Oracle Value Chain Planning Suite (aka former APS )

R12.2 Demantra Pre-release material now available !

2011-10-13T19:41:00.000-07:00

R12.2 Demantra Pre-release material now available !

Oracle has recently updated Demantra documentation library with R12.2 pre-release content. One can access TOI material around new enhancements which will be available with R12.2 release.

Some of the key enhancements are:
1. Import from File: Export to Excel option from worksheet interface has been enhanced considerably to allow users import csv files directly from their desktops to a predefined demantra worksheet. This will surely assist end users in making mass changes or uploading supplementary demand facts like customer forecast or other causal factors.

2. Calendar Month: This was a long awaited functionality which enables customers to build a weekly Demantra data model but still allows them to work at calendar month aggregation level. This enhancement has been in asking list from many demantra customers and will surely assist building more robust but flexible demand planning process.

3. Improved Multi-language support: Building on 7.2 feature of supporting alternate languages with constraint of one language per instance, now 12.2 features supporting multi-languages within a single instance.

4. Other enhancements include:

Improved Date Format
DOL & DA enabled for PTP module
Nodal tuning now available for TPO module
Improved Cost Modeling (ASCP/SNO/Rapid Planning integration)
Promotion and Calendar Optimization

Refer for more details Oracle Support site under metalink note:

Oracle Demantra Documentation Library [ID 443969.1]

Oracle Mix Open World Session

2011-06-16T05:50:00.000-07:00

Vote for this session @ Oracle Mix

Integrated Collaborative Forecasting for CPG Industry

Abstract

This session will explore how an integrated collaborative platform can be build using Value Chain Planning modules to enable usage of POS, Withdrawals, Shipments, Bookings and Trade promotions in building an integrated collaborative forecast using Demantra.

This session will also discuss:
1. S&OP solution options
2. Challenges faced during implementation
3. CPG Success Stories

Vote for this session @ Oracle Mix.

Integrated Causal Exponential Model (BWint)

2011-06-06T15:05:00.000-07:00

Demantra has Integrated Causal Exponential Model (BWint) as one of the models available for analytical engine. This also is a regression model, known as Multiplicative regression - winter model. The model works only in DP mode. It runs multiplicative regression on Causal data (short CFs) and then smooths out the residual series exponentially like HOLT.

Data Type: Good fit for capturing Trends, Seasonality and Causality in demand data.

Example: Here is an example of where forecast is generated by Bwint model of Demantra. Look at how engine is able to capture seasonality and demand trend accurately, providing a good baseline forecast for planners to start with.

Demantra 7.3.1: Fast Divider Engine parameters

2011-05-16T15:19:00.000-07:00

Just a small note for those who wish to be on are on 7.3.1 level.

If you have noticed or are using engine parameters "RunFastDivider" & "RunPartialDivider" in your Demantra 7.3.0.1 install, there is a change awaiting you in 7.3.1 release. While the concept of fast divider which came with 7.3 release to speed up the engine run remains in existence, these parameters no more exist. This was established that these parameters need not exist to support fast divider process, hence Oracle decided to take out these parameters from 7.3.1 release.

Basics of Demand Forecasting

2011-04-03T20:23:00.000-07:00

CHAPTER 5- DEMAND FORECASTING

View more presentations from Bobtb

Few Forecasting Phrases

2011-02-01T10:25:00.000-08:00

Forecasting in business is like sex in society, we have to have it, we cannot

get along without it, everyone is doing it, one way or another, but nobody is

sure he is doing it the best way.

-G W Plossl

Last Frontiers for Profits

Forecasting is like trying to drive a car

blindfolded and following directions

given by a person who is looking

out of the back window

- unknown

All forecasts are wrong

Those who claim to forecast the future

are all lying even if, by chance,

they are later proved right .

Demantra 7.3.1 released

2011-01-31T16:55:00.000-08:00

Few key features which 7.3.1 has to offer are:

Support for Service Parts Forecasting: Seeded integration now available between Demantra and Service Parts Planning(SPP) module. For customers implementing SPP module this integration can help them use Demantra for developing a more accurate Service(Spare) Parts forecast.
Support for Multiple Business Processes: Forecast tree and Causal Factors can now be setup differently for each engine profile, allowing better flexibility around setting up analytical engine for different business processes.
Enhanced Proport: Improved Proport process performance by providing additional parameters to control proport run.
Worksheet Performance improvement: Additional parameters to create parallel hints for specific worksheets which can help in improving the performance of Demantra worksheets.
Support for Rolling Data Profile Groups: Users can now assign rolling data profiles to a group and then can call these groups for execution using workflow. This feature increases flexibility around archiving process within Demantra.

