang menarik hatimu itu.
Cinta terhadap sesuatu, termasuk pekerjaan atau hobi dapat mewujudkan sebuah prestasi yang gemilang dalam bidang pekerjaan atau hobi kita. Lakukan segala sesuatu dengan penuh rasa cinta, maka kita akan memperoleh hal-hal terbaik dalam bidang tersebut. Bekerja dengan penuh rasa cinta akan jauh berbeda dengan mereka yang bekerja karena uang semata.
Jika kita mencintai apa yang kita kerjakan sehari-hari, kita dapat meraih hasil yang terbaik. Semua orang yang sukses adalah mereka yang mencintai apa yang mereka kerjakan.
Sebagai teladan kita lihat Warren Buffet, salah seorang terkaya di dunia. Pada suatu hari dalam sebuah seminar di Universitas Nebraska dia ditanya rahasia kesuksesannya. Dia menjawab bahwa apa yang dia lakukan tidak ada yang istimewa, ”Saya tidak berbeda dari Anda sekalian,” katanya. ”Jika ada, perbedaannya hanya bahwa saya bangun setiap pagi dan memiliki kesempatan untuk melakukan apa yang saya cintai setiap harinya.”
Dengan melakukan apa yang kita cintai untuk orang-orang yang kita cintai, kita akan memperoleh hal-hal terbaik yang dapat ditawarkan kehidupan ini kepada kita. Intinya, cintai pekerjaan kita atau carilah pekerjaan yang kita cintai. Banyak orang sukses karena menekuni dan melakukan hal-hal yang mereka cintai dengan kesungguhan hati. n

Source : Anonime, internet !

Victims of their own success

2008-04-30T03:19:00.000-07:00

European ports have found themselves in the unaccustomed position of being a
high-growth business. Hutchison Whampoa, whose Hutchison Port Holdings
subsidiary has large investments in the region, now is making more money
from port operations than from its formerly high-flying mobile-phone
business.
But instead of celebrating, terminal operators are sweating about the
prospect of overstretched European ports being strangled by a second
consecutive year of peak-season congestion.
No port better sums up the sector's changed fortunes than Rotterdam. Its
container traffic fell for the first time in 2002, fanning fears that it
would surrender its position as Europe's top container hub to its aggressive
rivals, particularly neighboring Antwerp and Hamburg. But it rebounded in
spectacular fashion in 2003 with a 9 percent increase in traffic that made
it the first non-Asian port to handle more than 7 million TEUs a year.
That performance was eclipsed in 2004, when shipments soared 16 percent to
8.2 million TEUs. Through March of this year, the port was on pace to exceed
9 million TEUs in 2005.
The boom is driven almost exclusively by containers, reflecting the growth
in global world trade, rather than bulk cargoes, which are registering
steady but unspectacular growth. Hans Smit, chief executive of the Port of
Rotterdam, predicts containers will become the port's highest-tonnage cargo
within two years, surpassing crude oil.
Fears that the boom was merely a blip and would soon lose momentum have
ebbed as traffic continues strong growth from Le Havre to Hamburg. The
increase has been driven by trade with China, which last year supplanted the
U.S. as Rotterdam's main trading destination.
But China isn't the sole driver of the boom. A surge in exports from other
Asian nations, including South Korea and Japan, explains why Europe-bound
ships are sailing fully loaded. The EU's expansion to include eight Central
and East European countries last May also has boosted trade through Hamburg
and, to a lesser extent, Rotterdam.
Regional feeder routes also are flourishing, with Rotterdam attributing its
strong first-quarter performance to robust growth on intra-European trade as
well as to and from Asia and South America. Hamburg and Rotterdam are
benefiting from a surge in Russia's foreign trade through the Baltic, and,
because of the weak dollar, all Northwest European ports are importing more
from the U.S.
That has shipping lines worried as they gear up for this year's peak season
for imports. The prospect of double-digit growth in container traffic is
welcome but "makes us all nervous," Chris Bourne, European managing director
of Japanese carrier MOL, told a recent conference on port congestion.
Ocean carriers, terminal operators, barge operators, truckers and shippers
have drawn up contingency plans to cope with congestion, but many fear the
situation is set to worsen until more handling capacity can be added.
Dynamar, a Rotterdam-based consulting group, said port capacity will be
strained for several more years. Many terminals have been operating well
above 80 percent since the 2004 peak season, when European ports suffered
their first bout of congestion.
Carriers also worry that Europe's increasingly congested ports will be
unable to handle the increasingly large ships entering service. Orient
Overseas Container Line said Rotterdam and Antwerp are the only European
ports that will meet the carrier's requirements when it is operating a dozen
8,000-TEU vessels in its services from Asia in 2007.
The top U.K. container ports, Felixstowe and Southampton, are expected to be
congested again this year. The delays are likely to spread to Rotterdam,
which will have to accept diverted containers from Asia and transfer them
onto to feeder vessels for onward shipment to smaller, less-crowded British
ports.
The threat of congestion holds hope for Amsterdam, which is one of Europe's
biggest ports but has a negligible container business. The port's Ceres
Paragon terminal, built around a slip where a ship can be worked
simultaneously from port and starboard, has handled only a couple of ships
since it opened five years ago. The Grand Alliance was expected to switch
some of its Asian services from Rotterdam to Amsterdam after one of its
members, NYK Line, acquired control of the facility. The move has been
vetoed by another alliance member, P&O Nedlloyd, which did not want to
jeopardize its investment in a new Rotterdam terminal it is building with
Hutchison Port Holdings, the owner of Europe Container Terminals.
But with Hapag-Lloyd saying it backs a move, Amsterdam soon could be more
than a blip in the Le Havre-Hamburg container market.
Also expected to alleviate the congestion are several multibillion-dollar
projects that will boost the annual capacity of Northwest European ports by
some 15 million TEUs. Most won't be finished until the next decade, however.
Antwerp is best placed to ward off the congestion that forced it to turn
away 10,000 boxes a week last year to rival Rotterdam. The first phase of
the port's Deurganckdok terminal is scheduled to open in July, boosting
capacity by about 800,000 TEUs a year. Another terminal is scheduled to open
nearby in November.
The northern French port of Le Havre, which has failed to exploit is
position as the main port of Europe's second-largest economy, will get
another chance to win back domestic cargoes from foreign rivals at the end
of the year with the opening of a terminal designed to handle 1.5 million
TEUs a year.
Congestion also will provide a major boost for Zeebrugge. The Belgian port
posted an 18.5 percent jump in traffic to 1.2 million TEUs last year but has
yet to make a breakthrough as a major container port in Northwest Europe.

Source : Journal of Commerce BY BRUCE BARNARD

The New theory, solution for the traveling salesman problem.

2008-04-25T03:26:00.000-07:00

A new theory on what may be a significant advance in mathematics
was introduced. During a two-hour presentation by Dr. Anang Z. Gani, a
senior lecturer in the Departement of Industrial Engineering at Bandung
Institute of Technology (ITB). Dr. Gani's theory which he calls the
"interaction" theory was introduced before an inter-disciplinary audience of
ITB's faculty members, students and journalists. The presentations was held
in a seminar room in the building housing the ITB Departement of Industrial
Engineering.

Dr. Gani claims that his new theory will permit the development of much more
efficient algorithms for solving combinatorial optimization problems, which
are problems where the number of possible solutions increases in proportion
to the number of possible combinations of the values of the variables concerned.

Operations Research
These problems pose serious computational difficulties because even small
problems can possess a very large number of possible solutions. The result
is that great deal of valueable computer time used up in determining the
optimum answer, despite the fact that all combinatorial optimization
techniques eximine only a small fraction of all feasible solutions. If the
interaction theory does stand up under critical appraisal, it will
revolutionize the mathematical field known as operations research. Operation
research is the colective name for a group of mathematical optimization
techniques, that are extensively utilized by companies all over the world,
if Dr. Gani's claims can be subtantisted, the potential savings run into the
tens of millions of dolars.

Traveling Salesman Problem
Particularly interesting is Dr. Gani's claims that the interaction theory
guarantees an optimal solution to the traveling salesman problem, a problem
that has defied solution until now. Stated briefly, the traveling salesman
problem concern itself with attemting to find a route that enables each node
(city, building, area etc.) in a network to be visited exactly once, with
the provision that we start and end the route at the same node. All attempt
to find an algorithm that guarantees an optimum solutions have until now
failed, despite years of sustained effort by many brilliant researchers.
Existing methods for solving the TSP produce solutions that are only
approximately optimal. To disaapointment of the present, Dr Gani's
presentations did not discuses the theoretica basis of his theory. Turning
aside requests for a rigorous mathematical proof, Dr. Gani hinted the he
would provide detailed justification of his theory is based on a special
project that Dr. Gani undertook as a student at the Georgia Institute of
Thechnology in 1965. The project was attempt to develop a mathematical model
that could help engineers trying solve material handling problems
encountered during the design of plant layouts. The final verdict on the
interaction theory is not in yet.
Academic debate about the virtues and the shortcomings of this new theory
will have to await Dr. Gani's release of its theoritical justifications.

Source : The Jakarta Post

Understanding Office Politik.

2008-04-25T03:24:00.000-07:00

Sebagaimana sebuah negara, kantor juga mempunyai politik, tak terkecuali kantor anda.Sebagai? warga negara? yang baik, semestinya anda memahami arah politik kantor anda, karena mau tidak mau anda bersinggungan dengan hal ini dan tak mungkin menghindarinya begitu saja.Mungkin anda beranggapan istilah ?politik? terlalu mengerikan dan berkootasi negatif karena hal-hal yang berbau politik itu selalu berkaitan dengan intrik-intrik dan kelicikan. Memang, kalau tak pandai-pandai, Anda bisa terjebak di dalamnya, atau lebih buruk lagi Anda menjadi? korban politik?.Sebelum itu terjadi , ada strategi-strategi yang perlu anda ketahui.

Apa itu politik kantor?
Sederhananya, politik kantor adalah suatu cara memanfaatkan lingkungan kerja kita dengan tujuan agar pekerjaan, tugas, dan tanggung jawab kita terselesaikan atau tercapai dengan baik sesuai harapan kita.Boleh dibilang, tak ada satu kantor pun yang tidak mempunyai politik.Mengapa? karena, dalam suatu kantor terdapat beberapa orang dengan tugas serta tanggung jawab berbeda, yang menyebabkan tiap-tiap orang mempunyai siasat untuk sampai ke tujuan masing-masing, baik yang diupayakannya sendiri maupun secara berkelompok.Jika setiap orang melakukan hal yang sama sehingga tercapai iklim kompetisi yang sehat, maka politik di kantor itu sehat.
Dengan kata lain, setiap orang mempunyai strategi dan kepekaan sendiri-sendiri dalam menangkap isyarat-isyarat dari lingkungannya dan menentukan tindakan-tindakan yang menurutnya paling tepat untuk diambil.

Politik selalu identik dengan intrik?
Politik di tempat kerja memang sering kali dikonotasikan negatif dan identik dengan intrik-intrik.Hal ini terjadi karena yang tercipta adalah suasana kompetisi yang negatif, dimana tujuan utamanya adalah mencengkramkan kekuasaaan dan pengaruh yang kuat, bukan lagi memberi kontribusi yang memadai kepada perusahaan.Padahal, jika tujuan yang ingin dicapai lewat berpolitik itu adalah kulaitas kerja yang lebih baik, tidak semata-mata karena ambisi untuk meraih posisi tanpa mengindahkan hal-hal lain, maka politik yang berjalan adalah politik kantor yang benar.

Perlukah kita mempedulikan politik kantor?
Ya! Pertama, agar pekerjaan bisa anda selesaikan dengan lancar, karena anda tahu celah-celah sulit dan bagaimana menembusnya degnan cara taktis.kedua, agar anda mengenal sekeliling anda dan tidak salah langkah.Orang yang tidak mau mengenal politik kantor , ibarat katak dalam tempurung, karena ia tidak tahu apa-apa.Lebih jauh lagi, ketidaktahuan ini bisa berakibat buruk.misalnya anda menganggap salah satu rekan kerja anda sebagai teman kerja yang baik, tanpa menyadari bahwa ia sedang memeanfaatkan anda sebagai salah satu?bidak catur? untuk kepentingan ambisinya.

Bagaimana mengenali politik di kantor kita?
anda harus rajin melakukan pengamatan , menjadi orang yang terbuka(suka menyerap informasi dan bertanya), menciptakan kesan bahwa anda bisa dipercaya.Namun, yang tak kalah penting, anda diharapkan pandai menciptakan komunikasi serta interaksi yang bersifat netral.dengan begitu, informasi yang anda butuhkan bisa segera anda dapatkan, dan proses pengenalan anda bisa berjalan mulus.

Politik kantor hanya dilakukan oleh posisi menengah ke atas
Tidak.Siapapun bisa berpolitik.Orang-orang dengan jabatan tingi belum tentu bisa menciptakan suatu atmosfer yang memicu timbulnya politik.Bisa jadi yang memenentukan adalah orang-orang yang ada di bawahnya, tetapi mempunyai pengaruh cukup kuat.Di kalangan bawah, politik pun bisa bergulir.misalnya, mereka berkolompok untuk mendapatkan informasi rahsia dan sengaja membuat geger perusahaan untuk menekan pihak manajemen.Oleh sebab itu, sebaiknya anda berhati-hati jika ingin melibatkan diri dalam politik kantor.Anda tahu risiko yang akan anda pikul.
( next………office politik !)

Source : Anonime , internet source.

Maximize Yourself, Do it now !

2008-04-25T03:23:00.000-07:00

Bagi anda pecinta basket, saya kira sudah sangat paham betul aturan permainan di dalamnya. Untuk mendapat 3 point dalam satu kali lemparan, sang pemain harus melempar di luar garis 3 point yang ada. Logikanya pemain tersebut harus melempar lebih kuat jika ingin memasukkan bola ke dalam keranjang dibandingkan dia ada di dalam garis tersebut. Contoh lain adalah pemain golf, apabila dia ingin memasukkan bola ke dalam hole yang letaknya lebih jauh maka otomatis dia harus mengayunkan stick golfnya lebih kencang.

Hal serupa terjadi dalam hidup anda, jika ingin mendapat hasil yang optimal sesuai harapan anda, maka konsekuensinya anda harus mau dan mampu memaksimalkan kemampuan anda. Banyak orang memiliki perspektif yang salah, di mana mereka mau mendapat hasil yang maksimal tapi enggan untuk memaksimalkan potensi dirinya sendiri. Saya ingat sebuah pepatah mengatakan “Apa yang kau tanam itulah yang akan kau tuai” Sangatlah adil memang jika anda mengeluarkan usaha yang begitu minim, maka mendapat hasil yang minim pula. Usaha yang dikeluarkan sangat maksimal, maka hasilnya pun akan maksimal.

Maksimal yang seperti apa yang seharusnya dilakukan? Apakah harus bekerja terus menerus sampai anda kelelahan? Atau kerja keras tanpa menghiraukan waktu? Setiap orang mungkin memiliki pandangan yang berbeda dan sah-sah saja, tapi salah satu yang cukup efektif untuk dilakukan adalah memaksimalkan potensi diri khususnya talent (bakat) yang anda miliki.

Setiap manusia diciptakan Tuhan memiliki talent yang berbeda, ada yang mahir dalam dunia musik, pandai dalam ilmu eksakta, paham dengan dunia programing, mahir dalam olahraga, atau bidang lainnya. Tidak ada manusia diciptakan tidak memiliki sebuah talent, jika ada yang mengatakan “Saya tidak memiliki talent” maka orang tersebut bukannya tidak ada melainkan belum mencari dan menggali lebih dalam. Anda harus mengidentifikasi sendiri apa yang menjadi kegemaran anda, dan pada bidang apa anda merasa dapat lebih maksimal dibandingkan dengan bidang yang lain. Jika anda sudah menemukan, mulailah untuk dikembangkan dan dimaksimalkan.

Tidak ada manusia yang diciptakan memiliki talent yang lebih dibanding yang lain, tidak ada talent yang porsinya lebih besar di antara manusia. Menurut saya semua hal tersebut diberikan dalam ukuran yang sama. Yang membedakan adalah apakah anda mau memperbesar dan memaksimalkan talent anda tersebut atau hanya membiarkannya saja. Deretan orang sukses dibidangnya masing-masing seperti Bill Gates, Beethoven, Michael Jordan, bukan semata-mata karena mereka memiliki talent lebih dari anda, tapi mereka mau memaksimalkan talent tersebut.

Saya pernah membaca sebuah artikel yang menggambarkan sebuah perumpamaan seperti ini: bayangkan sebuah kolam air yang tenang, jika anda ingin membuat gelombang di antaranya anda harus melemparkan batu yang cukup besar ke dalamnya. Apabila kerikil yang anda lempar maka gelombang yang dihasilkanpun kecil. Membentuk Batu besar atau batu kerikil tergantung dari anda apakah mau memaksimalkan potensi anda menjadi sebuah batu besar atau cukup dengan kerikil saja. Jika anda mau menciptakan gelombang yang lebih besar dalam hidup anda, anda tahu batu mana yang diperlukan. You will never grow if you never maximize yourself.

Source : Anonime, Internet source .

