Think Businessy

Do you think enough about how you think?

noreply@blogger.com (Ian Tomlin) — Mon, 19 Mar 2018 17:48:00 +0000

(Thought for the day... And possibly week)

Do you think enough about how you think? I know that sounds slightly ridiculous but it's quite important.

There's a lot going around the blogosphere about how and why humans need to rediscover being human. This is because, as a race, we've now created our own competition in the form of artificial intelligence (clever humans). Listen to experts like the recently passed Stephen Hawkins and the real-world manifestation of Ironman that is Elon Musk and you would be encouraged to believe we've finally invented something that can erase us from the planet. Perhaps, perhaps not, but robots and AI definitely have the potential to break the economic rule that says growth in the productivity of economies leads to increased wages and therefore more spending power to drive consumer spending.

The other thing we know robots can definitely do better than humans are repeatable, tedious tasks; you know, like the hundred or so ones that people do in the office, like populating forms, crunching data in spreadsheets, producing legal papers and writing articles like this one. Funny thing is, you don't actually know whether it was me who wrote this article or whether I had Encanvas produce it.

And while all of this automation and computing is going on, Otto Sharmer and 'guru's like him are tearing up the conferencing circuit waking executives up to the fact that they don't habitually take in those sparkly fresh ideas with an open mind.... Nope. Most of us are way too quick to 'download' new thinking only to put it into a familiar box. Sharmer argues that those businesses in need of transformation require someone at the helm that does something more than just drop new ideas into old boxes. Afterall, the boys and girls in the fresh fruit markets can sort oranges and apples into the most appropriate box! You're not exactly leadership material nowadays if that's all you know.

As a consultant I'm often speaking to clients about single loop and double loop learning - what the remarkable knowledge management 'guru' Dr. Martin Vasey described as the difference between 'doing things better' and doing better things'. With double-loop learning you really do need humans that bounce ideas around the room (or stick them to walls with PostIt Notes) and are prepared to look beyond how processes work. There was a time for LEAN - when most manufacturing firms really were shoody at repeatedly making products of a high quality. It's now past. If you can't make a decent produce at a market ready price, you're either dead or dying. That's not a watering hole you want to stick around for too long! Yep, douple-loop learning is where it's at, and to do that you need people that think differently.

Naturally, when for decades society has tried really hard to drive the creative types and people with Asbergers (who really do think differently) to the very back of the class, pasting stickers on the back of their shirts like "Here sits an idiot that doesn't follow rules", suddenly these weird - rare kids- have become the nerdy saviour of man-kind. And it's not because they've suddenly learnt how to think linial. No, it's because he or she is a creative thinker that's always comfortable to take risks, question the norms, strive for perfection, because they've never fitted in and so it doesn't feel any different.

So how do you think?

There's actually a name for it... you know, the act of thinking about thinking. It's called metacognition (yup, you can genuinely learn something new everyday).

'Course, Albert Einstein has been misquoted about a million times for saying something like, 'We can not solve our problems with the same thinking we used when we created them.' And he's right.

It's a really useful skill to be able to apply different kinds of thinking, new patterns and shapes to the way we absorb information and rationalise it. Bear in mind, I'm not saying I can do it.

I describe myself as a curvy thinker. I know a lot of straight line thinkers (and boy gosh, they're useful when you need to map a process or step through a problem one step at a time!). but they're less useful when you need off-the-wall thoughts (nice lyric, Michael Jackson). Most people are too constrained by their environment and their education to do anything else but linial thinking. Businesses need all sorts of thinkers - but in a world of transformation and AI robots, it's the creative thinking of humans that sets us apart. Robots are GREAT linial thinkers.

Having the ability to adapt how we think, to NOT think in a linial way, could be the main reason why humans retain a role in the workplace.

So grab your mouse and click on metacognition and see where it takes you. A new idea perhaps?

Ian

What is Robotic Process Automation?

noreply@blogger.com (Ian Tomlin) — Thu, 18 Aug 2016 16:10:00 +0000

http://www.slideshare.net/ictomlin/what-is-robotic-process-automation-rpa

This article provides a simple introduction to Robotic Process Automation (RPA) and provides some insights into the likely impact it will have on enterprise technology procurement, employment and businesses. Included are examples of use cases that are already being deployed today.

Fine-Tune Your Voice of Customer with ODI

noreply@blogger.com (Ian Tomlin) — Wed, 30 Jul 2014 15:29:00 +0000

Applying Outcome Driven Innovation (ODI) Techniques to Quantify Voice of Customer and Translate it into Customer Value

Outcome Driven Innovation (ODI) is a methodology for harvesting customer insights in a way that distills what matters most to customers. Its original purpose was to provide basis of evidence to drive product innovation but I’d argue it has the potential for broader application. In this article I share how ODI is invaluable as a mechanism for Organizational Designers to find new Customer Value by quantifying what the Voice of the Customer MEANS to the enterprise.

Are you familiar with Outcome Driven Innovation (ODI)? I won't blab on about the detail of how ODI came about, the people behind it - or the low-down on how the method works in this article because you can always google it - but I did want to explain why it matters to every organization.

If you've read any of the volumes of work authored by Peter Drucker then you’ll know we share a similar instinct when it comes to customer value. Simply put, most businesses are about finding a source of customer value and then translating that value into a repeatable source of return for stakeholders. It makes sense therefore that businesses should be good at identifying and qualifying customer value and turning it into cashable returns - right?

If you follow this logic then it will probably surprise you how many organizations are 'poor' if not truly terrible at understanding and valuing what matters to customers. It's not that organizations don't invest good money into listening to and understanding customers: Few would claim not to. The problem is HOW they listen and HOW they apply this knowledge.

I’d also say it’s not the case that organizations that are poor at listening to customers automatically fail. Far from it. There are many operationally poor enterprises that continue to make money for shareholders and grow in size and scale even though the do ignore their customers. Take British Telecom’s Openreach business for example. The company has a monopoly in the UK on telecoms infrastructure – so if you’re not happy as a consumer customer, tough! Of course, not every company has the advantage of a monopoly, so if you want to grow and be successful IN MOST CASES listening to customers and sourcing customer value is important, if not essential.

Here's a summary of the challenges of gathering and applying the voice of the customer to organizational design and performance improvement:

1. Not listening to customers

Some organizations spend very little time listening to customers. It could be they are operating as a monopoly and don't care, or they have a pretty solid economic engine and very little competition, so they don't care. Other organizations lose contact with their customers as the enterprise grows and key managers and relationship holders leave, never to be replaced. But this still represents the minority of companies in my experience.