New versions of various Demantra documentation now available in Oracle MySupport @

Oracle Demantra Documentation Library [ID 443969.1]

Demantra 7.3: Engine split based on series

2010-11-17T12:09:00.000-08:00

Whas is NEW ?:
Demantra 7.3 has come up with quite few features which customers have been wishing to see. One of these is ability to split statistical forecast which generated at aggregated level to split down to lowest level based on user defined/controlled proportions. Prior to 7.3 this split was always based on historical proportions and there was no workaround for it. These historical proportions were calculated based on every product and location combinations historical monthly sales averages using proport procedure. Split by series option allows user to pick a series which dictates weights for dis-aggregation of baseline forecast.

How we USE it?
1. Define a new series with server expression, the server expression gets used in weight calculation.
2. Using Business modeler setup parameter: ENGINE > PROPORT tab > parameter name "ProportionSeries" shall be populated with the internal name of the above series.
3. Select combinations/population to use SPLIT MECHANISM by using series "Engine Proportion Method" in a worksheet. The series has two dropdown values, Matrix Based Proportions which is the default and Series Based Proportions which is the value required for series based split.

Oracle Open World 2010: Sales and Operations Planning for the Food and Beverage Industry

2010-08-09T18:57:00.001-07:00

Join us at Oracle Open World 2010 for a session on "Sales and Operations Planning for the Food and Beverage Industry"

http://www.eventreg.com/cc250/sessionDetail.jsp?SID=315911

Oracle E-Business Suite, Virtualization and Cloud Computing

2010-06-18T14:25:00.000-07:00

Oracle E-Business Suite, Virtualization and Cloud Computing

<< Previous Next >>

New and Valuable Capabilities in this Oracle Release
February 3, 2010,
Volume 144, Issue 1

Oracle E-Business Suite 12.1.1 in a five-part nutshell.

In a five-part series on virtualization and cloud topics, Ivo Dujmovic, an architect in Oracle's Applications Technology Integration group, offers a detailed view of the Oracle E-Business Suite 12.1.1 for prospective and current users.

Read the complete article by clicking on this link "Oracle E-Business Suite, Virtualization and Cloud Computing"

Oracle Cloud Computing - Oracle Wiki

2010-06-18T14:23:00.000-07:00

Oracle Cloud Computing - Oracle Wiki

Cloud Computing

2010-04-16T04:50:00.000-07:00

Definition:

As defined by NIST(national institute of technology) Cloud computing is essentially on demand access to computing resources.

It has essential characterstics of on demand self service, resource pooling, rapid elasticity to scale out and scale in, the ability to meter who is using what and broad network access.

Three service models for cloud computing are:
1. SaaS software as a service, is a prebuilt, vertically integrated application/solution delivered to customer as a service.

2. IaaS infrastructure as a service, is purely providing computing resources, storage and network, as service to the client.

3. PaaS platform as a service. is a flexible combination of above two service models and thus customer can develop and deploy their own application using best of both the worlds.

Deployment models:

1. Public cloud, is shared across multiple customers or tenants and is hosted and managed by a service provider.

2. Private cloud on the other hand is exclusive for an organization and is controlled and governed by that organization.

3. Hybrid cloud is where an organization with a private cloud model uses public clouds for any excess cloud service requirements occassionally. Eg an overflow or for additional workload needs

4. Community cloud is a semi private cloud with access to only a set of defined tenants who share backgrounds or needs

What is driving clouds ?

AGILITY AGILITY AGILITY
The fact that users can provision resources on demand, acquire more resources when needed and release them when done with them, is the key driver for cloud computing.

Any drop off which may occur in the interaction happening between two clouds, might just mean a complete loss of valuable services. It is like two clouds up in the sky and informatiin flashin like lightening going from cloud to cloud and cloud to ground, the possibiltiess of loss of energy is inevitable and that is where the core problem of cloud computing lies.

Amazon web services are already in this niche market. For a public cloud to become a feasible solution for small businesses, the need to ensure the security of transaction and data.

Google OS is another such initiative where we will see a huge participation and usage of cloud computing capabilities.