Simple Mixed Model Scheduling

2008-04-25T03:21:00.000-07:00

Mixed-model scheduling is a highly visible change in the Production scheduling of the products with different models or specifications. The product range is wide and extends from Paints, Chemicals, Paper, Engineering, Plastics, Synthetic Yarn, Consumer goods, Food and Plastic products etc.
Prior to MMS, the conventional approach in most companies has been to “batch-build” products to gain the cost advantage that has come with large batch quantities. MMS however, forces us to minimize the batch sizes, while sacrificing neither productivity nor incurring extra costs.
Mixed model scheduling works like this. If there were three products being built – Product A was 50 percent of total volume, Product B was 25 percent of the volume and Product C the remaining 25 percent, a company would attempt to schedule these three each day as follows:

Day 1 Day 2 Day 3

A,B,A,C A,B,A,C A,B,A,C

Obviously, every other product is the popular one and the other two are interwoven.
There are two incentives for doing this, externally to the customer and internally to the factory and suppliers. The advantage externally is that by making products frequently, you can offer quick delivery to marketplace without having to carry the sizeable finished goods inventory.
MMS reduces the customer – response time up to 80%
Prior to MMS, in the anxiety building higher batch sizes, a Production schedule will include firm-order with yet to be booked orders. Besides increasing customer response time, the earlier approach creates a crisis when the “Yet to be booked” orders do not materialize and other models get booked. This triggers a chain of mutual retributions between marketing and Production. Such situations are the cause of continuing functional confrontations and non-co-operation.
A JIT company normally always builds what customer need, rather than periodically building batches. This is accomplished first by reducing lead times and cycle times. This reduces the time for model to model change to almost one forth. The system improves the sales opportunities due to better customer response time.

Source : Tushar Kulkarni - Accenture

Best Tips for practical retail supply chain.

2008-04-25T03:20:00.000-07:00

As merchants and buyers continue to take on more and more responsibility for product concepts, their development, and margin potential, it's important to understand what best practices get those products to market. There's art and science to getting the right product to the right store at the right time and at the right price point. At TradeStone, we provide the infrastructure for both the design and development. The right product hinges upon the buyer's decision: what items will I source, what are its attributes, and where will I find it.
In essence, this is what TradeStone calls the Unified Buying Process. This means that it should be just as easy to source flip flops, mp3 players, or drumsticks from 6,000 miles away as it would be to have them manufactured across the street.
This leads us to the first best practice: evaluate your product portfolio in terms of margin potential. It is a well-known fact that domestically-sourced items carry a mark-up of 45 percentage points. That same item, sourced overseas, can command a mark-up of 65 percentage points. It's easy to see that a strategically weighted portfolio can dramatically increase department and store revenue figures.
Now it has to be easy to share product attributes and specifications and work back and forth on fabrications and colors, quality testing, sampling, and production. With the product constantly evolving, and profitability on the line, it's easy to see that the next best practice has to be the ability to normalize communications and collaboration with vendors. What does this mean? It means that RFQs should be delivered to each supplier adjusted for their language, their currency, their time zone. This means that the supplier can simply respond with the best cost per item they can offer, the best lead time they can offer, and any recommendations for variations. Why is this important? With this apples-to-apples comparison of vendor capabilities, pricing, and lead time, the Buyer can make the best supplier determination based on product profitability.
With the order placed, the next best practice is to establish the production milestones for all the components, quality tests, fit evaluations, and packaging, bringing together all the supply chain stakeholders with exception-based alerting and workflows. With this critical information on their dashboards, designers, merchants, buyers, and factories are able to react quickly to color dips, sampling requests, and the myriad of quality tests.
This true collaboration capability between Buyers and Vendors leads to the next best practice: using the Purchase Order as the central repository for all product refinement and change requests. So often in Retail, the CFO has no visibility into the received orders, the committed-to orders, and the outstanding requests-for-quote. Nor is there any visibility into what quality tests have failed and the where-used ripple effect this has throughout the program. Nor is it always clear when or why quantities changed, transportation modes changed, or attributes changed. These changes can all be captured with true collaboration in the live purchase order document, visible to all supply chain stakeholders. With the order as the central repository, all packing list and customs documentation is kept up-to-date with no need to re-key changes. With the purchase order as the central repository, all planning reports are kept up-to-date with no clerical data entry. With the purchase order as the central repository, all shipment alerts are kept up-to-date with no surprises for warehouses and distribution centers.
By designating the purchase order as central to all transactions, we can achieve our next best practice: C-TPAT compliance. Instead of scrambling for customs notification, digging through HTS codes, and maintaining country quota spreadsheets, TradeStone customers are literally sailing through customs. By maintaining country of origin, value, and product classification in the purchase order, the vendor simply needs to drag and drop line items from the purchase order document to their packing list. This packing list information now feeds data to the commercial and service invoices, all without data entry resources.
And with Tier 3 C-TPAT compliance in check, it's easy to move forward to our next best practice: 10 Plus 2 compliance. As you can see, by simply using the purchase order as the keystone for all transaction data, 10 Plus 2 compliance becomes second nature. The new initiative asks for Manufacturer, Seller, Consolidator, Buyer and Ship to names and addresses, Container stuffing location, Importer and Consignee record numbers, Country of origin of goods and the Commodity Harmonized Tariff Schedule number. The 2 additional data sets are: Vessel Stowage Plan (or BAPLIE), and Container Status Messages filed by the carrier.
These best practices not only ensure that supply chains will be efficient, but also that they will be secure. They will be able to turn on a dime as market testing results come in, quickly switching out colors, fabrications, and attributes. When all is said and done, the ultimate best practice is giving the consumer what they want

Source : ALI (Assosiasi Logistic Indonesia)

Indentified Top Ten Trends in SCM and Logistics

2008-04-25T03:19:00.000-07:00

Global supply chains displayed gains in efficiency and customer service during 2007, but many companies took supply chain management (SCM) a few steps further by enhancing flexibility, responding effectively to demand variation, and adopting environmentally friendly practices. As for 2008, AMR Research has identified the top ten trends in SCM and logistics for the coming year.

1. SCM and logistics technology markets will enjoy healthy growth. The average increase on spending this year will be 12 percent.
2. Near-shoring presents a viable alternative to low-cost country off shoring. Companies are reviewing nearby outsourcing to enhance speed. Plus, nearby outsourcing may actually be less expensive when the hidden costs of low-cost manufacturing are factored in.
3. Best-of-breed vendors regain some ground lost to ERP competitors. ERP may be easy, but users still show a preference for best-of-breed.
4. SCM outsourcing alleviates the SCM talent shortage in increasingly complex global supply chains.
5. Companies manage risk for business continuity and competitive advantage. Emphasis on supply chain risk mitigation will grow in 2008.
6. Impressive returns on investment from current projects nudge RFID back into the spotlight. Now that the wave of compelled adoption has passed, RFID is ready to prove its worth on its own terms.
7. Software vendors expand their managed-services offering to deliver results.
8. S&OP technologies - not just processes - take center stage. Expect a wider adoption of sales and operations planning (S&OP) functionality in 2008.
9. Connectivity grows in importance as companies extend their value networks.
10. What-if analysis and simulation-based tools see growing adoption

Source : Supply Chain Management Review, 1/30/2008

Optimizing Economic Order Quantity (EOQ)

2008-04-23T06:01:00.000-07:00

Inventory models for calculating optimal order quantities and reorder points have been in existence long before the arrival of the computer. When the first Model T Fords were rolling off the assembly line, manufacturers were already reaping the financial benefits of inventory management by determining the most cost effective answers to the questions of When? and How much?. Yes long before JIT, TQM, TOC, and MRP, companies were using these same (then unnamed) concepts in managing their production and inventory. I recently read Purchasing and Storing, a textbook that was part of a “Modern Business Course” at the Alexander Hamilton Institute in New York. The textbook published in 1931 (that’s right 1931) was essentially a how to book on inventory management in a manufacturing environment. If you’re wondering why I would want to read a 70-year-old business text, my answer would be that the fundamental concepts of managing a business change very little with time, and reading about these concepts in a vintage text is a great way to reinforce the value of the fundamentals. The occasional reference to “The War” (referring to WWI) also keeps it interesting and the complete absence of acronyms is refreshing.
As you may have guessed, this 70-year-old book contained a section on Minimum Cost Quantity, which is what we now refer to as Economic Order Quantity (EOQ). I can imagine that in the 1930’s an accountant (or more likely a room full of accountants) would have calculated EOQ or other inventory related formulas one item at a time in a dimly lit office using the inventory books, a mechanical adding machine and a slide rule. Time consuming as this was, some manufacturers of the time recognized the financial benefits of taking a scientific approach to making these inventory decisions.
So why is it that, in these days of advanced information technology, many companies are still not taking advantage of these fundamental inventory models? Part of the answer lies in poor results received due to inaccurate data inputs. Accurate product costs, activity costs, forecasts, history, and lead times are crucial in making inventory models work. Ironically, software advancements may also in part to blame. Many ERP packages come with built in calculations for EOQ which calculate automatically. Often the users do not understand how it is calculated and therefore do not understand the data inputs and system setup which controls the output. When the output appears to be "out of whack" it is simply ignored. This sometimes creates a situation in which the executives who had purchased the software incorrectly assume the material planners and purchasing clerks are ordering based upon the systems recommendations. I should also note that many operations will find these built-in EOQ calculations inadequate and in need of modifications to deal with the diversity of their product groups and processes.
Corporate goals and strategies may sometimes conflict with EOQ. Measuring performance solely by inventory turns is one of the most prolific mistakes made in the name of inventory management. Many companies have achieved aggressive goals in increasing inventory turns only to find their bottom line has shrunk due to increased operational costs.
EOQ is essentially an accounting formula that determines the point at which the combination of order costs and inventory carrying costs are the least. The result is the most cost effective quantity to order. In purchasing this is known as the order quantity, in manufacturing it is known as the production lot size.
While EOQ may not apply to every inventory situation, most organizations will find it beneficial in at least some aspect of their operation. Anytime you have repetitive purchasing or planning of an item, EOQ should be considered. Obvious applications for EOQ are purchase-to-stock distributors and make-to-stock manufacturers, however, make-to-order manufacturers should also consider EOQ when they have multiple orders or release dates for the same items and when planning components and sub-assemblies. Repetitive buy maintenance, repair, and operating (MRO) inventory is also a good application for EOQ. Though EOQ is generally recommended in operations where demand is relatively steady, items with demand variability such as seasonality can still use the model by going to shorter time periods for the EOQ calculation. Just make sure your usage and carrying costs are based on the same time period.
Doesn’t EOQ conflict with Just-In-Time? While I don’t want to get into a long discussion on the misconceptions of what Just-In-Time (JIT) is, I will address the most common misunderstanding in which JIT is assumed to mean all components should arrive in the exact run quantities “just in time” for the production run. JIT is actually a quality initiative with the goal of eliminating wasted steps, wasted labor, and wasted cost. EOQ should be one of the tools used to achieve this. EOQ is used to determine which components fit into this JIT model and what level of JIT is economically advantageous for your operation. As an example, let us assume you are a lawn equipment manufacturer and you produce 100 units per day of a specific model of lawn mower. While it may be cost effective to have 100 engines arrive on your dock each day, it would certainly not be cost effective to have 500 screws (1 days supply) used to mount a plastic housing on the lawn mower shipped to you daily. To determine the most cost effective quantities of screws or other components you will need to use the EOQ formula.
The basic Economic Order Quantity (EOQ) formula is as follows:

The Inputs
While the calculation itself is fairly simple the task of determining the correct data inputs to accurately represent your inventory and operation is a bit of a project. Exaggerated order costs and carrying costs are common mistakes made in EOQ calculations. Using all costs associated with your purchasing and receiving departments to calculate order cost or using all costs associated with storage and material handling to calculate carrying cost will give you highly inflated costs resulting in inaccurate results from your EOQ calculation. I also caution against using benchmarks or published industry standards in calculations. I have frequently seen references to average purchase order costs of $100 to $150 in magazine articles and product brochures. Often these references trace back to studies performed by advocacy agencies working for business that directly benefit from these exaggerated (my opinion) costs used in ROI calculations for their products or services. I am not denying that some operations may have purchase costs in this range, especially if you are frequently re-sourcing, re-quoting, and/or buying from overseas vendors. However if your operation is primarily involved with repetitive buying from domestic vendors — which is more common — you’ll likely see your purchase order costs in the substantially lower $10 to $30 range.
As you prepare to undertake this project keep in mind that even though accuracy is crucial, small variances in the data inputs generally have very little effect on the outputs. The following breaks down the data inputs in more detail and gives insight into the aspects of each.

Annual Usage.
Expressed in units, this is generally the easiest part of the equation. You simply input your forecasted annual usage.

Order Cost.
Also known as purchase cost or set up cost, this is the sum of the fixed costs that are incurred each time an item is ordered. These costs are not associated with the quantity ordered but primarily with physical activities required to process the order.
For purchased items, these would include the cost to enter the purchase order and/or requisition, any approval steps, the cost to process the receipt, incoming inspection, invoice processing and vendor payment, and in some cases a portion of the inbound freight may also be included in order cost. It is important to understand that these are costs associated with the frequency of the orders and not the quantities ordered. For example, in your receiving department the time spent checking in the receipt, entering the receipt, and doing any other related paperwork would be included, while the time spent repacking materials, unloading trucks, and delivery to other departments would likely not be included. If you have inbound quality inspection where you inspect a percentage of the quantity received you would include the time to get the specs and process the paperwork and not include time spent actually inspecting, however if you inspect a fixed quantity per receipt you would then include the entire time including inspecting, repacking, etc. In the purchasing department you would include all time associated with creating the purchase order, approval steps, contacting the vendor, expediting, and reviewing order reports, you would not include time spent reviewing forecasts, sourcing, getting quotes (unless you get quotes each time you order), and setting up new items. All time spent dealing with vendor invoices would be included in order cost.
Associating actual costs to the activities associated with order cost is where many an EOQ formula runs afoul. Do not make a list of all of the activities and then ask the people performing the activities "how long does it take you to do this?" The results of this type of measurement are rarely even close to accurate. I have found it to be more effective to determine the percentage of time within the department consumed performing the specific activities and multiplying this by the total labor costs for a certain time period (usually a month) and then dividing by the line items processed during that same period.
It is extremely difficult to associate inbound freight costs with order costs in an automated EOQ program and I suggest it only if the inbound freight cost has a significant effect on unit cost and its effect on unit cost varies significantly based upon the order quantity.
In manufacturing, the order cost would include the time to initiate the work order, time associated with picking and issuing components excluding time associated with counting and handling specific quantities, all production scheduling time, machine set up time, and inspection time. Production scrap directly associated with the machine setup should also be included in order cost as would be any tooling that is discarded after each production run. There may be times when you want to artificially inflate or deflate set-up costs. If you lack the capacity to meet the production schedule using the EOQ, you may want to artificially increase set-up costs to increase lot sizes and reduce overall set up time. If you have excess capacity you may want to artificially decrease set up costs, this will increase overall set up time and reduce inventory investment. The idea being that if you are paying for the labor and machine overhead anyway it would make sense to take advantage of the savings in reduced inventories.
For the most part, order cost is primarily the labor associated with processing the order, however, you can include the other costs such as the costs of phone calls, faxes, postage, envelopes, etc.

Carrying cost.
Also called Holding cost, carrying cost is the cost associated with having inventory on hand. It is primarily made up of the costs associated with the inventory investment and storage cost. For the purpose of the EOQ calculation, if the cost does not change based upon the quantity of inventory on hand it should not be included in carrying cost. In the EOQ formula, carrying cost is represented as the annual cost per average on hand inventory unit. Below are the primary components of carrying cost.
Interest. If you had to borrow money to pay for your inventory, the interest rate would be part of the carrying cost. If you did not borrow on the inventory, but have loans on other capital items, you can use the interest rate on those loans since a reduction in inventory would free up money that could be used to pay these loans. If by some miracle you are debt free you would need to determine how much you could make if the money was invested.
Insurance. Since insurance costs are directly related to the total value of the inventory, you would include this as part of carrying cost.
Taxes. If you are required to pay any taxes on the value of your inventory they would also be included.
Storage Costs. Mistakes in calculating storage costs are common in EOQ implementations. Generally companies take all costs associated with the warehouse and divide it by the average inventory to determine a storage cost percentage for the EOQ calculation. This tends to include costs that are not directly affected by the inventory levels and does not compensate for storage characteristics. Carrying costs for the purpose of the EOQ calculation should only include costs that are variable based upon inventory levels.
If you are running a pick/pack operation where you have fixed picking locations assigned to each item where the locations are sized for picking efficiency and are not designed to hold the entire inventory, this portion of the warehouse should not be included in carrying cost since changes to inventory levels do not effect costs here. Your overflow storage areas would be included in carrying cost. Operations that use purely random storage for their product would include the entire storage area in the calculation. Areas such as shipping/receiving and staging areas are usually not included in the storage calculations. However. if you have to add an additional warehouse just for overflow inventory then you would include all areas of the second warehouse as well as freight and labor costs associated with moving the material between the warehouses.
Since storage costs are generally applied as a percentage of the inventory value you may need to classify your inventory based upon a ratio of storage space requirements to value in order to assess storage costs accurately. For example, let's say you have just opened a new E-business called "BobsWeSellEverything.com". You calculated that overall your annual storage costs were 5% of your average inventory value, and applied this to your entire inventory in the EOQ calculation. Your average inventory on a particular piece of software and on 80 lb. bags of concrete mix both came to $10,000. The EOQ formula applied a $500 storage cost to the average quantity of each of these items even though the software actually took up only 1 pallet position while the concrete mix consumed 75 pallet positions. Categorizing these items would place the software in a category with minimal storage costs (1% or less) and the concrete in a category with extreme storage costs (50%) that would then allow the EOQ formula to work correctly.
There are situations where you may not want to include any storage costs in your EOQ calculation. If your operation has excess storage space of which it has no other uses you may decide not to include storage costs since reducing your inventory does not provide any actual savings in storage costs. As your operation grows near a point at which you would need to expand your physical operations you may then start including storage in the calculation.
A portion of the time spent on cycle counting should also be included in carrying cost, remember to apply costs which change based upon changes to the average inventory level. So with cycle counting, you would include the time spent physically counting and not the time spent filling out paperwork, data entry, and travel time between locations.
Other costs that can be included in carrying cost are risk factors associated with obsolescence, damage, and theft. Do not factor in these costs unless they are a direct result of the inventory levels and are significant enough to change the results of the EOQ equation.