2. Listening, but not well

Organizations will often rely on information gathering mechanisms like customer surveys, forums, complaints and suggestion systems (etc.) to source their feedback. Often, these mechanisms distort the voice of the customer by their design or in the way they are implemented. Other times they employ closed questions (i.e. 'Are you happy or not?') and this doesn't provide the opportunity for customers to 'vent' and really say what they WANT to say. Poorly formalized listening mechanisms can deliver a shallow, hugely inaccurate perspective of the customer voice. I would say something like 80% of companies fall into this category.

3. Failing to route customer insights to the right parts of the enterprise

Attempts to listen to customers generally happen in small silos around the enterprise. While front-line customer service staff, sales people, line managers and others will interact with customers frequently, rarely are these insights harvested and shared. I often see first-hand organizations investing thousands of dollars in listening to customers and then the resulting outputs end up in a file somewhere and never get used. Sometimes surveys and research projects funded by one department can have more value to other parts of the organization but because they’re funded by one silo, other silos fail to access the insight (sad but true and surprisingly common).

4. Interpreting Voice of Customer Poorly

As organizations grow they develop their own culture and ‘biosphere’. They start to apply vocabulary, understanding, norms of behavior and ways of making sense of their market that start to skew HOW managers interpret feedback from customers and markets. Unless care is taken a management team can cocooned itself from customers by assuming it knows what customers care about because the feedback they get only seems to reinforce the assumptions they’ve already built up about their customers and markets. This can result in poor interpretation of the voice of the customer – mostly driven by opinions and false perspectives rather than evidence and meaningful quantitative measures.

5. Ignoring the learning lessons

Organizations that pass through all of these hoops sometimes fall at the last hurdle. When focused on ‘the day job’ and departmental priorities it can be difficult to break out of the cycle and look up for a moment to consider something new. Very often the inflexibility of budgets, organizational designs, norms-of-behavior (etc.) can build up a huge barrier of resistance against considering new ideas and fresh perspectives – the sort of things that come from listening to customers.

Where ODI Comes In

Let’s face it, the picture painted by customer feedback can look unclear. There’s no silver-bullet solution to gathering insights or weighing their importance. For this reason, organizational priorities and interpretations of voice of customer tend to be driven by management opinions. Outcome Driven Innovation (‘ODI’) helps this process by translating the voice of the customer in a more meaningful, measurable way.

The underpinning common sense behind ODI is that people ‘hire’ products and services to get a job done better. Appreciating ‘what the job is’ and then assessing ‘what unmet needs exist’ helps to frame customer feedback into manageable chunks. Of course, when assessing what unmet needs exist, organizations must also qualify ‘how much pain’ does the unmet need create and ‘what’s in it for them?’ so it’s important to understand to what extent is the unmet need to hire something being served by another vehicle, mechanism, supplier etc.

The ODI methodology serves to construct a formalized process to churn the voice of the customer into a measurable list of wants that enables organizations to appreciate what they can do to bring more or so far untapped customer value.

The Relevance of ODI in Organizational Design

My philosophy behind OD is that it should create better organizations by design – better meaning able to produce more stakeholder value, higher levels of workforce productivity, improved customer journeys and a generally more efficient and effective economic engine for churning out customer value and producing the wonderful bi-product that is profitability.

For me, ODI is the essential ingredient to that mix: No strategy should be formed or fashioned into a balanced scorecard until leadership teams KNOW what the voice of the customer is and how their enterprise can translate it into value.

So let me ask you, what matters most to your customers?

Ian.

Latest CIPD Research Says 'Workers Don't Feel Performance Management Systems Are Fair'

noreply@blogger.com (Ian Tomlin) — Wed, 28 May 2014 07:36:00 +0000

Performance management systems deemed unfair by a third of employees

Trust in leaders is at a two-year low according to the latest CIPD/Halogen Employee Outlook survey. The CIPD are calling on managers to step up and talk to their employees about their development or risk losing valuable talent. Almost a third of employees also feel that progression within their organisation is unachievable, with one in five stating that their managers do not effectively communicate objectives and expectations. Last week's poll reveals that 63% of voters believe that employers place too much weight on academic qualifications during the recruitment process.

It's an interesting survey as it exposes the divide between 'what leadership teams think they should be doing' - when it comes to formalizing performance management and establishing robust recruiting protocols - and the real-world practicalities of how a workforce thinks and acts.

In my opinion, the recruitment process has been fragmented in the last decade with ever more filtering mechanisms added to the process to distil the best talent. It's all too easy to use qualifications as a filter, when the majority of baby boomer talent never went to University.

Similarly, performance management frameworks are relatively easy to establish these days but they simply don't work unless they are aligned to the needs of the organization they serve - and few HR teams have the know-how, authority and skill to make this happen without outside help that costs money to procure.

What this survey says apart from everything else is that the devil is in the detail when it comes to talent management.

From Agile Scrums to Codeless Workshops - The Evolution of Enterprise Software Development

noreply@blogger.com (Ian Tomlin) — Tue, 20 May 2014 14:35:00 +0000

Will the transition from Agile Scrum development to Codeless Real-Time Development Workshops be as high impact as the move from Waterfall to Scrum?

The Journey from Waterfall to Codeless Software Development

In the Beginning

For companies that were accustomed to adopting a waterfall project approach for their software developments, the move to agile scrum methods has been dramatic, both in terms of its results and its impact on the size and skills of project teams.

Waterfall describes a traditional software development approach (that dates back well into the 1970’s) where different threads of development are performed by different development people or teams.

When development teams adopt the waterfall method, projects are scope up front and then components are developed in parallel by different people – often employing specialist skills and tools. The number of people involved in projects and the many threads of activity creates a complex project model that then requires expert project management tools, methods and skills to orchestrate (PRINCE2 became the answer to this eventually and led to a whole new set of skills requirements for companies to mince over).

Following development of the various streams of the waterfall, these are bound together and formed into a final ‘end-product’. This approach has been fraught with project management issues. Delays in any of the parallel developments causes the entire project to over-run. Often, ‘next steps’ of integration with third party tools and data, and activities such as testing and tuning, can’t be progressed until the last thread of development has been done. This can result in huge project over-runs and costs.

The article ‘Why Your IT Project May Be Riskier Than You Think’ by HBR (November 2011), that followed a survey of 1,471 IT projects with an average spend of $167m, found that the average overrun was 27%, one in six of the projects studied was a black swan, with a cost overrun of 200%. And almost 70% of black swan projects also overrun their schedules.