Demantra SIG Webinar: "Infrastructure Rationalization for Demantra Environments"

2010-03-03T07:51:00.000-08:00

Demantra SIG group is coming up with their March month webinar, you can join in for learning and understanding Demantra better.

----------------------------------------------------------------------------------------

"Demantra SIG Webinar - 03/10/2010

Please join the Demantra SIG's March Webinar. Arup Chatterjee will be presenting "Infrastructure Rationalization for Demantra Environments"

Space is limited.
Reserve your Webinar seat now at:
https://www2.gotomeeting.com/register/607944203

Title:		Demantra SIG Webinar - 03/10/2010

Date:		Wednesday, March 10, 2010

Time:		8:00 AM - 9:00 AM PST

After registering you will receive a confirmation email containing information about joining the Webinar.

System Requirements
PC-based attendees
Required: Windows® 2000, XP Home, XP Pro, 2003 Server, Vista

Macintosh®-based attendees
Required: Mac OS® X 10.4 (Tiger®) or newer"

---------------------------------------------------------------------------------------

Understanding Forecast Bias

2010-03-02T10:29:00.000-08:00

What is bias ?

If you observe forecast error going in one direction or other, then you have a forecast which is possibly biased. In the example below try to observe the bias and see if you are able to find the forecast versions with bias.

As you would have pointed out already following is the observation on above example:

Forecast1 has a positive forecast bias
Forecast2 has a negative forecast bias
Forecast3 has mixed bias and the cumulative bias in such case could be insignificant

Decision on whether a forecast is biased or not can be made by reviewing the forecast error as well, study the example below.

Why it exists?

As final forecast is combination of statistical forecast and manual intelligent updates, the bias can slide into Final forecast through any of the mentioned input gateways. While statistical forecast bias are normally specific to items(local bias), bias building up due of manual intervention usually has impact on all the items(global bias).

Manual updates done by forecasters/demand planners at times lead to building of a biased forecast. These updates are driven by various factors like:

- Increasing forecast to match up with volume targets

- Optimistic or pessimistic approach towards forecasting

- Expecting Promotional incremental sales volume

This kind of bias usually has impact on all the items.

Bias found in statistical forecast is most of the times under-forecasting or over-forecasting situation for a specific item-location combination. Few of the cases which lead to such observation can be list as:

- Under-forecasting for complete future horizon due of recent months sales volume showing a down trend.

- A persistent trend in sales volume

Such forecast bias is normally particular to an item or an item-customer combination.

Getting rid of Bias?

Bias shall be removed from forecast as it can assist in improving your forecast accuracy, which eventually reflects across supply chain health. An overall reduction on forecast across all items can take out the global bias(e.g. 15% decrement on forecast numbers all across). For bias which is specific to item, one needs to identify and fix them for every incident by adjusting the forecast.

Fueling supply chain with retailer's POS data - Oracle DSR

2010-02-18T15:24:00.000-08:00

When recession hit the market, the impact on CPG industry was inevitable. With customers trying to save every penny possible, the competition in market for providing best quality product at minimal price possible has surpassed all previous levels. Everyone is trying to get the most of every dollar they spend. Few most common CPG industry specific issues can be easily listed as:

Lost sales due to out of stock conditions
High inventory carrying cost due of misplaced stocking
Promotion expenses going in vain
Loss of margins due of expedition costs
Increasing IT Complexity

Circumstances like this call for nothing but best in class, efficient and optimized business processes which are driven by one and only goal, increasing the profitable revenue making.

The road to accomplish this target is anything but smooth, need is to ensure that the supply chain backbone transforms into an efficient value chain. The value shall be visible and transparent to every stakeholder, be it an internal department(e.g. sales, marketing, operations) or an external vendor. With growing capabilities at retailer's end to capture demand at the point of it's origin, need is to build processes to capture this demand data and utilize it to drive the supply chain. Problem in gathering and utilizing this information is variety of retailer's POS capturing systems, standards and granularity.

One of the AMR Research paper clearly outlines this fact by saying "The Bottom Line: Consumer products manufacturers must centrally manage all demand signal data, including POS, to create a Demand-Driven Supply Network (DDSN) that improves demand visibility to reduce stockouts by more than half and increase Perfect Order performance by 17%"

While in today's generation of supply chain, availability of data is lowest of concerns, problem is with managing this high volume and ensuring the accurate required information is made available to upstream for planning. With variety of sources of POS data, the need to capture and cleanse it prior to it's availability for being used in planning is of high importance.