Variations
There are many variations on the basic EOQ model. I have listed the most useful ones below.
• Quantity discount logic can be programmed to work in conjunction with the EOQ formula to determine optimum order quantities. Most systems will require this additional programming.
• Additional logic can be programmed to determine max quantities for items subject to spoilage or to prevent obsolescence on items reaching the end of their product life cycle.
• When used in manufacturing to determine lot sizes where production runs are very long (weeks or months) and finished product is being released to stock and consumed/sold throughout the production run you may need to take into account the ratio of production to consumption to more accurately represent the average inventory level.
• Your safety stock calculation may take into account the order cycle time that is driven by the EOQ. If so, you may need to tie the cost of the change in safety stock levels into the formula.

Implementing EOQ
There are primarily two ways to implement EOQ. Both methods obviously require that you have already determined the associated costs. The simplest method is to set up your calculation in a spreadsheet program, manually calculate EOQ one item at a time, and then manually enter the order quantity into your inventory system. If your inventory has fairly steady demand and costs and you have less than one or two thousand SKUs you can probably get by using this method once per year. If you have more than a couple thousand SKUs and/or higher variability in demand and costs you will need to program the EOQ formula into your existing inventory system. This allows you to quickly re-calculate EOQ automatically as often as needed. You can also use a hybrid of the two systems by downloading your data to a spreadsheet or database program, perform the calculations and then update your inventory system either manually or through a batch program. Whichever method you use you should make sure to follow the following steps:
• Test the formula. Prior to final implementation you must test the programming and setup. Run the EOQ program and then manually check the results using sample items that are representative of the variations of your inventory base.
• Project results. You'll need to run a simulation or use a representative sampling of items to determine the overall short-term and long-term effects the EOQ calculation will have on warehouse space, cash flow, and operations. Dramatic increases in inventory levels may not be immediately feasible, if this is the case you may temporarily adjust the formula until arrangements can be made to handle the additional storage requirements and compensate for the effects on cash flow. If the projection shows inventory levels dropping and order frequency increasing, you may need to evaluate staffing, equipment, and process changes to handle the increased activity.
• Maintain EOQ. The values for Order cost and Carrying cost should be evaluated at least once per year taking into account any changes in interest rates, storage costs, and operational costs.
A related calculation is the Total Annual Cost calculation. This calculation can be used to prove the EOQ calculation. Total Annual Cost = [(annual usage in units)/(order quantity)(order cost)]+{[.5(order quantity)+(safety stock)]*(annual carrying cost per unit)}. This formula is also very useful when comparing quotes where vendors offer different minimum order quantities, price breaks, lead times, transportation costs.
Use it! The EOQ calculation is "Hard Science", if you have accurate inputs the output is the most cost-effective quantity to order based upon your current operational costs. To further increase inventory turns you will need to reduce the order costs. E-procurement, vendor-managed inventories, bar coding, and vendor certification programs can reduce the costs associated with processing an order. Equipment enhancements and process changes can reduce costs associated with manufacturing set up. Increasing forecast accuracy and reducing lead times which result in the ability to operate with reduced safety stock can also reduce inventory levels.

Source : Dave Piasecki, Logistic Management .

Optimizing Safety Stock

2008-04-23T05:58:00.000-07:00

Optimizing Safety Stock levels by calculating the magical balance of minimal inventory while meeting variable customer demand is sometimes described as the Holy Grail of inventory management (ok, forecasting is probably the true holy grail but I thought this sounded good). Many companies look at their own demand fluctuations and assume that there is not enough consistency to predict future variability. They then fall back on the trial and error best guess weeks supply method or the over simplified 1/2 lead time usage method to manage their safety stock. Unfortunately, these methods prove to be less than effective in determining optimal inventory levels for many operations. If your goal is to reduce inventory levels while maintaining or increasing service levels you will need to investigate more complex calculations.
One of the most widely accepted methods of calculating safety stock uses the statistical model of Standard Deviations of a Normal Distribution of numbers to determine probability. This statistical tool has proven to be very effective in determining optimal safety stock levels in a variety of environments. The basis for this calculation is standardized, however, its successful implementation generally requires customization of the formula and inputs to meet the specific characteristics of your operation. Understanding the statistical theory behind the formula is necessary in correctly adapting it to meet your needs. Errors in implementation are usually the result of not factoring in variables which are not part of original statistical model

Terminology and calculations
The following is a list of the variables and the terminology used in this safety stock model:
Normal distribution. Term used in statistical analysis to describe a distribution of numbers in which the probability of an occurrence, if graphed, would follow the form of a bell shaped curve. This is the most popular distribution model for determining probability and has been found to work well in predicting demand variability based upon historical data.
Standard deviation. Used to describe the spread of the distribution of numbers. Standard deviation is calculated by the following steps:
determine the mean (average) of a set of numbers.
determine the difference of each number and the mean
square each difference
calculate the average of the squares
calculate the square root of the average.
You can also use Excel function STDEVPA to calculate standard deviation. In safety stock calculations, the forecast quantity is often used instead of the mean in determining standard deviation.
Lead time. Highly accurate lead times are essential in the safety stock/reorder point calculation. Lead time is the amount of time from the point at which you determine the need to order to the point at which the inventory is on hand and available for use. It should include supplier or manufacturing lead time, time to initiate the purchase order or work order including approval steps, time to notify the supplier, and the time to process through receiving and any inspection operations.
Lead-time demand. Forecasted demand during the lead-time period. For example, if your forecasted demand is 3 units per day and your lead time is 12 days your lead time demand would be 36 units.
Forecast. Consistent forecasts are also an essential part of the safety stock calculation. If you don't use a formal forecast, you can use average demand instead.
Forecast period. The period of time over which a forecast is based. The forecast period used in the safety stock calculation may differ from your formal forecast periods. For example, you may have a formal forecast period of four weeks while the forecast period you use for the safety stock calculation may be one week.
Demand history. A history of demand broken down into forecast periods. The amount of history needed depends on the nature of your business. Businesses with a lot of slower moving items will need to use more demand history to get an accurate model of the demand. Generally, the more history the better, as long as sales pattern remains the same.
Order cycle. Also called replenishment cycle, order cycle refers to the time between orders of a specific item. Most easily calculated by dividing the order quantity by the annual demand and multiplying by the number of days in the year.
Reorder point. Inventory level which initiates an order. Reorder Point = Lead Time Demand + Safety Stock.
Service level. Desired service level expressed as a percentage.
Service factor. Factor used as a multiplier with the Standard Deviation to calculate a specific quantity to meet the specified service level.

Understanding the statistical model and factoring in additional variables.
As mentioned previously, an understanding of the statistical theory behind this formula is necessary to ensure optimal results. The statistical model uses the standard deviation calculation to describe the probability of a number occurring in reference to the mean in a normal distribution. A table is then used to determine a multiplier to use along with the standard deviation to determine ranges of numbers which would account for a specified percentage of the occurrences. The multiplier is referred to as the number of standard deviations required to meet the percentage. The theory states that zero standard deviations added to the mean will result in a number in which 50% of the occurrences will occur below, one standard deviation added to the mean will result in a number in which 84% of the occurrences will occur below, 2 standard deviations added to the mean will result in a number in which 98% of the occurrences will occur below, and 3 standard deviations added to the mean will result in a number in which 99.85% of the occurrences will occur below.
In the safety stock calculation we will refer to the multiplier as the service factor and use the demand history to calculate standard deviation. In its simplest form this would yield a safety stock calculation of : safety stock = (standard deviation) * (service factor). If your lead time, order cycle time, and forecast period were all the same and if your forecast was the same for each period and equaled the mean of the actual demand for those periods, this simple formula would work great. Since this situation is highly unlikely to occur you must add factors to the formula to compensate for these variations. This is where the trouble lies. You must add factors to adapt this theory to work with your inventory, however, each factor you add compromises the integrity of the original theory. This isn't quite as bad as it sounds. While the factoring can get complicated you can keep tweaking it until you find an effective solution. Your final formula will look like: safety stock = (standard deviation)*(service factor)*(lead-time factor)*(order cycle factor)*(forecast-to-mean-demand factor).
There is not a general consensus on the formulas for these factors; in fact, many calculations do not even acknowledge the need for them. I will give some recommendations for these factors, however, I strongly suggest you test and tweak them with your numbers to arrive at something that works for you.
Lead-time factor. This is necessary to compensate for the differences between lead time and forecast period. The standard deviation was based on the forecast period, a factor is necessary to increase or decrease the safety stock to allow for this variance. A formula you can try is lead time factor = square root (lead time/forecast period).
Order cycle factor. Since longer order cycles result in an inherent higher service level you will need to use a factor to compensate for this. A formula you can try is Order cycle factor = square root (forecast period/order cycle).
Forecast-to-mean-demand factor. Remember that the original statistical model was based upon the mean of the distribution. Substituting a forecast for the mean in the calculation of standard deviation creates a problem if the forecast mean and the actual demand mean are not close and also if the forecast varies between forecast periods (seasonality, sales growth). Sorry but I don't have a canned formula for this one that I feel confident enough with to publish. The actual formula used will vary based upon the types of variances and the method for standard deviation calculation used.
Minimum Reorder Point. For slow moving products and especially if the lead time is short, you may want to program in a minimum reorder point which is the equivalent of one average sale.
Lead-time Variances. You may have noticed that I have only discussed demand variations in this model. While you can use this model for predicting variations in supply, I have found that supply variations tend to be far too random and unpredictable. Supply problems tend to be related more to a vendor than an item and the severity of the variations do not fall into the pattern of a normal distribution. The safety stock calculated for demand variation will also cover for some supply variations, however, the best way to deal with variable supply is to have a high level of communication with the vendor and not to count on safety stock. You may find that certain items which are critical to your operation may require a safety stock calculation based upon the nature of the supply chain of the specific item.
While all of these factors and their potentially detrimental effect upon the integrity of the original formula may leave you feeling less than confident with the results of this model, you should realize that these factors would be necessary in any method of calculating safety stock which takes a scientific approach to meeting service levels while maintaining minimal inventory levels. It is very important to thoroughly test the model prior to final implementation to ensure it is working correctly and to determine impact on inventory levels and cash flow. It's also a good idea to start with a higher service factor initially and gradually reduce it until your actual service levels meet your objectives. You will never find perfection in determining probability, however this type of formula is certainly more effective than the previously mentioned keep it simple approaches.

Source : Dave Piasecki, Logistic Management .

How to be a good warehouse employee

2008-04-23T05:56:00.000-07:00

very employee in every position wants to do a good job. However, I found we
often need reminding about what a good job is, more than we need teaching about
what a good job is. And, since everyone and their mother are constantly telling us
how to be good leaders, I decided to tell those that aren.t in leadership positions,
.YET,. what they can do to be a good employee.
Below are 16 tidbits I put together while researching and writing a white paper
with the same title. I decided to shorten it up and this is what I came up with:

1. Work While At Work: The average American worker wastes 2.9 hours per
day. When you include lunch and breaks that means the average employee
works for 4.5 hours a day.

2. Charge Your Cell Phone at Home: I have seen order pickers have to stop
working and get off of the Forklift, because someone cell phone was
charging and they could not get by without moving the cell phone and the
charger out of the way.

3. Stop Complaining About Your Pay: You negotiated it or accepted it, if you
are not happy with it, find another job. It is disruptive when one employee
talks about their salary. Ben Franklin said, .If you want to get rich, diminish
your wants or augment your means.. It is best to do both simultaneously.

4. Help Out Your Boss: Ask them what projects they are working on and can
you help. If your boss replies no, then he or she is an idiot and you should
start looking for another job anyway. Any supervisor worth their salt will
gladly accept the assistance and the opportunity to assist with your career
advancement.

5. Stay Away From Negative Individuals: For two reasons, everyone in the
organization already knows how negative they are and you don.t want to be
associated with them. My mother always told me, .You are known by the
company you keep!. Two, if you are around them enough, you will
ultimately begin believing what they are saying.

6. Find Out What Average is And Beat it By 10%: No one wants to be
average, therefore to move away from the pack and do more. Every week
monitor your progress. Average people are the ones on the news
complaining about the company laying-off half of its work force.

7. Find Out What Your Best Day Was and Beat it By 10% Consistently: It
amazes me to see our culture engulfed with mediocrity, then when there is
an incentive we always do better. Do better on your own without anyone
telling you.

8. Clean Up: Don.t walk past that Coke can today: Tell someone about the
ladder that is broken today. Tell someone about the blown light bulb today.
The problem with most warehouses is not a lack of productivity but the lack
of a broom. Most shipping errors happen because the packing area is a mess.
Most inventory errors happen because the aisles are a mess. Most receiving
errors happen because the receiving area is a mess. Do something about it
today!

9. Read an Industry Magazine Article Twice a Week: After high school the
average American worker never picks up a book. In order to .Earn More
You Must Learn More!. Warehouse Management Systems, RFID, Pick-to-
Light, Voice Directed Picking they are all coming to your warehouse sooner
or later. The more you know about them before they get to you, the more
valuable you are once they arrive. Side Note: I read somewhere that most
people only learn 5 new words a year. And without fail in study after study
the highest paid people in the organization have the best vocabulary. What
better way to improve your vocabulary, and potentially your salary, than to
read.

10. Find Out the Progression Within the Warehouse: That means if you are a
picker what is the next position above that. Document what position you
want next. If the next position from picking is receiving, then when a
position for inventory control becomes available, and you are a picker, you
will know why you may not be considered. But also you need to ask what it
takes to move to the next position and begin working on it.
11. Stay Out of The Customer Service Office: Inside Sales personnel get paid to
take sales calls not talk to warehouse personnel. That does not mean they are
better than you, it means they have a job to do. And customers should not be
placed on hold because the person who should be taking the call is chit-
chatting with a warehouse guy about the game the night before.

12. Learn The Names of The Company.s Top 25 Customers: You have to
know who patronizes your organization. But you really have to know who
spends the most with your organization. I know ever small customer has the
potential to become a big customer. But as Bear Bryant said, .Potential
Means You Ain.t Done It Yet!.

13. Complete What You Start: When assigned a task complete it! Then tell your
supervisor, who assigned it to you, that it was completed and they can
scratch it off of their list. After they scratch it off, ask, .What.s Next!.

14. Keep a Note Pad and Take Notes With It: A lot of warehouse supervisors
do not keep accurate notes. They think they can remember everything.
Therefore make it your responsibility to take notes of the tasks you are
assigned. This shows your supervisor that you care enough to write it down.
It also shows their supervisor that you are a conscientious employee.

15. Go To Lunch With Your Supervisors Boss: Believe it or not, .Business is
emotional.. People trust people they know. When your supervisor puts your
name in for a new position, it is good if the person responsible for approving
it already knows who you are.

16. Keep Track of The Amount of Work You Produce: Most of us are self
motivated individuals. If you pick 100 orders today, and you know it, you
will not pick less tomorrow. Without anyone telling you to, you will always
try to do better than you did the previous day.

Guide to inventory accuracy

2008-04-20T07:33:00.001-07:00

Having problems with inventory accuracy? Implementing technologies such as bar coding systems, RFID, and pick-to-light are often assumed to be the solutions to inaccurate inventories. If properly implemented these technologies can help reduce errors, however, none of them will eliminate all errors, and a poorly implemented system can leave you worse off than you were before. Whether you are planning on implementing additional systems or not you should consider taking care of the basics first.