Even when projects do get delivered on-time, the consequences of using one or many expert programmatic tools means that documentation is more complex, testing and tuning takes longer, and more bugs are likely to be embedded in the code. EVEN should everything go according to plan, the remoteness of intended system users and stakeholders to the back-room development process means that resulting systems are difficult to get right as a perfect fit to the user community. It’s quite an art to write a paper specification for a software application and produce a perfect system right-first-time. More like impossible in fact.

A major challenge all development teams face is application users and stakeholders rarely know PRECISELY what they need in terms of database management, reports, process workflows and user interfacing requirements out-of-the-box. Normal domain expert business users find it hard to visualize end-applications and often struggle to formalize their end-product in a format that programmers can use.

Accepting the high resourcing costs, need for costly specialist best-of-breed tools, use and constraints of coding and its impact on testing, tuning and adaptability, perhaps the biggest issue of traditional waterfall development tools and methods however lies in what gets left behind. Programmed systems are inherently difficult to maintain and adapt. Companies don’t particularly want to be left with systems they can’t change over time, or that require a team similar in size to the team that built the application to maintain it into the future (mainly because of the dependencies created on a smorgasbord of best-of-breed tools and skills.

The step-up to AGILE SCRUM

Advances in Integrated Development Environment (IDE’s) since the turn of the century, aided by the timely emergence of standards around enterprise web server computing platforms, has produced a number of capable tool-kits to enable software development teams to work more closely together with fewer tools and fewer expert skills. This reduction in tool-kit complexity has meant the project approach has been able to transition more towards a team-based culture where individuals working towards a shared goal can work together in a collegiate way.

AGILE tools are so-called because they provide development teams with more adaptive tools that produce results faster. One aspect of the ‘agility’ comes from using bigger building blocks of code that can be shaped to fit a variety of needs but doesn’t require programmers to start with a blank page.

The SCRUM model has evolved around the need for members of development teams to keep in close contact with one another and stay on the same page. More frequent reviews of progress – perhaps on a weekly, even daily basis – ensures that the streams of development stay on-track and can be regularly check to ensure the quality of the end-product is as it needs to be and that project managers can check time and again that ‘what is being produced’ is ‘what the internal client wants’.

AGILE tooling does not provide developers with everything they need in one box. To improve the integration and use of third party expert tools, software providers today normally provide an Applications Programming Interface (API) so the various tools are EASIER to integrate with one another. While this is EASIER it remains a major overhead on developments as each API tends to be different and developments inherit any limitations presented by the ‘black box’ of functionality provided by the best-of-breed software they are integrating with. This inability to interplay one application with another using the same properties means that developers find themselves constantly having to come up with work-arounds to produce the best end-product.

SCRUM has its limitations too. While it’s great for developer teams to work towards a common goal and take more of an active interest in making sure their contribution is producing the best ‘total’ outcome, developers continue to work in back-rooms and continue to lack an appreciation of the domain area they are building applications for. Any developer knows the ‘last mile’ (i.e. managing the interaction with the user and stakeholder communities) is the most difficult part of an application to get right as different user groups will have very different expectations and needs from the applications they use.

Like the traditional waterfall approach, AGILE SCRUM still relies on coding and that’s a problem. Not only does it install more post–development overheads are more bugs are built into the end-product, and more testing, tuning, integration is necessary, it means that resulting applications continue to be expensive to maintain and adapt.

The New Age of Codeless Development

So-called ‘codeless’ development software describes Integrated Development Environments that displace the need for applications authors to code. The leading enterprise platform for this approach is Encanvas. All of the building blocks required to develop enterprise applications are built into a common IDE. ‘Design Elements’ - as they are known - adopt similar properties and have been designed to provide a sufficient level of tailoring to fit the majority of needs.

At one time, it was thought that codeless platforms would be only good enough for piloting of projects or serve ‘little application’ needs of the enterprise where larger platforms were too costly to use. The last decade has shown however that IDEs like Encanvas are capable of delivering enterprise, pan-regional and cross-industry applications to enterprise scale and levels of performance.

In the same way that a step-change in enterprise web platform standards at the turn of the century led to the evolution of SCRUM methods for software applications authoring, use of codeless tools has led to the formation of near-real-time applications authoring methods.

With codeless software, the removal of the programming activity in project (and the removal of best-of-breed tools and the need for APIs) has meant that users and stakeholders can be engaged in development workshops where applications designs are iterated in consort with the users and stakeholders who are able to see and understand what’s being authored because they see the ‘end-product’ being formed in-front of their eyes.

Codeless software has dramatically reduced the number of tools and the variety of skills needed to author applications, but its biggest impact is found in the leave-behind: resulting systems can be easily adapted as business requirements and user needs change. Neither are there any upgrade costs associated with software; platforms like Encanvas enable hundreds of applications to be authored and do not charge for any new improvements to the IDE. This means IT leaders seeking to reduce the number of technologies they support in their enterprise IT architecture can shrink their footprint from 100’s of tools to less than 10.

The bi-product of this change in technology tooling and methods makes a big impact on IT budgets. The expectation of IT leaders now is that IT operations should cost no more that 1% of operating profits. Deployments delivered through codeless workshop development methods demonstrate a factor of 10 increase in time-to-market and a similar dynamic in the lowering of onward IT costs.

Will the move from SCRUM to CODELESS be bigger or smaller than the move from WATERFALL to SCRUM?

I would argue the move from SCRUM to CODELESS has a greater bottom-line impact but a lesser change impact compared to the original transition from WATERFALL to SCRUM for the following reasons:

IT departments have already shrunk their internal IT teams and now use contractors for much of the heavy-lifting in software development and support. What the move to codeless does is internalize the support of IT systems – making IT more adaptive and better able to support the long-tail of demand for new or better enterprise applications - while displacing the use and cost of contractors.
IT departments are already using IDEs and reducing their use of specialist tooling. Platforms like Microsoft .NET and Ruby-on-Rails have done much to consolidate tooling for developers. What Codeless platforms do is FURTHER consolidate tooling.
IT leaders are already finding ways to embed IT development skills ever closer to the domain expert communities that use applications. What codeless software does is take development out of the back-room into the front-office workshop so that developments produce faster, better results that the users and stakeholders WANT to use because they were instrumental in the design of applications they use.
IT leaders are already rationalizing the numbers of technologies they support in the enterprise technology stack. What codeless software does is further reduce the footprint of technologies employed across the enterprise to install more commonality in development methods and tools.
Arguably the biggest change factor then with codeless workshop development lies in the impact of an IT department being able to keep-up with the ideas and process changes of the enterprise. This has surprisingly big organizational design implications. For decades people in the business have been able to BLAME IT for failing to support their domain needs. Consider what happens when suddenly it does: No longer is IT the scape-goat. Also consider the impact of embedding software development into improvement teams as some innovative companies like AUDI GROUP already do. The analysts that scope and build the applications are PART of the improvement team, incentivized by the impact of the process changes they manifest rather than being paid for ‘writing code’. Departmental and operational managers will be inevitably more responsible and accountable for IT as part of their function. They have no choice but to consider the performance of the IT they use as being part of their portfolio of responsibility. The role of the CIO becomes one of guardianship of IT resources rather than the deliverer of every single IT initiative.