Oracle's Demand Signal Repository product has shown thought leadership in this direction, by providing a collaborative demand signal management platform with best of breed functionality and reporting capabilities.

Oracle's DSR datasheet points out it's three key capabilities:

Capture and manage large volumes of disparate external demand data
Analyze, report and take action based on Day/SKU/Store level insights
Integrate clean, harmonized demand data to external applications

DSR empowers you to:

Greater visibility of data to better sense, shape and respond to demand
Reduce manual effort and cost
Simplify collaboration across teams and applications.

Oracle VCP Product and processes

2010-02-18T12:21:00.000-08:00

Exploring Demantra's BPM capabilities

2010-02-10T22:42:00.001-08:00

Oracle Demantra's various module releases have a lot to offer for small and medium scale enterprises, who can utilize the out of box processes(best in class) as it is to a lot extent. The standard demand forecasting and S&OP planning process offered with the install benefits the SMBs, but for larger enterprises there is always a need to create a custom process. But, Demantra does have BPM(Business Process Management) capabilities as part of its native platform.

Demantra's platform flexibility allows larger enterprises to build a totally custom tailored process. Some of the already established custom process implementations are:

- Store level forecasting and replenishment planning

- hourly forecasting

- Labor planning

- Safety stock calculations etc.

Basic entities like series, levels, workflows, methods, worksheets etc. are used to create any required custom business processes. The flexibility of designing pretty much any kind of custom process by usage of these entities, makes Demantra's BPM capabilities stronger.

With Demantra being a strong pillar of Oracle's VCP offering, the future road map for its BPM capabilities will be to get upgraded to Oracle's Fusion BPM suite.

(source: Oracle)

Also seeing almost all the Demantra integrations releases already out in market, we expect to see more robust and web-based versions(inching towards Fusion) of Demantra in future.

Model codes used in MDP_MATRIX

2010-01-21T11:11:00.000-08:00

Here is a list of the coding convention used by Demantra, when populating MDP_MATRIX with information about which models were used(column MODEL) and which weren't.(column DELMODEL)

H Holt
J Regression FOR Intermittent
K Multiplicative Monte Carlo Regression FOR Intermittent (ICMRegr)
L Transformation Model (log)
R Regression
E Combined Transformation Model (elog)
C Multiplicative Monte Carlo Regression (CMReg)*
B Integrated Causal Exponential Model (BWint)
F Croston For Intermittent
G Logistic*
A ARLogistic*
X Auto and Linear Regression (ARX)
V Integrated Auto and Linear Regression (ARIX)*
D DailyMultiplicativeRegression*

T Naive Holt
N Naive (if all models failed, a moving average forecast is generated)
NULL No forecast attempt made on this combination.
M Modified Ridge Regression*
NONE Combination remains non forecasted yet, not processed by engine.

E.g. MODEL column has value BFR for a combination, this means engine used models B, F and R to generate Bayesian combined model forecast.

Detailed information about models and parameters is available in Demantra implementation guide.
Refer to "My Oracle Support"
Oracle Demantra Documentation Library [ID 443969.1]

News: Oracle Integrates Financial, Operational Planning

2010-01-20T10:53:00.000-08:00

Oracle Corp. today introduced a packaged integration between its enterprise performance management application and its sales and operations planning software, making it easier for manufacturers to quickly analyze the financial implications of changing customer demand.

Oracle said the new integration between its Oracle Hyperion Planning EPM product and its Oracle Demantra Real-Time Sales and Operations Planning platform is available now. Based on Oracle’s Application Integration Architecture (AIA), the new EPM-S&OP integration provides manufacturers with a way to more easily tie together operational and financial planning processes

.............................................................read the complete article @

http://www.manufacturing-executive.com/news/read/Oracle_Integrates_Financial_Operational_Planning_33238

Engine enhancements in Demantra 7.3 release

2010-01-12T12:15:00.000-08:00

Demantra's 7.3 version has come up with quite a few new enhancements on Analytical engine side. The focus has been on improving the forecast performance, making the AE more robust and faster.

The list of few interesting available features are:
1. Forecast split based on series: Earlier the forecast generated at aggregated level used to get allocated down based on monthly proportions calculated during the proport process. This functionality let's you select a series based from where the proportions shall be picked up for splitting the future forecast.