The Basics
There is nothing revolutionary about my list of "The Basics", it's simply a series of steps which define a process for achieving higher levels of inventory accuracy. Your success or failure will be determined by your implementation of these steps. This is not something that should be rushed; throwing a quick fix approach together to alleviate an immediate need may be more damaging in the long run since the success of this plan requires a cooperative effort by many people within your organization. If your first attempt fails, you will find it more difficult to get a high level of cooperation for your next try. Take the time and do it right.
Attitude. Maintaining inventory accuracy must be an integral part of the attitude of the organization. Like quality, customer service, and plant safety, accuracy must be promoted throughout the organization as everyone's responsibility. This attitude must start at the top levels. Yeah I know all you managers and execs out there want an accurate inventory but are you doing your part through your decisions and business practices to promote it. Processes are often shortcut in the name of "Customer Service" (this also applies to processes for Quality, Inventory Management, and Production Plans) that reduce or eliminate the effectiveness of the plan, which in the long run will reduce your ability to service your customers. Remember that these plans are designed to meet the needs of the customer, don't compromise them.
Process Definition. You'll struggle to make any progress if you have not clearly defined the processes throughout the organization that affect inventory. While defining the processes, you should be looking for opportunities for errors and implementing changes to eliminate or reduce them. Even the most accurate employee will make errors, I suggest placing formal checks in place for critical operations. Get as many people involved in this step to ensure you have a complete and accurate understanding of the processes. Anything missed in this step will require new procedures and additional employee training later, so once again, "take the time and do it right".
Procedure Documentation. This is the part where you use the previously defined processes to document the procedures the employees will follow to maintain inventory integrity. The procedures documented here should not be limited to inventory issues; they should be the complete procedure including quality, physical aspects, and safety. This documentation should be as clear and comprehensive as possible. It should be written for a specific task within a specific job responsibility, it should include everything the employee needs to know to complete the task and nothing else. For example: if a stock clerk's responsibility is to notify the supervisor of any discrepancies, that is all it should state in the procedure for the stock clerk even though there will be additional procedures for dealing with the discrepancy. Procedures should also include the correct method for filling out and processing paperwork, the sequence and timing of entering data, and any checks that are required to be performed. If there are any exceptions to a procedure they should be specified in the document, allowing undocumented exceptions to a procedure will decrease its effectiveness. Be realistic, procedures are not a "wish list", they are the documentation of the requirements of a specific task. You must be prepared to enforce compliance to all procedures. Once you are completed with the documentation, I suggest you first distribute the procedures to a few key employees, then take a couple of weeks for you and the key employees to monitor existing operations to see if anything was missed or if anything is incorrect. Once this is done, the procedures should be officially put into effect and distributed to all employees.
Employee Training. Handing out a written procedure does not constitute employee training. It is important to set a training schedule to go through all the procedures with groups of employees. Take whatever time is necessary to ensure they have a thorough understanding of the procedures. Make it clear that the procedure document is the only way to perform the task. If you did your job correctly in defining the processes and documenting the procedures you shouldn't run into many surprises during the training. Try to refrain from making changes or exceptions to the documentation at this time (unless there is a critical error). Last minute changes or exceptions will cause confusion and diminish the value of the documents. Make notes for possible future revisions of the procedures instead. Set a timetable for publishing and putting into effect revisions (every quarter or six months). Frequent revisions of procedures tend to cause confusion and make it difficult to enforce adherence.
Employee Testing. I am a big advocate of formal testing of employees on procedures. This is the only way to know if they understand them (or have even read them). Be prepared, this will scare the hell out of your staff. Do not make the tests too difficult, I suggest multiple choice questions and maybe some true/false. You may also need testing which requires the employee to perform the task in the presence of the tester. Make a point to include items in the test that are known to have been issues in the past. There should not be any penalties for incorrect answers on the test. Any incorrectly answered questions should be discussed with the employee to ensure that he/she now understands the correct answer. You may need to make arrangements to conduct the test verbally for employees with inadequate reading skills or other arrangements if language is an issue.
Monitoring Processes for Compliance. You must begin to monitor the processes for compliance to the procedures immediately. Any actions observed which do not comply with the written procedures must be addressed immediately with the employees involved. As stated earlier, the written procedures are the only way to perform the task. Allowing employees to "do it their own way" (even if their way is a better way) will make it impossible to enforce compliance on other issues and will create problems when changes are made to processes. If they have a better way, consider it for the next revision at which point it would then become "the only way".
Setting Standards. I am also a big advocate of setting minimum accuracy and production standards wherever feasible. Do your research to ensure the standards set are high enough yet still achievable. You will have to enforce these standards so it is critical to set them correctly. If in doubt, set them lower, you can always increase them later when more data is available. If you set them too high you have put yourself in a difficult position when it comes time to enforce them. Standards should be set for the specific task being performed. For example, the accuracy standard for a stock clerk stocking in random storage area would be lower than for one stocking in fixed locations. Setting standards requires tracking of the accuracy and productivity of the tasks being performed which makes it more viable when you have several people performing the same tasks.
Tracking Accuracy. Whether you have set standards or not I still suggest you track accuracy organizationally and individually. Accuracy tracking should always be measured as a percentage of total transactions. Tracking accuracy as flat numbers (number of errors) puts your more productive employees at a disadvantage, and at an organizational level will be skewed by variances in business activity. Accuracy tracking should be communicated to staff in a positive manner; it is a tool to facilitate improvement in processes and people. I have found that by simply tracking and communicating accuracy to employees you will see immediate reductions in errors even if standards are not set. The fact is we all want to be accurate; the problem is we all think that we are accurate and it's always the other guy who is making all the mistakes.
Accountability. People must be held accountable for following documented procedures. You have spent the time to document the procedures, provide the training, and the testing. If someone is not following the procedures they must be dealt with applying appropriate disciplinary action. It's that simple. You may be amazed as to how much just one individual not following procedures can screw up your inventory. If you don't hold the employees accountable you may as well throw out everything you have done to this point. Mistakes are mistakes and everyone makes them, however, not following a specified procedure is a conscious decision made by the employee to not do what he/she was instructed to do.
Count, Count, Count. We would like to believe that since we have taken the above steps we should now assume our inventory is accurate. Not necessarily. You will have to count it to determine the accuracy, as well as determining areas needing additional evaluation. Year-end physical inventories are tools used by accountants and do very little for inventory accuracy. You should count your inventory on a continuous basis (cycle counting) to maintain high levels of accuracy. This is one of the best ways of identifying problem areas on a timely basis and providing an environment conducive to continuous improvement. The way you count and the frequency of your counts should be designed for your specific type of operation.
Reevaluate. You should be regularly reevaluating your processes and procedures. Results of your cycle count program should point you in the direction of areas where enhancements are needed. Business conditions often change and new processes are added which will require evaluation. As previously mentioned try to refrain from frequent revisions to procedures (the memo of the day), it is more effective to plan a revision date and group multiple revisions into a revised release of the procedures. These revisions should be implemented with the proper training and testing as was done during initial implementation.
As you may have noticed, each of the above steps is highly dependent on the successful implementation of the previous steps. Although this process for improving inventory accuracy is not very complicated, the implementation can prove to be demanding. Depending on the environment you are working in, it can sometimes seem to be an insurmountable task to change the attitudes of people towards inventory accuracy. It will require a high level of effort and diligence to ensure success.

Additional recommendations.
The following are some additional suggestions that may help in your quest for a more accurate inventory.
Dedicate positions for managing inventory. Make sure you have control of which employees are affecting your inventory. This is especially true in manufacturing operations where the priorities of machine operators and production supervisors are meeting the production schedule, keeping the machines running, and ensuring the quality of the product being produced. Inventory accuracy will never be a primary responsibility of these types of positions. Once you come to this realization, it is easy to see the benefits of putting your inventory and material handling responsibilities in the hands of people whose primary responsibility is inventory. Also, within your material handling/warehouse positions you should limit the people doing miscellaneous type inventory adjustments.
Control employee turnover. I know, easier said than done. You've invested the time into training them, now figure out what you need to do to keep them. Once you have your processes and procedures under control you will find that new employees will become your #1 source of errors. My experience shows a new employee generally makes 2 to 5 times as many mistakes as a one-year employee and 5 to 10 times as many mistakes as a five-year employee. These numbers are based on operations that track accuracy and promote continuous improvement. If you're not tracking accuracy, your five-year employees may be making as many mistakes as they did during their first year. Also high employee turnover results in operations that are frequently short staffed which will almost always lead to increased errors.
Be prepared to dismiss or reassign employees. May sound like a contradiction to the previous suggestion, however, if you have made every effort to assist an employee in improving their accuracy and insufficient progress is being made you will need to get them away from your inventory. Again, don't underestimate the damage that can result from just one employee's errors.
Don't be afraid to put Checks in place. Some people feel that checking or rechecking work is admitting failure or is a waste since it "should be done right the first time", so I'll say it once again, everyone makes mistakes, that means everyone. If you find there are certain areas that are highly prone to errors (such as random stocking areas) or critical parts of your operation where a mistake can have significant detrimental effect, consider putting checks in place. A check may be an employee checking their own work or a specific checking operation. Outbound shipments should always have some type of check in place, the specific type of check will vary from operation to operation. In a high-volume, low-value shipping operation a simple looking over the shipment may be all that's feasible, while in a lower-volume, high-value shipping operation I've had as many as three people performing redundant checks of each shipment prior to loading.
Storage Areas. How you store your product will also affect accuracy. Crowded unorganized areas become "black holes" for missing product. Crowded areas also cause increase damage to product that is often disposed of without inventory corrections being made. High-density storage makes it very difficult to accurately count the product. Maintaining proper lighting, shelf and product labeling, and organization makes it easier to stock, pick, and count product thus increasing levels of accuracy.
Know your inventory system. The more you know about how your specific inventory system works, the more successful you'll be in optimizing its features. Computer systems are regularly blamed for things that are usually turn out to be human error, however, occasionally your computer system can be the source of the problem. Bugs, glitches, hiccups or whatever you want to call them do occur and changes to system parameters to optimize functionality in one area can create havoc in a seemingly unrelated area. The only way to determine the source and correct these problems is to have a thorough understanding of how your system is set up and how the specific programs process the information. The bigger advantage to acquiring a high level of system knowledge lies in the amount of information you'll be able to extract from your system. Today's larger software systems maintain enormous amounts of data and contain far more functionality than most users realize. Managers need to be taking more active roles in system set up and implementations if they want to optimize the system to meet their business needs. The days of leaving it all up to the IS department are gone, the staffing levels of most IS departments are inadequate to deal with the complexity and the enormity of software packages today. IS personnel tend to spend the majority of their time making sure the system runs rather than optimizing its features.
The end result in accuracy improvement will be directly related to the effort put forth to achieve it. Building a sound consistent inventory accuracy plan will get people in the habit of being accurate, as the entire organization gets in the habit of being accurate you will find the accuracy plan starts to run itself. Until then, it will require a lot of work by those implementing it.

Source : Dave Piasecki, logistic management.

Order Picking: Methods and Equipment for Piece Pick, Case Pick, and Pallet Pick Operations.

2008-04-13T03:28:00.001-07:00

Of all warehouse processes, order picking tends to get the most attention. It’s just the nature of distribution and fulfillment that you generally have more outbound transactions than inbound transactions, and the labor associated with the outbound transactions is likely a big piece of the total warehouse labor budget. Another reason for the high level of importance placed on order picking operations is its direct connection to customer satisfaction. The ability to quickly and accurately process customer orders has become an essential part of doing business.
The methods for order picking vary greatly and the level of difficulty in choosing the best method for your operation will depend on the type of operation you have. The characteristics of the product being handled, total number of transactions, total number of orders, picks per order, quantity per pick, picks per SKU, total number of SKUs, value-added processing such as private labeling, and whether you are handling piece pick, case pick, or full-pallet loads are all factors that will affect your decision on a method for order picking. Many times a combination of picking methods is needed to handle diverse product and order characteristics.
Key objectives in designing an order picking operation include increases in productivity, reduction of cycle time, and increases in accuracy. Often times these objectives may conflict with one another in that a method that focuses on productivity may not provide a short enough cycle time, or a method that focuses on accuracy may sacrifice productivity.
Productivity. Productivity in order picking is measured by the pick rate. Piece pick operations usually measure the pick rate in line items picked per hour while case pick operations may measure cases per hour and line items per hour. In pallet pick operations the best measure is actual pallets picked per hour. Since the actual amount of time it takes to physically remove the product from the location tends to be fixed regardless of the picking method used, productivity gains are usually in the form of reducing the travel time.
Cycle Time. Cycle time is the amount of time it takes to get an order from order entry to the shipping dock. In recent years, customer’s expectations of companies to provide same day shipment has put greater emphasis on reducing cycle times from days to hours or minutes. Immediate release of orders to the warehouse for picking and methods that provide concurrent picking of items within large orders are ways to reduce cycle times.
Accuracy. Regardless of the type of operation you are running, accuracy will be a key objective. Virtually every decision you make in setting up a warehouse will have some impact on accuracy, from the product numbering scheme, to the design of product labels, product packaging, the design of picking documents, location numbering scheme, storage equipment, lighting conditions, and picking method used. Technologies that aide in picking accuracy include pick-to-light systems, counting scales, and bar code scanners. Beyond the design aspects of an order picking operation, employee training, accuracy tracking, and accountability are essential to achieving high levels of accuracy.

Piece Picking
Piece-picking methods. Piece picking, also known as broken case picking or pick/pack operations, describes systems where individual items are picked. Piece pick operations usually have a large sku base in the thousands or tens of thousands of items, small quantities per pick, and short cycle times. Mail order catalog companies and repair parts distributors are good examples of piece pick operations.
Basic order picking. In the most basic order-picking method, product is stored in fixed locations on static shelving or pallet rack. An order picker picks one order at a time following a route up and down each aisle until the entire order is picked. The order picker will usually use some type of picking cart. The design of the picking flow should be such that the order picker ends up fairly close to the original starting point. The picking document should have the picks sorted in the same sequence as the picking flow. Fast moving product should be stored close to the main cross aisle and additional cross aisles put in to allow short cuts. Larger bulkier items would be stored towards the end of the pick flow. This basic order picking method can work well in operations with a small total number of orders and a high number of picks per order. Operations with low picks per order will find the travel time excessive in this type of picking and operations with large numbers of orders will find that the congestion from many pickers working in the same areas slows down the processing.
Batch picking / Multi-order picking In batch picking, multiple orders are grouped into small batches. An order picker will pick all orders within the batch in one pass using a consolidated pick list. Usually the picker will use a multi-tiered picking cart maintaining a separate tote or carton on the cart for each order. Batch sizes usually run from 4 to 12 orders per batch depending on the average picks per order in that specific operation. Batch picking systems may use extensive logic programmed to consolidate orders with the same items. In operations with low picks per order, batch picking can greatly reduce travel time by allowing the picker to make additional picks while in the same area. Since you are picking multiple orders at the same time, systems and procedures will be required to prevent mixing of orders. In very busy operations, batch picking is often used in conjunction with zone picking and automated material handling equipment. In order to get maximum productivity in batch pick operations, orders must be accumulated in the system until there are enough similar picks to create the batches. This delay in processing may not be acceptable in same day shipping operations.
Zone picking. Zone picking is the order picking version of the assembly line. In zone picking, the picking area is broken up into individual pick zones. Order pickers are assigned a specific zone, and only pick items within that zone. Orders are moved from one zone to the next as the picking from the previous zone is completed (also known as "pick-and-pass"). Usually, conveyor systems are used to move orders from zone to zone. In zone picking it’s important to balance the number of picks from zone to zone to maintain a consistent flow. Zones are usually sized to accommodate enough picks for one or two order pickers. Creating fast pick areas close to the conveyor is essential in achieving high productivity in zone picking. Zone picking is most effective in large operations with high total numbers of skus, high total numbers of orders, and low to moderate picks per order. Separate zones also provide for specialization of picking techniques such as having automated material handling systems in one zone and manual handling in the next.
Wave picking. A variation on zone picking and batch picking where rather than orders moving from one zone to the next for picking, all zones are picked at the same time and the items are later sorted and consolidated into individual orders/shipments. Wave picking is the quickest method (shortest cycle time) for picking multi item orders however the sorting and consolidation process can be tricky. Operations with high total number of SKUs and moderate to high picks per order may benefit from wave picking. Wave picking may be used to isolate orders by specific carriers, routes, or zones.

Piece-picking equipment: As with the picking methods, the picking equipment used will also depend on a variety of factors.
Static shelving. The most common equipment for storage in piece pick operations, static shelving is designed with depths from 12” to 24”. Product is either placed directly on the shelving or in corrugated, plastic, or steel parts bins. Static shelving is economical and is the best method where there are few picks per SKU or where parts are very small.
Carton flow rack. Carton flow rack is similar to static shelving with the exception that rather than shelves, there are small sections of gravity conveyor mounted at a slight angle. Product is stocked from the rear of the flow rack and picking is done from the face. Product can be stocked in cartons or small totes or bins. As a carton or tote is emptied, it is removed from the rack and another one will roll into place. Carton flow rack is most useful where there is a very high number of picks per SKU.
Carousels. Horizontal carousels are a version of the same equipment used by dry cleaners to store and retrieve clothing. They have racks hanging from them that can be configured to accommodate various size storage bins. Generally an operator will run 2 to 4 carousels at a time avoiding the need for the operator to wait while one unit is turning. Picking is usually performed in batches with orders downloaded from the host system to the carousel software. Horizontal carousels are most common in picking operations with very high number of orders, low to moderate picks per order, and low to moderate picks per sku. Horizontal carousels provide very high pick rates as well as high storage density. Pick-to-light systems are often integrated into carousels. Vertical Carousels are frequently used in laboratories and specialty manufacturing operations and are rarely used in regular order picking operations.
Automatic storage and retrieval systems (ASRS). An ASRS is a system of rows of rack, each row having a dedicated retrieval unit that moves vertically and horizontally along the rack, picking and putting away loads. ASRS systems are available in mini-load types that store and transfer product on some type of tray or in bins, and unit-load types that transfer and store pallet loads or other large unitized loads. In addition to the automation features, ASRS units can provide extremely high storage density with capabilities to work in racking up to 100 feet high. Unfortunately the high costs of ASRS equipment and the length of the retrieval times make it difficult to incorporate into a piece picking operation.
Automatic picking machines. Fully automated picking machines (such as A-frames) are still pretty rare and are used only where very high volumes of similar products are picked such as music CDs, or, where high volume in combination with high accuracy requirements exist such as pharmaceutical fulfillment.
Pick-to-light. Pick-to light systems consist of lights and LED displays for each pick location. The system uses software to light the next pick and display the quantity to pick. Pick-to-light systems have the advantage of not only increasing accuracy, but also increasing productivity. Since hardware is required for each pick location, pick-to-light systems are easier to cost justify where very high picks per SKU occur. Carton flow rack and horizontal carousels are good applications for pick to light. In batch picking, put-to-light is also incorporated into the cart or rack that holds the cartons or totes that you are picking in to. The light will designate which order you should be placing the picked items in.
Bar-code scanners. Though very useful in increasing accuracy levels, bar-code scanners in a fast-paced piece-pick operation tend to become cumbersome and can significantly reduce your pick rates. With proper training, tracking, and accountability, you can get very high accuracy rates in order picking without scanners. I find they are better suited to case pick, pallet load, putaway, and order checking operations.
Voice-directed picking. Voice technology has come of age in recent years and is now a very viable solution for piece pick, case pick, or pallet pick operations.
Automated conveyor and sortation Systems. Automated conveyor systems and sortation systems will be integral to any large-scale piece pick operation. The variety of equipment and system designs is enormous.