Keywords: Waterfall, Agile, Codeless Software Development, CAAD, Encanvas, Software Development Methods, ALM, Application Life-cycle Management

Secrets of Going Codeless

noreply@blogger.com (Ian Tomlin) — Mon, 19 May 2014 19:00:00 +0000

How to Build Enterprise Apps without Coding

Building applications without code still requires methods and skills. In this article I describe the methods that Encanvas has used for well over a decade to successfully deliver situational applications developments.

The first application created on Encanvas in a codeless form was a silly form for appraisals. That was in 2002 I seem to recall. Since then the size and scale of applications authored 'codeless' have included several enterprise-wide systems, a few pan-regional systems and even industry-wide systems.

In the early years of Encanvas, most of the applications were created by Andrew Lawrie (the creator of Encanvas) himself. It was impressive enough that Andy could take an enterprise requirement and just 'make it happen' all by himself, but since then the community of Encanvas authors and architects has grown exponentially.

The types of backgrounds of authors too is wide and varied. I've produced a few systems and my background is generally sales and marketing. A couple of the guys are 'proper developers' that have sold their soul to the codeless god, while many are domain expert consultants, entrepreneurs, project managers and analysts. What do they have in common? They can all use a mouse I guess!!

As the scale of applications gets bigger, and the variety of author skills broadens, it becomes more important to adopt methods to optimize the authoring process. No question, it is possible without method to be able to produce results with codeless software, but then that places a 100% reliance on the talents of the practitioner.

CAAD came out of a series of 'interventions' to streamline the codeless authoring process that all hang together pretty well and perform certain key tasks well (like requirements gathering).

Hopefully you find the linked document interesting and easy enough to absorb. If you have any questions, I'd be happy to field them.

Ian.

Keywords:

Enterprise Applications, Codeless Software Development, CAAD, Encanvas, Situational Applications, IT Strategy, Application Life-Cycle Management

CAAD Codeless Software Development Methods

noreply@blogger.com (Ian Tomlin) — Fri, 16 May 2014 10:59:00 +0000

CAAD Methods

I produced this article to describe how analysts can build enterprise-scale situational applications time and again without coding based on the methods adopted by the team at Encanvas over the past decade. The methodology hasn't changed too much over the past few years but we continue to learn from customers and practitioners.

It's only in the last three or four years that we've honed the use of Outcome Driven Innovation (ODI) and Blue Ocean methods as part of this approach.

One of the factors that we've found critical to success is to specify the requirements, outcomes, user group structures, reporting needs (RPRS Analysis) etc. BEFORE jumping into a meeting room and workshopping solutions.

It's great to work in a collaborative way but having the structures and outcomes buttonned down means that analysts can get to work on the boring 'basic modelling' of a solution and have something to walk around before users and stakeholders start iterating their design.

I hope you find it helpful!

I.

Keywords:
Codeless software development, CAAD, Software Development Methods, Agile Software Development Methods, Encanvas, Enterprise Situational Applications Development Methods

Sub Surface Spend

noreply@blogger.com (Ian Tomlin) — Fri, 09 May 2014 21:07:00 +0000

Slideshare presentation on sub-surface spend

In this presentation I argue the case for federated spend management software tools as a vehicle to affordably source sub-surface spend economies in organizations where procuement teams have harvested the low hanging fruit and now need to consider digging deeper into spend behaviors to achieve the next stage of procurement economies.

Key words:
Sub-Surface Spend, federated spend analysis platforms, encanvas, situational applications, data mashups, actionable insights, procurement strategies

$ub-$urface $pend - Mining the Untapped Spend Economies

noreply@blogger.com (Anonymous) — Tue, 06 May 2014 15:50:00 +0000

How Federated Spend Analytics Software taps into hard-to-reach sub-surface spend economies with its ‘all seeing eye’ and fine-grained analysis

Federated Spend Analytics Software is cloud-based business software that places a lens across back-office administrative computer systems to expose areas of potential spend economy. In this article I explore how the latest generation of cloud-based applications platforms are facilitating fine-grained analysis of spending behaviors to expose new opportunities for cost reduction and efficiencies in the procurement function.

People not acquainted with procurement so often see the discipline as a reactionary back-office function, but anyone who’s dealt with high performing procurement teams knows that it’s one of the few discipline areas tasked with looking ACROSS the silos of operation that tend to build up in organizations; giving procurers the opportunity to invest time in seeking better ways of working and find cost reductions through more thoughtful buying approaches.

Although there is no single journey to better ways of buying, procurement teams will quite sensibly start most cost reduction initiatives by tackling the highest spend areas first. Next will come the poor performing or poorly controlledareas spend. Then a third tranche of cost economies is gained through rationalization and compressing the supply-chain (these are typically more complex ‘root and branch’ changes that demand more transformation and change in the way the enterprise works and so quite sensibly fall further down the transitional scale even though sometimes the rewards can be something akin to a step-change).

As procurement teams venture through this life-cycle, they change their own DNA and move from being reactionary to proactive. Mature procurement teams might well have delivered ALL of these initiatives and are now on the march to find new sources of stakeholder value, cost reduction and improvement (think of it as a mining company that initially searches out mineral reserves on the surface to then move deeper and deeper through the strata in search of new reserves). Contemplating this next-stage sub-surface procurement initiative is where many procurement leaders now find themselves – but they also know, to achieve the best results whilst keeping their own operational costs down, they need better exploratory tools for their teams.

But for what benefit? The obvious areas of cost economy in sub-surface procurement initiatives comes from better understanding the ‘when, where, hows and whys’ of procurement behavior to then benchmark approaches to ‘best practice’ (sometimes happening in different industry sector) to then install new behaviors. Unfortunately, the cost of sub-surface procurement changes can rack up unless procurement professionals gain the tools to more easily speculate on areas that look on the surface to be efficient. Time-to-value in turning potential weaknesses in procurement to rewards in terms of cost savings becomes a key measure of success.