2. Engine deployment on Linux: Analytical engine is no more restricted to be installed on a windows box, you can install Engine on a Linux box. Engine can be even started and stopped remotely from a browser after doing the required configurations.

3. Forecast output threshold: This functionality provides you more control on engine output, by stating whether or not to write engine output to database, if the forecast numbers are not a lot different from the previous forecast numbers. E.g. if new forecast is 10010, while previous forecast was 10000, then you can mention a threshold so that engine would not try to write the new 10010 output to database.

For complete list of enhancements, refer to metalink's Demantra documentation library.

Bajaj Electrical success story - Oracle ERP, JDE, Demantra & Siebel

2010-01-08T09:24:00.000-08:00

A video presentation on Oracle's yet another success story on a big bang implementation of Oracle ERP, JDE, Demantra and Siebel.

Updates: Oracle Rapid planning 1.0

2010-01-04T07:25:00.000-08:00

Oracle's latest release in VCP suite, Oracle Rapid Planning(RP)'s version 1.0 can be installed only with VCP version 12.1.1

Rapid Planning, an addition to Value Chain Planning products suite

2009-12-31T19:34:00.000-08:00

In May 2009, during Collaborate 2009 event Oracle provided a preview of it's new product "Rapid Planning" and they made a timely release of the product by announcing it's availability on 16th Nov 2009. Rapid planning will benefit customers with it's quicker, real-time, event driven planning and simulation abilities.

Extending the Information-Driven Value Chain

Leveraging its unique web services and open, standards-based architecture, Oracle Rapid Planning customers can enable reduced supply chain decision-making time with the following capabilities:

Fast, event-driven simultaneous material and capacity planning for rapid scenario analysis and real-time evaluation of supply chain events.

Fast sales and operations planning scenario simulation, integrated with Oracle’s Demantra.

Compatible and complementary capabilities to Oracle Advanced Supply Chain Planning.

Mass edit of supply chain data, enabling customers to conduct ad-hoc, rapid scenario modeling without the need to make changes to the ERP data or transactions.

Predictive and actionable insight via embedded analytics, a spreadsheet-style flexible user-interface, and embedded exceptions and scenario comparisons.

Comprehensive constraint modeling to mimic real-life planner decision making such as alternate bills of material, routings, sources and shipping methods, substitution and lead times.

Multi-enterprise visibility and planning, spanning internal facilities and contract manufacturers.

Multi-planner collaboration and simulation to help speed up the analysis and decision-making process.

Integration with ERP to help quickly translate decisions into actions and release planning recommendations directly to execution without latency.

For complete details about product read the complete release article on Oracle's site @ http://www.oracle.com/us/corporate/press/040402

Demantra 7.3 comes clean

2009-10-26T17:00:00.000-07:00

Oracle's latest release 7.3 of Demantra Suite comes with an empty schema, unlike previous versions which had demo data. This surely would be a good news for those who have faced problems while cleaning up the demo data in older versions.

DB issue: Business modeler/Engine Admin cannt connect to database

2009-10-26T15:54:00.000-07:00

Problem: When trying to open Demantra Business modeler on my local install, started getting error "ORA-01033 ORACLE initialization or shutdown in progress ". Also found that while connecting to Engine Administrator I started getting error "Cann't connect to database".

Analysis: Found that even while tnsping to database works, even SQLplus connection to database using Oralce SQLPLUS wouldn't work. It happens at times when the last DB shutdown didnt happen properly. Database needs to be re-started after shutting down explicitly by using SQL PLUS.

Solution:

Using command prompt,

Login as:
> sqlplus /nolog

Once logged in, use following commands:

SQL> connect / as sysdba
ConnectÚ.
SQL> shutdown abort
Instance ORACLE arrÛtÚe.
SQL> startup nomount
Instance ORACLE lancÚe.

While executing this, I got below error:

Database mounted.

ORA-00600: internal error code, arguments: [kcratr1_lastbwr], [], [], [], [],[], [], []

To further fix this issue, used following commands to re-start database:

SQL> startup mount
ORACLE instance started.

Total System Global Area 1073741824 bytes
Fixed Size 1264916 bytes
Variable Size 264241900 bytes
Database Buffers 801112064 bytes
Redo Buffers 7122944 bytes
Database mounted.
SQL> recover database
Media recovery complete.
SQL> alter database open;

Database altered.

Verify that you are able to login into Database and then into Demantra applications. All set and we are back to action.