Case Picking
Case-picking methods. Case picking operations tend to have less diversity in product characteristics than piece picking operations, with fewer SKUs and higher picks per SKU.
Basic case-picking method. This is the most common method for case-picking operations. Rather than product stored on static shelving, case-pick operations will have the product stored in pallet rack or in bulk in floor locations. The simplest picking method is to use a hand pallet jack (or motorized pallet truck) and pick cases out of bulk floor locations however many operations will find that going to very narrow aisle (VNA) pallet racking and using man-up order selectors or turret trucks will provide high storage density and high pick rates.
Batch picking. Batch picking is rarely used in case pick operations primarily because of the physical size of the picks. You are unlikely to have enough room on a pallet to pick multiple orders.
Zone picking. Zone picking can be used in case-picking operations, however, like batch picking, the size of the picks and the size of the orders in most case-pick operations do not lend themselves well to zone picking. If you do have a case pick operation where you have a large number of SKUs, and orders with small quantities per SKU, or where you have enough cases per order per zone to fill a pallet, you may find zone picking applicable.
Wave picking. Wave picking can be applied to case picking operations where you have very large orders with many picks per order and are looking for ways to reduce cycle time.
Case-picking equipment.
Pallet rack. Pallet rack is the most common storage system for case pick operations.
Flow rack. Although carton flow rack rarely applies to case pick operations, pallet flow rack or push back rack can be useful.
Carousels. Although you can incorporate unit-load carousels into a case pick operation, it tends to be an unlikely match-up. If doing batch picking where you have many picks per SKU and few pieces per pick you can pick from an ASRS unit onto a unit-load carousel.
Automated storage and retrieval systems (ASRS). Unit-load ASRS systems can be useful in case-pick operations, especially if you can provide storage heights of 40 to 100 feet.
Pick-to-light. Pick-to-light can be used in case-pick operations, however, its application is significantly less than in piece pick operations.
Bar-code scanners. Bar-code scanners are frequently used in case-pick operations. Since the time to physically pick the product is higher in case-pick operations, the time spent scanning tends to have little impact on productivity and therefore the accuracy benefits will usually outweigh any reduction in productivity.
Voice-directed picking. Voice technology has come of age in recent years and is now a very viable solution for piece pick, case pick, or pallet pick operations.
Automated conveyor and sortation systems. If using zone or wave picking, automated conveyor and sortation systems will likely be a part of your system. In case picking, you may use standard conveyors to transport individual cases or unit-load conveyors to transport pallets.
Lift trucks. As previously mentioned, motorized pallet trucks, man-up order selectors, and man-up turret trucks are the vehicles of choice for case-pick operations.

Pallet Picking
Full-pallet-picking methods. Full-pallet picking is also known as unit-load picking. The systematic methods for full-pallet picking are much simpler that either piece pick or case pick, however, the choices in storage equipment, storage configurations, and types of lift trucks used are many.
Basic pallet picking. This is the most common method for full-pallet picking. Orders are picked one at a time. The order picker will use some type of lift truck, retrieve the pallet load and stage it in a shipping area in a staging lane designated for that order, or just pick and load directly into an outbound trailer or container..
Batch picking. Since the nature of pallet picking is a single pick per trip, batch picking has no application in pallet-picking operations.
Zone and wave picking. Although the normal definition of zone picking where an order is moved from zone to zone as picks are accumulated doesn’t apply to pallet picking, pick zones are used in wave picking in pallet-picking operations. The storage area is broken into zones to eliminate multiple lift-truck operators from picking in the same aisle. The lift truck operator may pick the pallet and deliver it directly to the designated staging lane or place it on a unit-load conveyor that will deliver it to the sorting/staging area.
Task interleaving. Task interleaving is a method of combining picking and putaway. Warehouse Management Systems (WMS) use logic to direct a lift truck operator to put away a pallet en route to the next pick.

Pallet-picking equipment.
Pallet rack. There are numerous pallet rack configurations used in full pallet operations, from standard back-to-back single pallet depth configurations to double-deep rack, push-back rack, drive-in/drive-thru rack, and flow rack. The best racking configuration for your operation will be based on the total number of pallets per sku, pallets per pick, and the length of time the product is in the rack prior to shipment. There are a lot of tradeoffs in choosing a racking configuration including storage density, picking productivity, equipment costs, and the ability to maintain first-in first-out.
ASRS. Unit-load ASRS units when combined with unit-load conveyors and sortation systems can provide fully automatic pallet picking operations. And again, the ability to store product in racking up to 100 feet high gives excellent storage density.
Automated conveyor and sortation systems. Automated conveyor and sortation systems can be combined with ASRS units or used in conjunction with manual picking with lift trucks in zone/wave picking systems. Either the ASRS or the lift truck operator delivers the pallet load to the conveyor. The conveyor system then delivers the pallet to the shipping area where it is either manually sorted by lift trucks into the designated staging lane, or a sortation system automatically sorts into a staging lane. Staging lanes can be equipped with automated or gravity fed unit-load conveyor.
Bar-code scanners. Bar-code scanners are very commonly used in pallet-pick operations.
Voice-directed picking. Voice technology has come of age in recent years and is now a very viable solution for piece pick, case pick, or pallet pick operations.
Lift trucks. The lift trucks used for pallet picking will depend upon the storage configuration. Standard lift trucks are used in bulk floor storage and wide-aisle pallet rack storage in singe-depth, push-back, drive-in/drive-thru, and flow rack. Reach trucks are used in narrow-aisle storage in single-depth, double-deep, push-back, drive-in/drive-thru, and flow rack. Swing mast and turret trucks are used in very narrow aisle storage in single depth pallet rack.

General Information
Regardless of the product handled, or the picking method and equipment used, locating product by the frequency of picks should be incorporated into the system design. The fastest moving product should be stocked as close to the pick point as possible and at the levels that are easiest to pick from. Even if you are using an ASRS unit, the retrieval time will be less the closer the location is to the pick point, and in a horizontal carousel, the picking time will be less if the order picker does not need to bend down or reach up to pick.
In fixed location picking, you designate a specific picking location for each SKU. Fixed picking locations are most commonly used in piece-pick operations, however, they may also be used in case picking and pallet picking where flow rack is incorporated. Slotting in fixed picking locations needs to be reviewed on a regular bases to ensure high levels of productivity. The frequency of review will depend upon product life cycles and seasonality. In random storage operations, a WMS system can direct fast movers to the closest open location to the pick point.
Operations using fixed picking locations will generally also have a reserve or overflow storage area. The overflow storage area will usually use a system of random storage. A replenishment system will need to be put in place to move product to the fixed picking locations as inventory levels drop to predetermined levels.
Outbound shipments should always have some type of a check in place. The type of check will vary from operation to operation. In a high-volume low-value shipping operation, a simple "looking over" the shipment may be all that's feasible, while in a lower-volume high-value shipping operation, I've had as many as three people performing redundant checks of each shipment prior to loading.
Extensive data analysis is necessary in determining the best methods for order picking. Historical data on picks per SKU, quantity per pick, picks per order, total picks, total orders, orders received by time of day, etc. will be important in not only the initial plan, but also in the ongoing operation of the system.
It will also be very important to project growth, especially in automated systems. While you can throw more people into a manual system when transactions increase, automated systems such as carousels and ASRS units will have capacity limits.
Order-picking systems can be very simple systems in small operations or become very complex systems using a little bit of everything. In a large operation you may have totes start as batch pick in a carousel picking area for your medium moving piece-pick items, and then move individually to a manual picking area for slow moving small-parts piece picking out of static shelving (possibly in a mezzanine). Then move to a carton-flow rack area for your fastest moving items, and finally to a shipping staging/consolidation area where it is matched up with cases and bulkier items from a case-pick ASRS unit and full pallets from a racked warehouse.

Source : Dave Piasecki, Logistic Management.

Cycle Counting and Physical Inventories

2008-04-13T03:26:00.000-07:00

So it's the end of the year and the warehouse workers and all the salaried employees are gathered together on a Saturday morning to perform the annual physical inventory. The coffee and donuts help to put color into the faces and cover up the odors enveloping those who had overindulged themselves the night before. People are wandering around not sure what they should be doing, when the boss walks in with stacks of reports, cards, and colored stickers and says "OK here's how this is going to work." By noon it's obvious that less than half the warehouse has been counted and the pizza lunch has left everyone with an enthusiasm deficit. At two o'clock, one by one, people start approaching the boss with the reasons as to why they have to leave. Suddenly the pressure increases on those remaining to get finished. Five o'clock and the last of the counters are abandoning ship, there's an enormous pile of paperwork marked "discrepancies" and several piles of product marked "unknown," "what's this?" and "needs to be identified." The boss surveys the scene and instructs the people in charge of investigating the overwhelming pile of discrepancies to "just make the adjustments, we need to get out of here."
With some variations, this is how annual physical inventories are performed year after year. So what’s wrong with this process? Everything!!! You’ve just had a group of people with inadequate training and experience — most of them forced into being there on their day off — count your inventory, and have then made adjustments to your on-hand balances based on those counts without having the time to adequately investigate the variances. The final result likely being that half of the adjustments corrected previous inventory problems while the other half created new inventory problems on items that were correct prior to the inventory. In case it’s not obvious to you, I don’t like annual physical inventories. Counting inventories on a regular basis throughout the year (cycle counting) combined with a process for continuous improvement in inventory accuracy will prove a far better method for achieving accurate inventories. My definition of cycle counting tends to differ slightly from the generally accepted one. Most people think of cycle counting as regularly scheduled (usually daily) counting of product where you randomly count items based upon some type of predefined parameters. For example, inventory is broken down by ABC classifications and frequencies assigned such as A items counted 10 times/year, B items 5 times/year, and son on. I prefer to define cycle counting as any count program using regularly scheduled counts where you count less than the entire facility's inventory during each count. This includes a system that I’ve found to be highly effective, that is a hybrid of a physical inventory and a cycle count, where you’re counting all inventory within a physical area like a physical inventory, however, you are not counting the entire facility at one time. The next day you simply start where you left off the day before. Regularly scheduled physical inventories can be an effective way of counting inventory in smaller operations provided you are using trained counters and have adequate time to investigate the discrepancies prior to making adjustments. If your inventory is so extensive that you cannot adequately investigate the count discrepancies, you must break it down into some sort of a cycle count program.
If you are running a successful and comprehensive cycle counting program, there is little benefit to performing an annual physical inventory. Unfortunately, many in the financial establishment still live in the Dark Ages when it comes to inventory counting and will try to tell you that “you must perform an annual physical”. Once again I’ll state that if you can count and adequately investigate count discrepancies in a single day, then go ahead and perform the physical. However, if your inventory is too extensive or if you are in a 24/7 operation, do not want to shut down operations, and feel confident in the accuracy of your cycle count program, you can pressure them into accepting some type of on-site audit instead. They generally don’t like it but they will do it.

Designing your Count Program.
Your count program should be customized to your specific operation and business. Do not accept the “one system fits all” approach. In complex operations you may have a count program that uses multiple approaches to counting, such as one method for finished goods, another for WIP, another for raw materials, and still other methods based upon whether the inventory is stored in fixed or random storage areas.

Why are you counting?
The first thing you need to determine is why you are counting. Specifically, what is it that you expect to achieve through your count program? If you are setting up a program just to fulfill a corporate requirement of counting inventory X times per year or to achieve some subjective accuracy number thrown at you, you will likely not end up with a highly effective count program. You should be counting to optimize your business operations and achieve high levels of customer service. If your business has been operating for some time you probably have some idea of the areas that have had ongoing problems related to inaccurate inventories. This is a good place to start, however, you should also weigh the effects created by these inaccuracies to determine which areas are more critical than others. Small variances in some types of raw materials may have little or no effect on operations while inaccuracies on others may shut down an operation. Inaccuracies in finished goods tend to have the most obvious direct effect on customer service and generally get a high priority in count programs.

Frequency of Counts.
Count frequency should be calculated to meet your previously stated objectives. Factors such as the effects on customer service and manufacturing operations, and the potential for inaccuracy within the specific product group will affect the frequency of your counts. Even factors such as manufacturing and supplier lead times should be considered in prioritizing counts. Certain key raw materials critical to your operation that are highly prone to variances due to high scrap factors or variation in manufacturing processes may need to be counted every week (or day) while some very slow-moving finished goods may only need to be counted once a year. As your count program evolves, the frequency of counts will change based upon the accuracy levels achieved.

Accuracy Tracking.
Your count program should be considered part of a continuous improvement process. Tracking accuracy is necessary to determine where improvement is needed. The more detail you can provide, the better you will be able to pinpoint specific areas requiring attention. Breaking down accuracy by product groups, physical area, and operational groups, will provide the information needed to improve processes and determine priorities for future counts. Don’t get hung up on “Benchmarking”. There are so many variables in the ways accuracy is tracked from one organization to another that these comparisons tend to be a waste of time. What you should get hung up on is consistency. Spend the time to develop your methods for tracking accuracy to meet current and future needs. Long-term data is invaluable provided the method used to compile it has not changed.
I primarily use two methods for tracking inventory variances, which I will refer to as Transactional and On-hand methods. On-hand tracking is the most commonly used method where variance amounts are divided into on-hand amounts to give you a variance percentage. The On-hand method gives you a snapshot of what your inventory accuracy is at that specific point in time. It is helpful in projecting the impact your variances might have on subsequent operations and is the only method accountants use. The problem with the on-hand method is that it may not give you enough information to pinpoint process problems and, at a detail level, it fluctuates too much based upon current on-hand balances. For example, if on Monday you count part #XYZ and find you are short 20 units out of an on-hand balance of 100, this results in an accuracy rate of 80%. However, if you did not count this item until Tuesday and a receipt of 2000 units was received Monday afternoon, your accuracy rate would now be 99% even though you are still missing those 20 units.
Transactional tracking compares the variance amount to the amount consumed during the count period, showing the accuracy of your operation. This type of tracking is far more useful in determining process problems. Unfortunately, it is also much more difficult to implement this method. In the same example where you are short the 20 units and you determined that you have consumed 1000 units during the count period, you now have an operational accuracy of 98%. If this item is a raw material used in manufacturing and you determine that your finished goods is accurate, then you may have a 2% variance either in your bill of material or scrap reporting. Transactional tracking assumes that your receipt quantities are accurate.
There is another method widely used in cycle counting I will refer to as Good Count Bad Count. In this method you compare the number of good counts to the number of bad counts. Tolerances are often put in place to allow a count to be considered "good" if it is within a certain percentage. I personally find very little value to this method. Regardless of the methods used it is important to summarize variances in both net and gross amounts. For example, if you had variances on three items, one being short $50, another short $5, and another over $40, you would have a net variance amount of -$15 and a gross variance of $95. Gross accuracy calculations are a better method of showing true accuracy. In the end, the measurement must be meaningful. If the measurement is not providing information that will allow you to optimize operations, why are you doing it?

Blind Counts.
Now I know I’ll get a fair amount of disagreement on my views on this subject, but here goes. First of all, a blind count occurs when you send your counters out with an item number and location, but with no quantity information. They count the product and write down the quantity or enter it directly into a data collection device. The count administrator then compares the count quantities to on-hand quantities and investigates any variances (usually conducting recounts of each variance). The problems with blind counts are that they have lower first-pass accuracy rates and are more time consuming. Just the action of writing and/or entering the counts creates an opportunity for error. Having someone perform a recount on all variances is necessary on blind counts, this puts greater demands on your resources. If you do blind counts and perform recounts of all variances, this is the most accurate method of counting inventory. However, by giving your initial counters the quantity information and setting a system to just confirm correct counts and only enter variances, you will greatly reduce initial count errors, thus reducing recounts, thus enabling you to count more product with the same amount of resources.
Now don’t get me wrong, there is a downside to giving your counters the quantities. If you don’t keep tight control you may find some counters cheating on items that are difficult to count by just confirming it as correct if it looks close. You also risk honest employees unconsciously making errors just because the quantity is visible. Trust me, when you're doing a lot of counting your mind can play tricks on you, if you see a quantity of 12 on the paper you might look at a stack of 16 and think 12. If you closely monitor the count process and thoroughly train your counters, the benefits of counting more product often outweighs the risks associated with non-blind counts.

Timing.
Timing is critical in cycle counting. In a perfect world you should be able to count and resolve discrepancies with no other processing going on during the count process. If your operation allows you to do this, great, your job will be a lot easier. If it is cost prohibitive or impossible to shut down all other operations, it does not mean you cannot have a successful cycle counting program — it just means you're going to have to work a lot harder at it. You will need a thorough understanding of all operations and must be able to track any transactions occurring during the counts. Even with this you may have situations where it is just far too difficult to get an accurate count on an item that day and may need to skip it and count it again a couple of days later. Whether you are shutting down operations or not, you must have solid procedures and thorough control over inventory operations making sure that all transactions are performed in a timely manner.

Staffing.
Only use highly trained accurate employees to count your product. Specialize if possible. Having employees whose primary responsibility is counting inventory and resolving discrepancies will greatly increase the level of success of the program. In some operations this may not be feasible.