One hurdle that most procurement teams encounter when transitioning from a ‘reactive’ to ‘proactive’ procurement stance then is the need to source richer spend-analytics across all disciplines. This is the role of spend analytics. But where spend analytics software tools generally fall down is not in their scope of use, or ability to present insights, but in harvesting existing data for analysis.

Few organizations truly operate ONE computer system across their business. Even companies that have committed to a core technology stack - such as SAP, ORACLE, IBM or MICROSOFT - will often have multiple ‘systems’ of their chosen platform to cater for disparate operating divisions, geographical variances, group companies (etc). This means SOMEHOW data needs to be harvested, mashed together and normalized, then presented in a data-mart that allows it to be interrogated.

Like most systems that revolve around ‘people being curious’, good Spend Management systems don’t simply regurgitate data in the form of charts and dashboards, what they do is provide a platform for users to ask new questions about what, where, when, how, why and whom in the enterprise spends money.

Federated Spend Analytics platforms are the newest breed of performance tooling for procurement professionals operating in large and complex organizations. Federated platforms should as a minimum provide the following capabilities:

Harvest data from existing applications without requiring manual interventions
Transform and normalize data to produce coherent data perspectives
Form a unifying data-mart that auto-refreshes with the latest data from back-office systems
Present user interfaces supporting interactive charts, maps, dashboards, side-by-side comparison tables and other visualization tools to distill key facts
Support the ability for users to create their own KPIs, alerts, chart and map views
Install RASCI role accountability to spend analysis process
Provide an always-on (secure) platform accessible via browser-based devices
Scale to meet enterprise needs

By implementing a Federated Spend Analysis platform, what should procurement teams expect? While each organization will benefit differently from adopting a federated system here’s a quick run-down of some of the more common ROI outcomes:

Add

Multi-threaded sourcing and multi-linking of data; Tooling to harvest data from multiple sources and augment automation of information flows to route data and place it into a data-mart
Ready-to-use design elements; Tooling that provides self-service creation of situational applications and analytical dashboards, interactive charts, maps etc. without coding.
The means to be curious; to ask ‘when, where, how and why’ questions without hugely increasing frictional costs associated with the enquiry process itself (such as time spent authoring reports, sourcing data, manual data entry and data crunching, time spent working spreadsheets etc.).
The means to expose fine-grained economies; which, by minimizing enquiry and analytical costs, become economic to act on.

Grow

Opportunities for sub-surface procurement economies by distilling fine-grained operational behaviors (made affordable by reducing enquiry/reporting/analytics unit costs).

Reduce

Time-to-value; expose weak-points in procurement faster by having the ability to interrogate data rather than creating and running ad-hoc reports time and again in the hope that a sub-optimal behavior will be uncovered.

Remove

Reporting and analytical overheads
Software change/upgrade costs
Technology complexity; save on the number of tools needed to harvest, analyze, report, share insights and related cost of authoring situational applications to ACT on learning lessons.

If you have implemented projects/tools to source sub-surface spend economies it would be great to hear about them. Otherwise, if you’ve yet to explore the potential for sub-surface spend projects I would be happy to talk over the subject with you.

The fastest route to achieving operational excellence lies in re-mastering your enterprise DNA 'digitally' as a 3D data cube

noreply@blogger.com (Anonymous) — Thu, 01 May 2014 11:36:00 +0000

Managers driving HR, compliance and performance initiatives need 3D (CUBED) federated data perspectives – but how do you get clarity when data is siloed in hybrid enterprise software applications? And why does it matter?

As an organizational designer I spend much of my week working with business owners and line-of-business managers leveraging people assets, reducing costs – and more recently installing more robust policy governance and growing performance. One of the more challenging aspects of my role is helping non-IT people get their head around the importance and value of looking at data in multi-layered perspectives rather than on ONE flat view.

Consider process accountability for example: All organizations have capabilities (things they do to create customer value and sustain their business continuity) supported by a cascading tree of mission critical processes, then sub processes, and process steps. Each process step SHOULD have a matrix of role accountability, responsibility, things to be done etc. From an organizational design perspective I need to know EVERYTHING about the fine-grained action that happens right at the bottom in order to make sure it happens, and that it happens right. That means I want to look at each action from the perspective of being a customer (customer science), being a shareholder, its contribution to strategy (performance), how often it doesn’t happen and the consequence on customer value produced (Six-Sigma), the impact on policy governance and risk (compliance)….

…and today, in most businesses, you can’t do that.

So what? Why is it so important to digitize the DNA of an enterprise?

With a 3D digitized view of your enterprise, decisions can be made through more useful insights. Leaders and managers can ‘ask their own questions’ and be curious about how the business works. When things don’t happen as they should, it’s easier to spot. NEW LEARNING that results from customer and stakeholder feedback can be directed to the right places in the enterprise where these lessons can be applied. Digitizing the enterprise is fundamental to understanding, is fundamental to operational excellence, compliance, performance, success!

All too often, business leaders want the outcome of projects ‘by tomorrow’ (quite understandable!) and so the last thing they ordinarily want to do is start at the very top of the tree formalizing a data model of the enterprise. They’d rather pick the low hanging fruit. They want to see the swishy dashboards - and they don’t care how the data gets there. But, if you want accurate perspectives on data and you want to be able to examine topics (and answer new questions) then SOMEONE has to build-up the DNA of the enterprise into a reliable data structure. When this preparatory work isn’t done it means consumers of the data are likely to misinterpret what they’re seeing. This can lead to all sorts of bad outcomes and consequences.

Invariably, taking these short-cuts can move things forward quickly to begin with, but every successive step takes longer, and the absence of a unified data-mart to interrogate means that every question requires a new report, a new spreadsheet, another new process… aaargggghh!

One time my satnav took me the quick way to Edinburgh late one week-day as I made my way to a conference from my home in The Midlands, England. A little after 11pm I found myself cross a cattle grid on top of a wind-swept hill with cows watching my progress on all sides! Some shortcuts are not worth taking.