Understand the effects of adjustments.
It is imperative the person responsible for approving and making the inventory adjustments based on your counts understands the effects of these adjustments. One of the biggest problems I see with cycle count programs is that they do not handle “lost product” well. If you have a random storage warehouse and are counting by item, your count program will tell you when you’re missing something but does nothing for locating this lost product. You will need some type of location auditing process in conjunction with this to find the “lost product” or change your program to be based on location rather than item. Meanwhile your count administrator must be making decisions on variances and determining when to make adjustments. In many operations, an adjustment is made one day to deduct the missing product and an offsetting adjustment made a few days later when it is found. The problem with this is the effect this has had on materials management. When the product was deducted, a new purchase order was probably generated to order more product and production schedules and manufacturing orders may have been changed due to the unavailability of this item. Even though the product turned up just a few days later you’ve still caused additional work, disrupted the production schedule, and may now end up with excess inventory on this item. A good count administrator should be able to determine if a variance is due to a process issue or is “lost”. Adjustments for “lost” and “found” inventory should be avoided whenever possible. Creating a variance location to move “lost" and “found” product to and from is a great way to have visibility to the variances without the havoc created by the adjustments. These variance locations must be closely monitored and you must have an aggressive program for finding the product. An aggressive location auditing process will prove to be far more effective than sending someone out to “look for the lost product”. Obviously, tightening up the processes to avoid missing product in the first place makes this less of an issue.
Now I’d like to say that your count program doesn’t need to be this complicated, however, in many operations a complex count program will prove to be the most effective method of dealing with a complex inventory. A good count program combined with solid inventory practices will prove to be a significant asset to any organization. You may still have specific counting demands placed on you by outside sources such as customers and financial institutions. Demonstrating the success of your counting program and inventory practices should reduce or eliminate the need for these special inventories.

Source : Dave Piasecki, Logistic Management.

Warehouse Management Systems (WMS).

2008-04-13T03:25:00.000-07:00

The evolution of warehouse management systems (WMS) is very similar to that of many other software solutions. Initially a system to control movement and storage of materials within a warehouse, the role of WMS is expanding to including light manufacturing, transportation management, order management, and complete accounting systems. To use the grandfather of operations-related software, MRP, as a comparison, material requirements planning (MRP) started as a system for planning raw material requirements in a manufacturing environment. Soon MRP evolved into manufacturing resource planning (MRPII), which took the basic MRP system and added scheduling and capacity planning logic. Eventually MRPII evolved into enterprise resource planning (ERP), incorporating all the MRPII functionality with full financials and customer and vendor management functionality. Now, whether WMS evolving into a warehouse-focused ERP system is a good thing or not is up to debate. What is clear is that the expansion of the overlap in functionality between Warehouse Management Systems, Enterprise Resource Planning, Distribution Requirements Planning, Transportation Management Systems, Supply Chain Planning, Advanced Planning and Scheduling, and Manufacturing Execution Systems will only increase the level of confusion among companies looking for software solutions for their operations.
Even though WMS continues to gain added functionality, the initial core functionality of a WMS has not really changed. The primary purpose of a WMS is to control the movement and storage of materials within an operation and process the associated transactions. Directed picking, directed replenishment, and directed putaway are the key to WMS. The detailed setup and processing within a WMS can vary significantly from one software vendor to another, however the basic logic will use a combination of item, location, quantity, unit of measure, and order information to determine where to stock, where to pick, and in what sequence to perform these operations.

Do You Really Need WMS?
Not every warehouse needs a WMS. Certainly any warehouse could benefit from some of the functionality but is the benefit great enough to justify the initial and ongoing costs associated with WMS? Warehouse Management Systems are big, complex, data intensive, applications. They tend to require a lot of initial setup, a lot of system resources to run, and a lot of ongoing data management to continue to run. That’s right, you need to "manage" your warehouse "management" system. Often times, large operations will end up creating a new IS department with the sole responsibility of managing the WMS.
The Claims:
WMS will reduce inventory!
WMS will reduce labor costs!
WMS will increase storage capacity!
WMS will increase customer service!
WMS will increase inventory accuracy!
The Reality:
The implementation of a WMS along with automated data collection will likely give you increases in accuracy, reduction in labor costs (provided the labor required to maintain the system is less than the labor saved on the warehouse floor), and a greater ability to service the customer by reducing cycle times. Expectations of inventory reduction and increased storage capacity are less likely. While increased accuracy and efficiencies in the receiving process may reduce the level of safety stock required, the impact of this reduction will likely be negligible in comparison to overall inventory levels. The predominant factors that control inventory levels are lot sizing, lead times, and demand variability. It is unlikely that a WMS will have a significant impact on any of these factors. And while a WMS certainly provides the tools for more organized storage which may result in increased storage capacity, this improvement will be relative to just how sloppy your pre-WMS processes were.
Beyond labor efficiencies, the determining factors in deciding to implement a WMS tend to be more often associated with the need to do something to service your customers that your current system does not support (or does not support well) such as first-in-first-out, cross-docking, automated pick replenishment, wave picking, lot tracking, yard management, automated data collection, automated material handling equipment, etc.

Setup
The setup requirements of WMS can be extensive. The characteristics of each item and location must be maintained either at the detail level or by grouping similar items and locations into categories. An example of item characteristics at the detail level would include exact dimensions and weight of each item in each unit of measure the item is stocked (eaches, cases, pallets, etc) as well as information such as whether it can be mixed with other items in a location, whether it is rackable, max stack height, max quantity per location, hazard classifications, finished goods or raw material, fast versus slow mover, etc. Although some operations will need to set up each item this way, most operations will benefit by creating groups of similar products. For example, if you are a distributor of music CDs you would create groups for single CDs, and double CDs, maintaining the detailed dimension and weight information at the group level and only needing to attach the group code to each item. You would likely need to maintain detailed information on special items such as boxed sets or CDs in special packaging. You would also create groups for the different types of locations within your warehouse. An example would be to create three different groups (P1, P2, P3) for the three different sized forward picking locations you use for your CD picking. You then set up the quantity of single CDs that will fit in a P1, P2, and P3 location, quantity of double CDs that fit in a P1, P2, P3 location etc. You would likely also be setting up case quantities, and pallet quantities of each CD group and quantities of cases and pallets per each reserve storage location group.
If this sounds simple, it is…well… sort of. In reality most operations have a much more diverse product mix and will require much more system setup. And setting up the physical characteristics of the product and locations is only part of the picture. You have set up enough so that the system knows where a product can fit and how many will fit in that location. You now need to set up the information needed to let the system decide exactly which location to pick from, replenish from/to, and putaway to, and in what sequence these events should occur (remember WMS is all about “directed” movement). You do this by assigning specific logic to the various combinations of item/order/quantity/location information that will occur.
Below I have listed some of the logic used in determining actual locations and sequences.
Location Sequence. This is the simplest logic; you simply define a flow through your warehouse and assign a sequence number to each location. In order picking this is used to sequence your picks to flow through the warehouse, in putaway the logic would look for the first location in the sequence in which the product would fit.
Zone Logic. By breaking down your storage locations into zones you can direct picking, putaway, or replenishment to or from specific areas of your warehouse. Since zone logic only designates an area, you will need to combine this with some other type of logic to determine exact location within the zone.
Fixed Location. Logic uses predetermined fixed locations per item in picking, putaway, and replenishment. Fixed locations are most often used as the primary picking location in piece pick and case-pick operations, however, they can also be used for secondary storage.
Random Location. Since computers cannot be truly random (nor would you want them to be) the term random location is a little misleading. Random locations generally refer to areas where products are not stored in designated fixed locations. Like zone logic, you will need some additional logic to determine exact locations.
First-in-first-out (FIFO). Directs picking from the oldest inventory first.
Last-in-first-out (LIFO). Opposite of FIFO. I didn't think there were any real applications for this logic until a visitor to my site sent an email describing their operation that distributes perishable goods domestically and overseas. They use LIFO for their overseas customers (because of longer in-transit times) and FIFO for their domestic customers.
Quantity or Unit-of-measure. Allows you to direct picking from different locations of the same item based upon the quantity or unit-of-measured ordered. For example, pick quantities less than 25 units would pick directly from the primary picking location while quantities greater than 25 would pick from reserve storage locations.
Fewest Locations. This logic is used primarily for productivity. Pick-from-fewest logic will use quantity information to determine least number of locations needed to pick the entire pick quantity. Put-to-fewest logic will attempt to direct putaway to the fewest number of locations needed to stock the entire quantity. While this logic sounds great from a productivity standpoint, it generally results in very poor space utilization. The pick-from-fewest logic will leave small quantities of an item scattered all over your warehouse, and the put-to-fewest logic will ignore small and partially used locations.
Pick-to-clear. Logic directs picking to the locations with the smallest quantities on hand. This logic is great for space utilization.
Reserved Locations. This is used when you want to predetermine specific locations to putaway to or pick from. An application for reserved locations would be cross-docking, where you may specify certain quantities of an inbound shipment be moved to specific outbound staging locations or directly to an awaiting outbound trailer.
Nearest Location. Also called proximity picking/putaway, this logic looks to the closest available location to that of the previous putaway or pick. You need to look at the setup and test this type of logic to verify that it is picking the shortest route and not the actual nearest location. Since the shortest distance between two points is a straight line, this logic may pick a location 30 feet away (thinking it’s closest) that requires the worker to travel 200 feet up and down aisles to get to it while there was another available location 50 feet away in the same aisle (50 is longer than 30).
Maximize Cube. Cube logic is found in most WMS systems however it is seldom used. Cube logic basically uses unit dimensions to calculate cube (cubic inches per unit) and then compares this to the cube capacity of the location to determine how much will fit. Now if the units are capable of being stacked into the location in a manner that fills every cubic inch of space in the location, cube logic will work. Since this rarely happens in the real world, cube logic tends to be impractical.
Consolidate. Looks to see if there is already a location with the same product stored in it with available capacity. May also create additional moves to consolidate like product stored in multiple locations.
Lot Sequence. Used for picking or replenishment, this will use the lot number or lot date to determine locations to pick from or replenish from.
It’s very common to combine multiple logic methods to determine the best location. For example you may chose to use pick-to-clear logic within first-in-first-out logic when there are multiple locations with the same receipt date. You also may change the logic based upon current workload. During busy periods you may chose logic that optimizes productivity while during slower periods you switch to logic that optimizes space utilization.

Other Functionality/Considerations
Wave Picking/Batch Picking/Zone Picking. Support for various picking methods varies from one system to another. In high-volume fulfillment operations, picking logic can be a critical factor in WMS selection.
Task Interleaving. Task interleaving describes functionality that mixes dissimilar tasks such as picking and putaway to obtain maximum productivity. Used primarily in full-pallet-load operations, task interleaving will direct a lift truck operator to put away a pallet on his/her way to the next pick. In large warehouses this can greatly reduce travel time, not only increasing productivity, but also reducing wear on the lift trucks and saving on energy costs by reducing lift truck fuel consumption. Task interleaving is also used with cycle counting programs to coordinate a cycle count with a picking or putaway task.
Automated Data Collection (ADC). It is generally assumed when you implement WMS that you will also be implementing automatic data collection, usually in the form of radio-frequency (RF) portable terminals with bar code scanners. I recommend incorporating your ADC hardware selection and your software selection into a single process. This is especially true if you are planning on incorporating alternate technologies such as voice systems, RFID, or light-directed systems. You may find that a higher priced WMS package will actually be less expensive in the end since it has a greater level of support for the types of ADC hardware you will be using. In researching WMS packages you may see references like “supports”, “easily integrates with”, “works with”, “seamlessly interfaces with” in describing the software’s functionality related to ADC. Since these statements can mean just about anything, you’ll find it important to ask specific questions related to exactly how the WMS system has been programmed to accommodate ADC equipment. Some WMS products have created specific versions of programs designed to interface with specific ADC devices from specific manufacturers. If this WMS/ADC device combination works for your operation you can save yourself some programming/setup time. If the WMS system does not have this specific functionality, it does not mean that you should not buy the system, it just means that you will have to do some programming either on the WMS system or on the ADC devices. Since programming costs can easily put you over budget you’ll want to have an estimate of these costs up front. As long as you are working closely with the WMS vendor and the ADC hardware supplier at an early stage in the process you should be able to avoid any major surprises here.
Integration with Automated Material Handling Equipment. If you are planning on using automated material handling equipment such as carousels, ASRS units, AGVs, pick-to-light systems, or sortation systems, you’ll want to consider this during the software selection process. Since these types of automation are very expensive and are usually a core component of your warehouse, you may find that the equipment will drive the selection of the WMS. As with automated data collection, you should be working closely with the equipment manufacturers during the software selection process.
Advanced Shipment Notifications (ASN). If your vendors are capable of sending advanced shipment notifications (preferably electronically) and attaching compliance labels to the shipments you will want to make sure that the WMS can use this to automate your receiving process. In addition, if you have requirements to provide ASNs for customers, you will also want to verify this functionality.
Cycle Counting. Most WMS will have some cycle counting functionality. Modifications to cycle counting systems are common to meet specific operational needs.
Cross Docking. In its purest form cross-docking is the action of unloading materials from an incoming trailer or rail car and immediately loading these materials in outbound trailers or rail cars thus eliminating the need for warehousing (storage). In reality pure cross-docking is less common; most "cross-docking" operations require large staging areas where inbound materials are sorted, consolidated, and stored until the outbound shipment is complete and ready to ship. If cross docking is part of your operation you will need to verify the logic the WMS uses to facilitate this.
Pick-to-Carton. For parcel shippers pick-to-carton logic uses item dimensions/weights to select the shipping carton prior to the order picking process. Items are then picked directly into the shipping carton. When picking is complete, dunnage is added and the carton sealed eliminating a formal packing operation. This logic works best when picking/packing products with similar size/weight characteristics. In operations with a very diverse product mix it's much more difficult to get this type of logic to work effectively.
Slotting. Slotting describes the activities associated with optimizing product placement in pick locations in a warehouse. There are software packages designed just for slotting, and many WMS packages will also have slotting functionality. Slotting software will generally use item velocity (times picked), cube usage, and minimum pick face dimensions to determine best location.
Yard Management. Yard management describes the function of managing the contents (inventory) of trailers parked outside the warehouse, or the empty trailers themselves. Yard management is generally associated with cross docking operations and may include the management of both inbound and outbound trailers.
Labor Tracking/Capacity Planning. Some WMS systems provide functionality related to labor reporting and capacity planning. Anyone that has worked in manufacturing should be familiar with this type of logic. Basically, you set up standard labor hours and machine (usually lift trucks) hours per task and set the available labor and machine hours per shift. The WMS system will use this info to determine capacity and load. Manufacturing has been using capacity planning for decades with mixed results. The need to factor in efficiency and utilization to determine rated capacity is an example of the shortcomings of this process. Not that I’m necessarily against capacity planning in warehousing, I just think most operations don’t really need it and can avoid the disappointment of trying to make it work. I am, however, a big advocate of labor tracking for individual productivity measurement. Most WMS maintain enough data to create productivity reporting. Since productivity is measured differently from one operation to another you can assume you will have to do some minor modifications here .
Activity-based costing/billing. This functionality is primarily designed for third-party logistics operators. Activity-based billing allows them to calculate billable fees based upon specific activities. For example, a 3PL can assign transaction fees for each receipt, and shipment transaction, as well as fees for storage and other value-added activities.
Integration with existing accounting/ERP systems. Unless the WMS vendor has already created a specific interface with your accounting/ERP system (such as those provided by an approved business partner) you can expect to spend some significant programming dollars here. While we are all hoping that integration issues will be magically resolved someday by a standardized interface, we ain’t there yet. Ideally you’ll want an integrator that has already integrated the WMS you chose with the business software you are using. Since this is not always possible you at least want an integrator that is very familiar with one of the systems.
WMS + everything else = ? As I mentioned at the beginning of this article, a lot of other modules are being added to WMS packages. These would include full financials, light manufacturing, transportation management, purchasing, and sales order management. I don’t see this as a unilateral move of WMS from an add-on module to a core system, but rather an optional approach that has applications in specific industries such as 3PLs. Using ERP systems as a point of reference, it is unlikely that this add-on functionality will match the functionality of best-of-breed applications available separately. If warehousing/distribution is your core business function and you don’t want to have to deal with the integration issues of incorporating separate financials, order processing, etc. you may find these WMS based business systems are a good fit.

Source : Dave Piasecki, Logistic Management.

How to be a lean, mean cross-docking machine

2008-04-13T03:23:00.000-07:00

Thinking about adding cross docking to your operation? A materials handling engineer explains what changes you’ll need to make.

Today’s “lean” warehousing managers are trimming the fat by eliminating unnecessary tasks and by improving value-added activities. One strategy they frequently adopt is cross docking, the practice of expediting the flow of product from receiving to shipping with a minimum of handling in between.
Although cross docking has become something of a buzzword lately, it’s a strategy that has been around for decades. Why rehash an old practice? Because cross docking helps shippers address specific business needs that are more important today than ever.
A Little Product, A Lot of Savings
First, cross docking accelerates speed to market by routing items to their end destinations as soon as they are received. “Our cross-docked items literally spend zero time on the warehouse floor,” reports Steve Avila, shipping and receiving traffic manager at Emulex Corporation, a manufacturer of computer hardware that cross docks about 85 percent of its shipping volume. “They go in one door and immediately out the other,” he says.
Cross docking also improves the bottom line. Because product is not sent into inventory, companies that cross dock reduce their storage requirements and consequently eliminate storage-related labor and inventory costs.
McCain Foods USA Inc., which manufactures nearly one-third of all french-fried potatoes produced internationally, has been cross docking its high-volume, fast movers for more than a year. Director of Warehousing Timothy Egan saw the benefits firsthand. “We saved twenty to thirty percent in total warehouse costs by not sending product into storage. And that’s with just one percent of our total SKUs (stock-keeping units) being cross docked,” he explains
Finally, cross docking allows companies to meet customers’ specific needs when time is of the essence. Some examples of such needs include product promotions and other timed marketing strategies, support of just-in-time practices, and consolidation of multiple supplier networks.
Despite these proven benefits, not many companies are cross docking today. Those that do often find themselves cross docking only a small percentage of their shipping volume. One reason, perhaps, is that the concept of not storing product in anticipation of demand is often difficult for managers to grasp.
Egan agrees: “Our supervisors had to change their way of thinking. Instead of storing product in the warehouse, they had to get product out the door and set up labor differently to make it happen.”
Other companies simply don’t know where to start, or may even get involved in cross docking by accident. That was the case for Emulex, Avila says. “We were incurring a tax liability for shipping from one of our plants in Mexico directly to our customers. This forced us to rethink our shipping practice and set up a cross-docking operation here in the U.S,” he says. In McCain’s case, cross docking began as part of the company’s lean, Six Sigma quality initiative in manufacturing and spilled over to its distribution operations.
What, When, and How to Do It
Many times cross docking cuts across interacting functions, including those that happen outside the four walls of the warehouse. It can take a wide variety of forms, from simple pallet movement to complex carton handling involving conveyor sortation systems.
Identifying the most appropriate cross-docking system for your business can require sorting out a complicated web of details.
Regardless of the specifics, though, adopting a systematic approach to managing change will be crucial if you’re to successfully renovate your distribution center (DC) and redesign its operations to accommodate cross docking. The following are some guidelines to help you get started:
Step 1. Product and Supplier Selection
Not all products can be cross docked. The best candidates are those that exhibit high levels of predictability, popularity, and cube movement; these should be identified based on an analysis of each product’s history. Figure 1 illustrates this concept. Other ideal cross-dock candidates include:
Perishable products that require immediate shipment;
High-quality items that do not require extensive quality checks during receipt;
Products that are pre-tagged, pre-ticketed, and ready for sale;
Items for promotional events and initial product launches
Products with continuous, consistent demand, such as “staple” items like milk and toilet paper;
Product moving from one retail store to another;
Pre-picked, pre-packaged orders from another facility;
Back-ordered items.
Supplier selection. Manufacturers that have their own DCs have a distinct advantage when it comes to cross docking. By keeping track of production runs, they can anticipate finished-goods receipts from their regular suppliers and re-route them to shipping as soon as inbound pallets are received in the DC. For retailers and distributors, selecting the ideal suppliers for a cross-docking program tends to be more involved. Choose suppliers that consistently provide the correct quantity of the correct product at the precise time it will be needed. The best suppliers for cross docking include those that can:
Configure products for efficient handling through the next point in the supply chain;
Consistently comply with customer mandates for labeling, ticketing, packaging, and product quality;
Effectively and efficiently share information with their customers.
Step 2. Planning and Designing the Operation
When planning a cross-docking program and deciding on the most appropriate design for your needs, it is important to first assess your current facility’s capabilities. How much change will be necessary will depend on the volume and handling requirements of the products you selected. Typically, when fewer items are being cross docked fewer renovations are needed. The type of handling unit involved also has a significant influence on your setup. A simple, full-pallet transfer from receiving to shipping, for example, tends to be easier to implement than an elaborate carton cross dock that may require complicated conveyor sortation systems. Specific considerations to keep in mind include:
Dock-area layout and capacity. Because most cross-docking activity is concentrated at receiving and loading docks, ensure that you have an adequate number of dock doors as well as enough capacity in those areas. Where possible, eliminate racks to create more dock space. Make sure product can flow quickly and freely through the DC. “At McCain, our only renovation for our full-pallet cross dock was to create new aisles and re-route travel paths to allow quicker access from inbound to outbound doors,” notes Egan.
Yard management. To comply with the rigid receiving/shipping schedule needed for cross docking, you may need a yard tractor and trained driver to move trailers around the yard. A yard manager must also be on hand to ensure that trucks are spotted at the right doors at the right times, resolve equipment issues, and coordinate incoming and outgoing trucks so that delays can be avoided.
Material handling equipment. When cross docking, it’s important to move large volumes of product in a short time. Using double pallet jacks to transport pallets can double throughput. Conveyors that are installed on the floor of truck trailers and connect to inbound and outbound pallet conveyors within your facility can significantly speed up pallet transfer (see Figure 2).
Where appropriate, powered extendibles can aid in loading and unloading cartons as well. Conveyor sortation systems add speed by automatically routing cartons from receiving to shipping and, if needed, to print-and-apply stations for the application of new shipping labels. Figure 3 illustrates a “before” and “after” example of a sortation system that has been renovated to accommodate cross docking.
Personnel. When it’s time to choose managers for a new cross-docking operation, remember that forward thinking is a critical success factor. “Cross docking cannot fully achieve its objectives without a good core of receiving/shipping supervisors and logistical planners who can identify product that needs to be cross docked and redirect personnel to make it happen,” says Egan. Avila agrees: “Supervisors must be able to recognize opportunities for pre-receiving or pre-allocating receipts before the actual product arrives.”
You may need additional personnel to accommodate cross docking’s requirements, but that doesn’t necessarily mean hiring more employees. Some companies outsource their labor requirements to a third-party provider. “With outsourced labor, budgets can be fixed on a piece-rate basis without the hiring/training headaches,” says Scott Orman, West Regional VP of Operations & Business Development for Supply Chain Solutions, an outsourced labor company that provides cross-docking labor for many large retailers.
Information systems. Some shippers have cross docked successfully using paper-based systems, but a real-time, paperless information flow among trading partners is strongly preferred.
Electronic data capture, using bar coding and radio frequency (RF) devices, improves dock productivity by automatically directing the driver to the proper outbound door. It also enables real-time order tracking and reduces the error rates that plague paper-based systems. Even better, radio frequency identification (RFID) tags relay inbound and outbound information without any line-of-sight scanning. Pallet information is automatically captured as arriving and departing shipments pass by RFID portals located on the docks.
Because cross docking moves fast, it’s important to not only capture data in real time but to also utilize it right away. “We track the total number of shortages on orders and discrepancies or damages in product received, and we report in real time so that our customer can adjust, communicate, and fill discrepancies within a fifteen-minute window of the identified issue,” Orman says.
Step 3. Cost Justification and Sharing
How much will it cost to implement cross docking at your company? For both Emulex and McCain Foods, startup costs for their cross-dock initiatives were insignificant, but the savings and benefits were considerable. “We improved inventory turns to six per quarter with cross docking, versus an average of two or three without cross docking,” says Avila.
For a complex, capital-intensive cross dock, it’s best to evaluate the effect on each SKU’s profitability. Where suppliers must take on additional responsibilities, gain-sharing—the practice of sharing projected savings—can be initiated with suppliers that make cross docking in your facility possible.
Step 4. Implementation and Maintenance
As with any renovation, a comprehensive plan will pave the way for a smooth implementation. If you’re a first-time cross docker, start with a pilot program. That will allow you to study the effects of cross docking on a small scale and resolve any weaknesses before rolling it out to an entire product line or network of facilities.
Be prepared for contingencies. This may include keeping a small inventory of cross-docked product in your facility. Standard operating procedures should also be in place so orders are not delayed and product can still be cross docked even when fewer units than expected are received (perhaps due to miscounts or damage). For example, consider redistributing orders and giving priority to your larger customers.
Continuous Improvement
Once your cross-docking operation is up and running smoothly, don’t sit back and assume that your job is done. “Cross docking should be an ongoing, continuous-improvement project,” advises Egan.
Instead, look for ways to get even more benefit from this increasingly popular strategy. For example, supply and demand conditions change constantly, so periodically monitor cross-docked products to determine their sustainability in your program. Another option: For increased benefits, gradually add new products to the cross-docking mix once you’ve
mastered the system.
If successfully planned, designed, and implemented, renovating your DC to enable cross docking can lower your operating costs, reduce inventory investment, and improve product turns—all stepping stones toward a “leaner” warehouse.

Source : Maida Napolitano,Logistics Management.

The cross-dock revolution--are you in or out?

2008-04-13T03:21:00.000-07:00

While it’s certainly not a new strategy, a recent survey tells us that cross docking is gaining momentum as manufacturers and retailers look to reduce transportation costs and increase service levels by increasing the speed of product to their customers. Are you part of the cross-docking movement?

In September 2007, Saddle Creek Corporation, a Florida-based third-party logistics (3PL) provider, announced that it had started construction on a new 60,000-square-foot, high-volume cross dock facility for Sam’s Club in Hattiesburg, Miss. “We’ve seen significant growth in our cross docking for Sam’s Club since we started working with them more than 16 years ago,” says Leta Hardy, director of marketing for the company. “Cross docking’s ability to dramatically reduce transportation costs gives Sam’s Club that all-important competitive edge. ”
It’s not just Sam’s Club that’s been jumping on the cross-docking bandwagon. Hardy says that they’ve been expanding cross docking services for several of their customers—a trend that reflects the industry as a whole. A January 2008 survey of logistics professionals conducted on behalf of Saddle Creek by RBI-US, Logistics Management’s parent company, shows over half (52 percent) of respondents are already doing some form of cross docking in their distribution operations; and another 13 percent are planning to add it to their logistics game plan in the next 18 to 24 months.
The strategy isn’t new. On average, respondents tell us that they’ve been cross docking for the past seven years. Many do it to reduce transportation costs, but most cross dock because they want to increase customer service levels by increasing the speed of product to their customers.
“Times have changed quite a bit,” observes Jeff Wolpov, president and CEO of Distribution Solutions Inc. (DSI), a New Jersey-based third party logistics provider that cross docks mainly for retail clients such as Citi Trends, Stein Mart, Toys R Us, and the Macy’s Merchandising Group. “If you go back 15 years ago, you used to have a three-month shipping window. Today you have a three-day shipping window.” Wolpov further explains how a season used to be three months long. Today a full price season is a mere one week, and then customers suddenly begin seeing markdowns. “You better have that merchandise in your stores during that one week of full-price selling; otherwise you’re shipping into a markdown,” he adds.
Cross docking is simply a mechanism for speed. Product is received in a facility, occasionally consolidated with products going to the same destination, and then immediately shipped without ever going into long-term storage. It requires advanced knowledge of the inbound product, knowledge of the product’s destination, and a system and infrastructure for routing the product to the proper outbound vehicle.
According to Wolpov, established cross-docking best practices today have found retailers shipping a majority of their merchandise—about 80 percent—at the beginning of a season. That 80 percent is being made floor-ready overseas in pre-packs, he says, since the further back you can push value-added services in the supply chain, the more cost effective the labor and the higher your profit margin. “That pre-pack is what gets cross docked,” explains Wolpov. “The remaining 20 percent is placed in inventory where it eventually gets picked as needed to replenish store shelves.”
Whether you are cross docking full pallets of merchandise or breaking them down to case level distribution, cross docking is a tried-and-tested strategy that’s here to stay. In the next few pages, we learn how the strategy has been doing wonders to different parts of the supply chain. In the first case study, Toyota shows us a thing or two about how they are keeping a leg up on the competition. Here they describe how they use cross docking to consolidate parts delivery to their plants. In the second study, we see how DSI has brought cross docking to a whole new technological level for its many retail customers.
Toyota’s need for speed
In the seventies and eighties, Toyota started producing cars and trucks in North America from plants in Kentucky, Canada, and California. Each site planned their logistics support independently with each plant receiving production materials from suppliers in high frequencies and low quantities in keeping with their philosophy of low inventory through just-in-time (JIT) Logistics.
Over the next two decades, consistent with the company’s belief to “build them where we sell them,” the carmaker experienced a rapid expansion with manufacturing plants opening in Indiana, West Virginia, Alabama, Mexico, and Texas. “This expansion resulted in a high level of complexity that became increasingly difficult to manage,” recalls Dave Maxwell, a logistics engineer for Toyota Motor Engineering and Manufacturing North America Inc. (TEMA), a division that oversees vehicle manufacturing and R&D operations for the carmaker.
Suppliers began expressing concern over shipping parts in such high frequencies and low quantities for eight different plants. And with transportation costs escalating, management knew something had to change. “We recognized that leveraging the separate demands into a single, integrated environment would not only make life easier for our suppliers, but we could save miles and still protect the high frequency delivery that is core to our corporate philosophy,” says Maxwell.
By 2000, plans for an integrated logistics network that would support all the plants began to unfold. Steve Hagan, now an assistant manager for Logistics Projects & Planning for the recently-created Logistics Control Division of TEMA, was there from the start.
“Linkage of multiple plant processes into one proved challenging,” says Hagan. “We had a very difficult 18 months learning from our problems and adapting our network to meet our supplier, plant, and 3PL needs.”
However, central to this consolidated logistics theme was the practice of cross docking. Plants determined where there was enough volume to bring freight directly from the supplier to the plant in the frequency required. If there wasn’t enough freight to meet those criteria, then that freight was put into the integrated logistics network and cross docked. The company designed and built cross dock facilities strategically located to minimize miles and maximize support to each nearby manufacturing plant.
Trucks are now dispatched from the cross dock facility to multiple suppliers on specified routes. The driver verifies that each supplier has prepared the proper freight for each delivery, and once the drivers have finished their routes they return to the designated cross dock facility where parts for multiple production runs and multiple plants are unloaded in pallets using regular lift trucks.
Pallets of parts headed for the same area for the same destination plant are immediately consolidated and staged by order sequence. Based on a planned schedule, each plant’s order sequence is loaded onto an outbound truck to be delivered just in time. Maxwell explains that this ensures that the plant receives the proper freight, in the proper condition, in the proper quantity, in the proper sequence at the proper time.
“After full integration in Toyota’s network with all of the plants,” says Hagan, “each plant was able to get miles reduction—and cost reduction—by picking up smaller volume suppliers combined with other larger parts requirements.” Delivery frequency to the plant was increased from 12 delivery cycles to 24, and routing from the on-site cross dock enabled dock-specific routing to each plant. A part delivery truck which used to have multiple stops to different assembly docks in a plant now had one, single-dedicated truck delivery to one assembly dock from its cross dock facility.
Both Maxwell and Hagan acknowledge that although they wouldn’t have done anything differently from their initial implementation, they are still changing and evolving their process to this day. With new plants slated to open in Canada and Mississippi by the year 2010, “we must consistently evaluate the structure of our organization,” says Maxwell.
DSI goes state-of-the-art
DSI has been doing various forms of cross docking for retailers over many years. As business shifted to a more retail-focused environment, more and more cross docks were required at the case level where the actual sort and segregation of inbound containers was often slow and laborious—sometimes taking two workers about three to four hours (or six to eight man-hours) to sort inbound cartons.
That’s fine if you’re doing a couple hundred cartons a day. But to sort 20,000 cartons, it becomes expensive. DSI knew that to satisfy growing customer demands they had to step up their cross docking process. In 2006, the company built a bi-directional sliding shoe carton sortation system that had the capacity to cross dock 70 cartons per minute in their Newark, N.J., facility. With six power unloading lanes and 20 gravity-fed loading lanes, DSI’s Wolpov says the company created a “high-speed, mechanized solution for our cross docking problem.” When asked how long cross-docked products stayed in this new automated facility, Wolpov simply responds, “It doesn’t.”
Working with forwarders, DSI is able to get electronic packing lists of exactly what’s in an inbound container. “With postponement distribution, our customers can create allocations right before we back it into our door,” says Wolpov. This ability allows their customers to change allocation to their stores based on the latest sales figures, weather-related forecasts, or transportation costs variability for different regions.
Cartons are manually unloaded onto powered conveyor lanes and scanned. This scan triggers the carton’s allocation and determines the carton’s end destination. The system then prints out a final destination label that is manually applied. The carton travels for four to six minutes through a network of powered conveyors before it’s diverted to the proper outbound loading lane where it gets stacked into the final destination truck en route to that retailer’s DC.
Despite substantial up-front costs, labor savings of the automated system were undeniable. Wolpov reports a labor savings of about 50 percent; and, from a reporting perspective, the automated system is light years ahead of their manual operation. “I can tell you where every carton is, which truck is carrying it and how many cartons I’ve shipped in an hour,” says Wolpov.
As with every implementation, DSI’s came with a few hiccups. “First we had to learn how to drive this thing,” recalls Wolpov. “Initially, it took 20 hours to cross dock 18,000 cartons. Now, we can cross dock 18,000 cartons before lunch.” Another learning factor was the need to properly manage the trailer yard to sustain the constant fluid work flow required by their cross docking system. “If I can’t get an inbound container in, I’m going to have people standing around and waiting.”
Wolpov explains that it all came down to getting people to understand how the system worked and figuring out the necessary labor required to keep it working.

Source : Maida Napolitano, Logistics Management

Managing the Labor Supply Chain part 2.

2008-04-10T21:23:00.000-07:00

"Labor typically ranges between 35 percent and 65 percent of a company's
distribution and other fulfillment costs," notes Peter Schnorbach, vice
president of labor products at RedPrairie Corporation, a supply chain
technology solution provider based in Waukesha , Wisc. "In many operations,
the cost of labor is greater than that of inventory," he says. Yet "very few
companies really have what we would call a 'productivity program.'"
Schnorbach defines a productivity program as one that involves engineered
labor standards, a process, and technological tools for managing them.
West Marine, Inc., a specialty retailer of boating supplies and accessories
headquartered in Watsonville , Calif. , has such a program in place. But it
hasn't always been that way for the company, which sells through catalog,
Internet, and retail channels, with 365 stores in 38 states, Canada and
Puerto Rico .
Several years ago, West Marine recognized that the performance metrics used
in its distribution centers were not a good measure of the work being
performed, reports Joe Turgeon, director of industrial engineering for the
company.
"Historically, our measures had been based on lines per hour,"
Turgeon says. The metrics didn't reflect product characteristics, like
whether the product being picked was a single roll of rope, an inflatable
boat or an anchor. To address the situation, West Marine decided to
implement engineered labor standards and a labor management system ( LMS )
in its two distribution centers.
After evaluating several potential vendors, West Marine selected
RedPrairie's labor management system ( LMS ). Engineered labor standards and
the LMS were implemented in 2003 in West Marine's 460,000 sq. ft.
distribution center in Rock Hill , S.C. The LMS is integrated with West
Marine's highly customized warehouse management system from JDA Software
Group, Inc.
Moving from virtually no standards to engineered labor standards
was a significant change, so West Marine carefully introduced and explained
the standards, system, and impact to associates and supervisors. Initial
meetings with associates introduced the concept of engineered standards as
well as the timeline and process for the change.
There were plenty of questions and some apprehension initially, Turgeon
observes. Getting out on the floor and answering associates' questions
helped alleviate any concerns they might have had, and the change was well
received overall. "People recognized that lines and units per hour are not a
fair measure," he explains.