What people do ‘get’

Appreciating how data works in cubes can be thoroughly mind-blowing, but what people do ‘get’ are spreadsheets. Most business people work with spreadsheets – and as everyone knows, spreadsheets are great to use and very versatile for looking at data. Whilst they can also be exploited and multi-layered using pivot-table features, most folk will use spreadsheets in a flat format where each spreadsheet compares ‘x’ data by ‘y’ data. That’s great – to a level, but when you want to examine ‘x’ by ‘y’ from the perspective of ‘z’ spreadsheet skills start to separate the men from the boys.

Organizational Designers need software too!

I find that most enterprises don’t hold data in very useful ways. IT systems are purchased from each department or discipline – and every application manages its own data in its own ways, under different labels. That’s a problem for me as an organizational designer.

It’s not until you have a 6000 column by 8000 row spreadsheet that you realize, as an organizational designer, you’ve not got the tools you need to become ‘operationally excellent’. Many stakeholders have a deep interest in data that describes an enterprise, what it does, how it delivers what it does, what it produces. Fundamental to Compliance, Governance, Risk, Performance, Human Resources Management and many other disciplines is the fundamental knowledge of:

• How is the organization structured (in terms of legal entities, organizational units, roles…)?

• What is its strategy?

• How is the strategy executed?

• What are the processes that are critical to its success?

• What ACTIONS must be done to achieve the plan and run the processes?

• What is the stakeholder value (particularly the customer value) produced?

All of the above requires landscape views of data that aren’t normally accessible to organizational designers because the data is not held in a form that lets you slice and dice the data.

The answer IS NOT Business Intelligence

Scale data analysis projects to enterprise data proportions and we have to deal with the thorny issue of data being held in silos of operation and ‘data silos’. The last few years have seen many different forms of so-called ‘business intelligence’ software platforms enter the market to solve the issue of helping leaders and managers understand what’s happening in their business by interrogating back-office data silos. The problem with all of these systems is they consistently fail to answer the ‘so-what?’ question.

You see, most things that leaders and managers want to know they don’t measure because they’re new questions (were they old questions then they’d already have systems and people in place to manage the process!) That means most actionable insights are answers to new questions. The problem for Business Intelligence tools is that it takes SO LONG to formalize the root and branch data structures needed to reliably get at data from wherever it’s being held that it becomes inflexible.

Moving forward

To make organizations BETTER BY DESIGN, business leaders and organizational designers MUST be able to understand how their organization works in 3D to deliver perspectives on operational activity that are needed to deliver optimal customer value, meet compliance expectations and drive performance.

It’s said ‘there are many ways to skin a cat’ but the solution we’ve developed here is to use a private-cloud platform called ENCANVAS to produce an adaptive lens across existing data repositories that removes the challenges of ‘getting hold of data’ and ‘organizing data into cubes’ through its built-in data connectors and transformation tools. What gets produced is a personalized data cube that produces ‘always purified data’. ENCANVAS also offers a suite of compliance, performance and operational analytics (reporting) tools to then allow senior managers and organizational designer to construct their own applications and views on data.

We’ve used the ENCANVAS platform to construct our own Organizational Design tools to facilitate the production of 3D cubed views of data for Human Resources Management, Performance and Compliance.

The reason ENCANVAS works when other systems don’t is because of the fact it works like LEGO® bricks and removes the need for IT projects or coding to produce the required outcomes. It humanizes the process of shaping technology to do our will rather than the other way around. You can ‘shape the bricks’ in workshops with stakeholders to make sure the outcomes work for the organization and the users.

Of course, a few rules apply:

Garbage in, garbage out – If your operational systems produce trashy data, ENCANVAS can purify and treat most of it, but if the data isn’t being captured (or captured correctly) that can become a problem.

Technology is never the answer – ENCANVAS, and platforms like it, are just tools; by themselves they never solve anything. What’s needed are domain experts that fully know their processes and how the processes need to work.

Ian Tomlin is European Regional Manager for US Tech Solutions Inc. and advises on federated solutions for compliance and performance, customer science, actionable insights and organizational design.

Has Google got it's business model wrong? (What happens when you don't need a map of the Web anymore?)

noreply@blogger.com (Anonymous) — Tue, 22 Apr 2014 13:01:00 +0000

Google's logo. One of the most familiar beacons of all that is good about the web - and the best story of what it takes to become a successful corporation in the 2000's. Or is it? (It's a registered trademark by the way of Google Inc.)

There are some things that business people take for granted - new startups take longer to make money, cash is always king and Google is one of the best examples of a successful business. Rule-101 of business says that the ground you walk on is never as stable as you think it is - so has Google got it right?

It's my opinion that US investors are way off the mark on tech company stock values. Recently Twitter launched and was greeted with enthusiasm, a little while before it was Facebook's turn. But seriously WHERE IS THE VALUE?

As an enthusiast of all things social network oriented and web oriented you might think me a weird source of criticism for valuations of companies that in many respects fly the flag for our industry - but my origins are not in the technology sphere and so I guess I'm not a purist. I've also been on the wrong side of investment discussions in tech-startups in the United Kingdom - a country that has absolutely no appreciation of how to value software (our government could make 'How not to make a software industry' a degree level subject-matter area).

The strongest commercial argument for web-community centric companies is that communities are places where advertising can happen and this is perhaps the future source of 'places to find new customers' which is an obvious draw for commercial organizations willing to invest in sourcing new business. At the head of this crowd is Google. The basic 'reason for being' of Google is to provide the people of the world with access to the content of the world. It is the defacto search engine for the majority of western world surfers and stands alone in the quality of its search engine and its ability to find stuff online.

Makes sense then that Google should have a robust future - it 'owns' the map to the Web.

But what if you didn't need a map?

Our future has a habit of following the past. The closest parallel we have to the future of the community-centric 'social' web is the 19th Century evolution of coffee houses in London. When coffee houses were introduced they quickly became 'a place to meet' for any type of community that wanted to gather somewhere (sound familiar?). What happened next is particulalrly interesting; specific communities began to gather in SPECIFIC coffee houses - 'Lloyds' coffee house was where the insurance folk would meet, 'Rainbow' was where the poets, actors, politicians and other luvvies would meet, and so on. News soon went around that if you want to meet other like-minded people talking about YOUR area of interest, 'this or that' coffee house was the place to be. The evolution of coffee houses led to the formation of Lloyds of London, the London Stock Exchange and, some might argue, was the instrument that eventually to our free press.