Implementation and Training
The engineered labor standards were developed by a team from RedPrairie,
which trained West Marine staff so that they could maintain the program on
an ongoing basis.

West Marine took a phased-in approach to implementation, first implementing
the standards with a core group of some 150 permanent associates. In 2004,
the company's temporary associates - another 150 or so that are added during
the peak summer months - were brought into the standards program. Today, "we
require our temporary associates to be at 100 percent after four weeks,"
Turgeon observes.
Associates receive a goal time through the system, and can check their
performance through one of four terminals located on the floor. "A lot of
times they'll check at lunch, breaks, and at the end of the day," Turgeon
says. In addition, reports are posted daily for the previous day's
performance.
Labor standards are regularly reviewed and modified to reflect
changes in methods, processes, and products. Supervisors use the LMS reports
to plan and schedule work more effectively as well as to track individual
associate performance and identify high and low performers. A top performer
is recognized every month, and low performers are observed, coached and
counseled. In addition, Turgeon notes, supervisors meet individually with
each associate twice a year to discuss productivity, ensure that things are
going well and that no process changes have occurred.
With the engineering labor standards well accepted and integrated into the
DC's operations, West Marine is considering implementing an incentive
program in its Rock Hill DC this year. The operation is a complex one to
standardize, as retail, wholesale, catalog, and internet customers are
fulfilled from the same building, often with different processes. "We wanted
to make sure we had a good grasp of the system before implementing a pay for
performance program," Turgeon says.

Return on investment
Moving to engineered labor standards has paid off handsomely for West
Marine, resulting in a 23 percent improvement in order selection
productivity at the Rock Hill DC . The company has received a strong return
on investment and realized payback of less than a year. "We have more tools
in our toolkit now, and are giving our managers and supervisors better
information that they can use to make decisions on planning the day,"
Turgeon explains. He expects similar results when standards and the LMS are
implemented at West Marine's distribution center in Hollister , Calif. ,
this spring.

What's your maturity level?
Not all companies are as far along as West Marine in
implementing standards and an LMS . In fact, Schnorbach explains, most
companies don't have truly engineered standards and measure productivity at
the key volume indicator (KVI) level, measuring variables such as orders
picked per hour.
"Those that do use engineered standards often don't have a good way of
reporting actual performance back to employees or supervisors in real time,"
Schnorbach says. "It's one thing to have the data - if you're not doing
anything with it, you're not doing much."
In a white paper written by Red Prairie (Optimizing the Labor Supply Chain),
Schnorbach describes Red Prairie's labor productivity maturity model, which
has five levels of maturity:
Base level - There's little accountability for any productivity for
operations.
Manual effort - Individual productivity is measured on units
over time, and is based on historical or industry numbers.
System supported - Engineered standards are introduced for some
activities. Measurements are at the key volume indicator (KVI) level.
Resource optimization - Companies use discrete engineered labor
standards for all activities, and track direct and indirect activities at
the task level.
Future state - Engineered standards incorporate real-time
environmental feeds.

Most companies are at the base or manual effort levels, according to
Schnorbach, and can potentially realize significant benefit - as much as 20
to 30 percent - by moving to a higher level of labor productivity maturity.

The foundation of labor management
For greatest results, "work measurement should be the foundation
of labor management," observes Jimmy Benefield, practice leader of
engineered standards and incentives for Kom International, Inc., a global
logistics and supply chain management firm based in Montreal .
"A lot of companies might be able to tell you basically what
their productivity is, but they usually don't know at the employee level,"
Benefield points out. In addition, many companies know what their
performance is compared to reaching a particular goal, such as number of
picks per hour - but that's just a start. "Unless the goal is based on an
engineered labor standards approach, you really aren't maximizing your
performance, you're just meeting your goal," Benefield warns. "Goals or
metrics based on historical benchmarks don't accurately report the
operation's effectiveness in relation to its capabilities." A goal-based
metric tracks "what you've done in the past, while the engineered standard
is based on what your company is able to do," the consultant says.
Engineered labor standards involve defining methods and each element in a
method, taking into account the unique characteristic of each individual
task. An industrial engineer developing a standard might observe a number of
associates picking into a carton, breaking the work down into elements such
as look for box, reach for box, grasp box, etc., and determining the best
methods to use for a particular task.
Engineered labor standards are well suited to consistent, repeatable,
measurable tasks, such as those found in many DCs. Labor management tools
support use and maintenance of engineered labor standards, monitor
performance at an individual, departmental, and facility basis. Because they
enable more effective planning and scheduling based on real-time
information, they can sharply improve resource allocation and reduce labor
costs. They also provide supervisors data that they can use to help
associates improve their performance. "An LMS can give the supervisor
real-time information, as it is occurring," Schnorbach says.
For instance, if an associate's productivity is at 80 as opposed to 100
percent, an LMS like Red Prairie's can send an alert via e-mail or page to a
supervisor, who can then address the situation right away.

Getting started
Implementing an advanced warehouse management system ( WMS ) by itself does
not constitute a labor management program. While the WMS does improve
productivity, it does not have the time and motion information that can be
found in a labor management system ( LMS ) nor can a WMS track such things
as travel distance or machine timing such as how long it takes to drive a
forklift down an aisle, Schnorbach remarks.
"Maximizing productivity is one of the benefits of implementing a WMS , but
the WMS doesn't really focus on labor. A WMS doesn't provide visibility into
how long it took an individual to pick a set of orders versus how long it
should've taken, or how long for one person versus another."
If you already have an advanced warehouse management system in place, "look
at a LMS as Phase 2" of your implementation, Schnorbach suggests. Your WMS
may have a labor management module that you're not using. "If you're not
concerned about an incentive program, you can go ahead and let the program
track labor performance," Benefield says. Without engineered labor
standards in place, however, you won't necessarily have a standard for
comparing performance. "You'll know that employee A does 50 cartons a day,
and can put in a goal that says you want her to do at least that much a day.
The mistake made is that people stop there," he observes.
"If you really want to define the capability of your company, then you have
to define exactly how long something should take, then compare that against
performance," according to Benefield. That requires the use of engineered
labor standards, which are generally developed by an industrial engineer.
Standards are generally set so that an average person with average skill,
performing at an average rate, will be able to perform at 100 percent,
Benefield says. While the standard is what people are generally capable of
performing, it's not unusual to see less than 100 percent performance. "It's
hard to get people to report at 100 percent unless you have an incentive
program in place," the consultant notes.
Also, engineered labor standards can't be put into place and
then forgotten, Schnorbach points out. "A lot of companies put standards
into place and then don't go back and change the standards," which should be
modified whenever conditions change, as when a process or the layout of the
warehouse changes. "A Tier 1 labor management system handles a lot of that
maintenance for you; that's a key benefit of the system," according to
Schnorbach.
About a handful of labor management tools are available today
offering a wide range of capability and functions. When evaluating tools,
Schnorbach suggests considering the following:
. For a standalone LMS , check out the vendor's integration
capabilities - does the tool have a standard interface for your WMS ? How
many times has the vendor interfaced their LMS with your WMS ?
. How well does the system support incentive programs?
. What kind of support does the vendor provide with respect to
development of engineered labor standards?
. Can the system generate exceptions alerts, if these are
important to you?
. Is time and attendance included in the system's functionality?
. What type of reports does the system generate? Can they be
customized by the vendor, or are only canned reports available?
"Labor management systems are turning into workforce performance
management solutions for the distribution center," Schnorbach notes. "If
you're not using a labor management tool and labor is a big part of your
cost, consider purchasing an LMS " and implementing engineered labor
standards. Together, they make a powerful tool that can help you maximize
the use of your people.

Managing the Labor Supply Chain part 1 .

2008-04-10T21:21:00.000-07:00

"Labor typically ranges between 35 percent and 65 percent of a company's
distribution and other fulfillment costs," notes Peter Schnorbach, vice
president of labor products at RedPrairie Corporation, a supply chain
technology solution provider based in Waukesha , Wisc. "In many operations,
the cost of labor is greater than that of inventory," he says. Yet "very few
companies really have what we would call a 'productivity program.'"
Schnorbach defines a productivity program as one that involves engineered
labor standards, a process, and technological tools for managing them.
West Marine, Inc., a specialty retailer of boating supplies and accessories
headquartered in Watsonville , Calif. , has such a program in place. But it
hasn't always been that way for the company, which sells through catalog,
Internet, and retail channels, with 365 stores in 38 states, Canada and
Puerto Rico .
Several years ago, West Marine recognized that the performance metrics used
in its distribution centers were not a good measure of the work being
performed, reports Joe Turgeon, director of industrial engineering for the
company.
"Historically, our measures had been based on lines per hour,"
Turgeon says. The metrics didn't reflect product characteristics, like
whether the product being picked was a single roll of rope, an inflatable
boat or an anchor. To address the situation, West Marine decided to
implement engineered labor standards and a labor management system ( LMS )
in its two distribution centers.
After evaluating several potential vendors, West Marine selected
RedPrairie's labor management system ( LMS ). Engineered labor standards and
the LMS were implemented in 2003 in West Marine's 460,000 sq. ft.
distribution center in Rock Hill , S.C. The LMS is integrated with West
Marine's highly customized warehouse management system from JDA Software
Group, Inc.
Moving from virtually no standards to engineered labor standards
was a significant change, so West Marine carefully introduced and explained
the standards, system, and impact to associates and supervisors. Initial
meetings with associates introduced the concept of engineered standards as
well as the timeline and process for the change.
There were plenty of questions and some apprehension initially, Turgeon
observes. Getting out on the floor and answering associates' questions
helped alleviate any concerns they might have had, and the change was well
received overall. "People recognized that lines and units per hour are not a
fair measure," he explains.

Implementation and Training
The engineered labor standards were developed by a team from RedPrairie,
which trained West Marine staff so that they could maintain the program on
an ongoing basis.
West Marine took a phased-in approach to implementation, first implementing
the standards with a core group of some 150 permanent associates. In 2004,
the company's temporary associates - another 150 or so that are added during
the peak summer months - were brought into the standards program. Today, "we
require our temporary associates to be at 100 percent after four weeks,"
Turgeon observes.
Associates receive a goal time through the system, and can check their
performance through one of four terminals located on the floor. "A lot of
times they'll check at lunch, breaks, and at the end of the day," Turgeon
says. In addition, reports are posted daily for the previous day's
performance.
Labor standards are regularly reviewed and modified to reflect
changes in methods, processes, and products. Supervisors use the LMS reports
to plan and schedule work more effectively as well as to track individual
associate performance and identify high and low performers. A top performer
is recognized every month, and low performers are observed, coached and
counseled. In addition, Turgeon notes, supervisors meet individually with
each associate twice a year to discuss productivity, ensure that things are
going well and that no process changes have occurred.
With the engineering labor standards well accepted and integrated into the
DC's operations, West Marine is considering implementing an incentive
program in its Rock Hill DC this year. The operation is a complex one to
standardize, as retail, wholesale, catalog, and internet customers are
fulfilled from the same building, often with different processes. "We wanted
to make sure we had a good grasp of the system before implementing a pay for
performance program," Turgeon says.

Return on investment
Moving to engineered labor standards has paid off handsomely for West
Marine, resulting in a 23 percent improvement in order selection
productivity at the Rock Hill DC . The company has received a strong return
on investment and realized payback of less than a year. "We have more tools
in our toolkit now, and are giving our managers and supervisors better
information that they can use to make decisions on planning the day,"
Turgeon explains. He expects similar results when standards and the LMS are
implemented at West Marine's distribution center in Hollister , Calif. ,
this spring.

What's your maturity level?
Not all companies are as far along as West Marine in
implementing standards and an LMS . In fact, Schnorbach explains, most
companies don't have truly engineered standards and measure productivity at
the key volume indicator (KVI) level, measuring variables such as orders
picked per hour.
"Those that do use engineered standards often don't have a good way of
reporting actual performance back to employees or supervisors in real time,"
Schnorbach says. "It's one thing to have the data - if you're not doing
anything with it, you're not doing much."
In a white paper written by Red Prairie (Optimizing the Labor Supply Chain),
Schnorbach describes Red Prairie's labor productivity maturity model, which
has five levels of maturity:
Base level - There's little accountability for any productivity for
operations.
Manual effort - Individual productivity is measured on units
over time, and is based on historical or industry numbers.
System supported - Engineered standards are introduced for some
activities. Measurements are at the key volume indicator (KVI) level.
Resource optimization - Companies use discrete engineered labor
standards for all activities, and track direct and indirect activities at
the task level.
Future state - Engineered standards incorporate real-time
environmental feeds.

Most companies are at the base or manual effort levels, according to
Schnorbach, and can potentially realize significant benefit - as much as 20
to 30 percent - by moving to a higher level of labor productivity maturity.

The foundation of labor management
For greatest results, "work measurement should be the foundation
of labor management," observes Jimmy Benefield, practice leader of
engineered standards and incentives for Kom International, Inc., a global
logistics and supply chain management firm based in Montreal .
"A lot of companies might be able to tell you basically what
their productivity is, but they usually don't know at the employee level,"
Benefield points out. In addition, many companies know what their
performance is compared to reaching a particular goal, such as number of
picks per hour - but that's just a start. "Unless the goal is based on an
engineered labor standards approach, you really aren't maximizing your
performance, you're just meeting your goal," Benefield warns. "Goals or
metrics based on historical benchmarks don't accurately report the
operation's effectiveness in relation to its capabilities." A goal-based
metric tracks "what you've done in the past, while the engineered standard
is based on what your company is able to do," the consultant says.
Engineered labor standards involve defining methods and each element in a
method, taking into account the unique characteristic of each individual
task. An industrial engineer developing a standard might observe a number of
associates picking into a carton, breaking the work down into elements such
as look for box, reach for box, grasp box, etc., and determining the best
methods to use for a particular task.
Engineered labor standards are well suited to consistent, repeatable,
measurable tasks, such as those found in many DCs. Labor management tools
support use and maintenance of engineered labor standards, monitor
performance at an individual, departmental, and facility basis. Because they
enable more effective planning and scheduling based on real-time
information, they can sharply improve resource allocation and reduce labor
costs. They also provide supervisors data that they can use to help
associates improve their performance. "An LMS can give the supervisor
real-time information, as it is occurring," Schnorbach says.
For instance, if an associate's productivity is at 80 as opposed to 100
percent, an LMS like Red Prairie's can send an alert via e-mail or page to a
supervisor, who can then address the situation right away.

Getting started
Implementing an advanced warehouse management system ( WMS ) by itself does
not constitute a labor management program. While the WMS does improve
productivity, it does not have the time and motion information that can be
found in a labor management system ( LMS ) nor can a WMS track such things
as travel distance or machine timing such as how long it takes to drive a
forklift down an aisle, Schnorbach remarks.
"Maximizing productivity is one of the benefits of implementing a WMS , but
the WMS doesn't really focus on labor. A WMS doesn't provide visibility into
how long it took an individual to pick a set of orders versus how long it
should've taken, or how long for one person versus another."
If you already have an advanced warehouse management system in place, "look
at a LMS as Phase 2" of your implementation, Schnorbach suggests. Your WMS
may have a labor management module that you're not using. "If you're not
concerned about an incentive program, you can go ahead and let the program
track labor performance," Benefield says. Without engineered labor
standards in place, however, you won't necessarily have a standard for
comparing performance. "You'll know that employee A does 50 cartons a day,
and can put in a goal that says you want her to do at least that much a day.
The mistake made is that people stop there," he observes.
"If you really want to define the capability of your company, then you have
to define exactly how long something should take, then compare that against
performance," according to Benefield. That requires the use of engineered
labor standards, which are generally developed by an industrial engineer.
Standards are generally set so that an average person with average skill,
performing at an average rate, will be able to perform at 100 percent,
Benefield says. While the standard is what people are generally capable of
performing, it's not unusual to see less than 100 percent performance. "It's
hard to get people to report at 100 percent unless you have an incentive
program in place," the consultant notes.
Also, engineered labor standards can't be put into place and
then forgotten, Schnorbach points out. "A lot of companies put standards
into place and then don't go back and change the standards," which should be
modified whenever conditions change, as when a process or the layout of the
warehouse changes. "A Tier 1 labor management system handles a lot of that
maintenance for you; that's a key benefit of the system," according to
Schnorbach.
About a handful of labor management tools are available today
offering a wide range of capability and functions. When evaluating tools,
Schnorbach suggests considering the following:
. For a standalone LMS , check out the vendor's integration
capabilities - does the tool have a standard interface for your WMS ? How
many times has the vendor interfaced their LMS with your WMS ?
. How well does the system support incentive programs?
. What kind of support does the vendor provide with respect to
development of engineered labor standards?
. Can the system generate exceptions alerts, if these are
important to you?
. Is time and attendance included in the system's functionality?
. What type of reports does the system generate? Can they be
customized by the vendor, or are only canned reports available?
"Labor management systems are turning into workforce performance
management solutions for the distribution center," Schnorbach notes. "If
you're not using a labor management tool and labor is a big part of your
cost, consider purchasing an LMS " and implementing engineered labor
standards. Together, they make a powerful tool that can help you maximize
the use of your people.