Let me know bring this diversion back to topic. When I use the web, YES I do use Google to find things, I use twitter to share things and I take advantage of these sites. But I don't pay anything for the services I use. What I don't do is USE the adverts that are regularly placed on these sites. They don't influence my buying decision. Why not? Because when I want to buy a car I go to Autotrader.com, when I want to find a hotel room I go to Hotels.com, a flight? Opodo, a house? Rightmove... and if I want to buy anything else I go to Amazon.com. These are the market-places I trust and I return to time and again. So how often do I search for things that I want to buy? Answer: Much less than I used to and the number of searches I do is shrinking as days go by because I know where to find what I need - 'I KNOW THE COFFEE HOUSES'.

What does this mean for US Tech Stocks? In my opinion, it means they're resting on shifting sand and are highly unlikely to return the values their stock valuations might suggest. In the last quarter Google's own stock dropped. I expect it will not be the last time this happens as advertising incomes fail to show their promise.

The winners of the battle for hearts and minds (and advertising spend) in the future will be those sites that become synonymous with a TYPE of community, a genre of buyer. There will always be coffee shops, but there is only one Lloyds of London, only one London Stock Exchange.

Sorry Google, you've got it wrong.

I.

China tech is on the rise - so will we be returning to the English Language?

noreply@blogger.com (Anonymous) — Wed, 15 Jan 2014 08:29:00 +0000

The tech market in China has been growing and growing but so far it's been pretty well hidden to Westerners that don't travel across to China to find out for themselves how modern and sophisticated China has become.
We live largely in a world dominated by US brands such as Google, Microsoft, Facebook, Linked-In, Amazon, ebay and Twitter - and just assume that some day the entire world will be using these platforms. Why? Because for years, the USA has dominated global markets. Its movie making, music and software industries have bled successfully across the Western world - and it would be of no surprise today that the music and films you see in Spain, Cape Town or Germany are broadly the same as you'd find in New York and Boston.

The article attached describes the eye-openig experiences of an ex-Google employee that found out first hand what it's like to live and work in China with one of their rising tech-star companies. His presentation on the rise of China's tech scene is a 'must-see' for anyone that plans to be in the software industry for the next couple of decades. It evidences that China is by no means behind when it comes to innovation and consumer tech.

In the 19th and 20th century, Britain gained its Great title through science and innovation - and trade. It's ability to trade and harvest the rewards of so many different continents supported its huge empire of the day. English language benefitted hugely from this period of expansion. Today it is the unrivalled language of business across the globe because it is the greatest leveller. For businesses that want to trade globally they need people to speak English. But what has this got to do with the China tech scene you ask?

My thought is that one day the 'things that China does well' in technology - including their consumer and business software brands - are going to grow BEYOND China and become household names around the planet. The article attached shows just how close that horizon truly is. When they do this, the apps won't be in Kanji or Hanzi - they will be written in English. I suspect they will be written in 'proper English' rather than the American version that has been served up by the US software industry for the last 30-years - because the rest of the world does its business in English, yep, good 'ol English as written by the folks in blighty.

Will this see a resurgence of paragraphs untainted by z's in every other word, and a slow-down in the sad demise of 'u's in such beautiful words as colour? I hope so. It would be nice to write a page in English and not have to re-edit it again for the American market.

Ian.

http://www.businessinsider.com/what-the-chinese-tech-industry-is-like-2014-1?nr_email_referer=1&utm_source=Triggermail&utm_medium=email&utm_term=Business%20Insider%20Select&utm_campaign=BI%20Select%20Weekend%202014-01-12&utm_content=emailshare

To anyone and everyone that has taken the time to read my blog articles over the past few years - Thank You!

noreply@blogger.com (Anonymous) — Mon, 06 Jan 2014 20:17:00 +0000

As we begin a new year I should like to take a moment to thank the 11,446 people that have taken time-out of their busy schedules to muse over my articles in recent years. Never did I imagine that anything I produced would get seen by 11,000 people. Wow! You never did show up in my teens when I was playing my electric guitar. (But there you go.)

Thank you even more to those who have reached out to me to give encouragement or let me know how they've applied some of the learning lessons I've documented about organizational design, business and IT that I have myself found useful.

I hope you all have a special 2014.

I.

The beginning of a New Year: A good time to BONSAI your organization design

noreply@blogger.com (Anonymous) — Mon, 06 Jan 2014 15:14:00 +0000

Do most business leadership teams think deeply about the design of their enterprise? Generally no. The design and internal behaviors of organizations develop organically over time as an enterprise grows. If you believe that organizational design is a bi-product of good management and effective leadership, you could argue that OD is an unnecessary profession. Certainly, some organizations work exceptionally well WITHOUT teams of consultants, HR and Change Management practitioners running all over them with measuring sticks and psycho-analysis tool-bags.

I often find myself debating whether it's better to have an enterprise that flies by a 'seat of the pants' management method or alternatively adopts 'systematic management' methods. The great joy and challenge of understanding how organizations work is their a unique blend of science and creativity, of systems and people, of tools and culture.

Getting the best out of an enterprise usually comes down to a blend of everything.

But how do you get the blend right? Even when organizations are led by great leaders, and have great people in them doing the right things, it doesn't hurt for everyone to know 'what the plan is' and 'how they contribute to it'. And there's the rub. When organizations aren't thoughtfully designed, they grow in an unkept way. They grow 'slack' in their processes, theifdoms build, budgets grow, resource pools become ever larger and unkept. Department managers grow their teams based on departmental needs. But what of the big picture? What if markets and customer needs are changing? Focusing on department needs and priorities, resources and plans could simply be encouraging wasteful practices to be repeated.

Most people will be familiar with Bonsai; the Japanese art form using miniature trees grown in containers. The main reason for the pastime lies the opportunity to contemplate the world by performing a slightly trivial task. The result of the activity is a more aesthetically pleasing tree design. But the ACT itself, of nurturing an attractive tree design through a constant vigilance on the part of the practitioner, has huge parallels to the role of an Organizational Designer.

Businesses require a ROLE that is constantly monitoring the health and growth of the enterprise - an Organizational Design practitioner. Think of it as the person that monitors the BONSAI and makes sure it grows in a healthy way. Without this role to shape the growth of an enterprise into a thoughtful design, it soon becomes unkempt.

Organizations work better when resources are aligned in the best possible way to the things that need to be done to achieve stakeholder outcomes. Designed well and the people working in the enterprise will produce more with the least resources - i.e. You get more growth for your feeding and watering. (Ask business leaders to state what proportion of the activity that happens in their enterprise contributes directly to strategic goals and you'll be surprised by the answer. If they say any more than 65% they'd be very lucky. And that's a lot of someone's energy being wasted on things that don't really sum up to very much value at all.)

Organizations CAN be designed to work in an optimal way. Partly it's about agreeing on a smaller number of agenda items that REALLY will make a difference to the success of the enterprise: Most organizations (and management teams) try to do too many things. But it's more about ALIGNMENT: aligning strategy to stakeholder needs, aligning customer value with stakeholder value, aligning processes to outcomes, aligning roles to processes...

As an Organizational Designer, trying to make sense of all the data needed to comprehend how an organization is designed and how to adapt it can be mind-bending. Many-a-time I have blown up my spreadsheet owing to the volume of data that needs to be brought together and understood!

Like most professions, Organizational Designers require tools to harvest data, build it into logical structures, maintain it and make sense of it. The key areas are:

INSIGHTS: Data that describes and evidences the drivers that underpin the decisions made on strategy.
PERFORMANCE AND STRATEGY: Data that describes the strategy of the enterprise, how it plans to achieve the stated outcomes and what progress is being made.
POLICIES AND PROCESSES: Data that describes how the enterprise operates to produce its outcomes.
ROLES AND ACCOUNTABILITY: Data that describes how duties are divvied out to people and resources.

The good news is that unlike the BONSAI owner, you don't need to go buy your tree! This means you only need to think about where to start trimming and nurturing your design.... NO!

The first job is to make sense of the existing design (what's the point in Change Management if you don't know what you're trying to change into?). Few organizations have a clear picture of what their strategy is, who does what and why, what processes and policies exist and how they dovetail together. That's where an Organizational Design Tool-Kit comes in. As the name suggests it's a tool-kit for Organizational Designers: a relational database-powered system that helps OD practitioners to make sense of the big data that defines how an enterprise works.

Using an OD Tool-Kit, it's easy to bring the large quantities of data together and articulate the design of the enterprise. Then you will see the BIG PICTURE of your BONSAI. Only then should you consider your first trim ;-)

Digital Marketing - Which Analytical Insights Really Matter?

noreply@blogger.com (Anonymous) — Thu, 12 Dec 2013 09:23:00 +0000

Digital Marketing Analytics is an important area for most companies at present as online channels become ever more influential in the marketing mix. Sometimes I get the impression that marketers are unnerved by the digital arena because it's challenging to build a robust performance management model. In this series of articles sponsored by Adobe, marketers get to understand the key threads of knowledge they could, should or must invest in. It goes some way to demystify the digital marketing arena. Take a look...

Metrics That Matter

Using behavioral science to improve the customer experience | McKinsey & Company

noreply@blogger.com (Anonymous) — Tue, 01 Oct 2013 12:04:00 +0000

This is an interesting article by McKinsey that highlights how business is now coming to terms with the need to register how customer structures and behaviors impact directly on operational excellence and performance.

Using behavioral science to improve the customer experience | McKinsey & Company: "e"

What Is Customer Science?

noreply@blogger.com (Anonymous) — Tue, 01 Oct 2013 10:45:00 +0000

This week I've been putting together a presentation to introduce Customer Science and why I think it's now come of age thanks to Cloud CRM data-marts.

At one time, marketers like me really struggled to build a rich understanding of the customers in their target markets. The first major challenge was to get customer data into a usable form. With so many business systems designed to support a specific process or discipline, it's not uncommon for data to be held in many different back-office systems. The Web made this situation even worse. Even when marketers could get their customer database onto a spreadsheet (and you were lucky if it didn't blow up when attempting this due to the files sizes), data quality and inconsistency issues meant that marketers faced hours if not days of data crunching to get their data consistent.

In today's digital world a great deal has changed. For one thing, the state of markets changes so quickly. It would be a nonsence to try to attempt this type of 'single view' when customers ebb and flow on eCommerce websites on an hourly basis. Another issue with digital customers is they don't interact using phones and face-to-face visits. They don't want suppliers to call them out of the blue to ask them a hundred questions about their product interests, buying preferences, future plans or buying behavior. We live in an era of event-driven, remote - practically always - online thoughtful consumers and buyers. They're always on the look-out for a good deal, positive product or service recommendations, happy to snack online in pursuit of their purchasing interests - it's a very different world to the one Micheal Porter described in his marketing 'how to' articles.

In this presentation I've put down my thoughts on Customer Science and how it's rapidly maturing as a discipline. I find the subject fascinating because, like many marketers, I share a huge interest in the fit between customer value and shareholder value. I also have a belief that most customers are willing to buy your product or service if it addresses an unmet need - IF ONLY you can communicate to them in a fine-grained, relevant way.

I hope you enjoy this article. Do let me have your feedback!

Ian.

What Is Customer Science - And Why Should You Care?

A Single View of Customer Data - Thanks Cloud ;-)

noreply@blogger.com (Anonymous) — Thu, 26 Sep 2013 20:22:00 +0000

Sourcing a single view of customer data can be painful for marketers

In this article I take my first walk around using a BIG DATA private-cloud data-mart for marketing and comment on what it’s actually like as a marketer to be armed with a ‘single-version-of-the-truth’ when it comes to customer insights.

I’ve spent my career as a business-to-business marketer being (one of) the last to leave the office because THE NEXT marketing activity required data in a certain sort, form and quality that required me – and often my willing team – to stay behind and fix all of the wrinkles that fall out of exporting data from operational systems like Customer Relationship Management (CRM), Contact Management (CM) or Intranet repositories.

The marketing industry has spent a life-time grappling with poor quality data from operational systems and using it for a different purpose to what it was intended. The vision of CRM and other systems was to create a ‘single-view-of-the-customer’. Great. Or at least it would be great if systems didn’t change, acquisitions didin’t happen and marketers only wanted to use data that exists within the organization. But this is the real-world, and in the real-world all of these factors impact on marketers to stretch their day.

Thankfully, the advent of cloud computing – and applications platform technologies like ENCANVAS – happily means that nowadays marketers don’t need to rely on operational systems to form their customer data-mart into a single view of the customer. Private-cloud data-marts are a new form of technology solution to the age-old problem of how to create a nice, neat bundle of customer data that marketers can get their knife and fork into without first having to herd cats.

Sometimes falling under the all conquering umbrella of BIG DATA, CRM private cloud data-marts are a secondary layer of glue-ware: Instead of creating a ‘new system’ and yet more data entry screens, CRM data marts harvest data from existing operational systems and website to build a holistic view of the customer and market landscapes. Data is securely uploaded to the cloud using Business Process Management and Workflow tooling (in the case of Encanvas it’s called INFORMATION FLOW DESIGNER), and as it’s harvested, clever algorithms are applied to the data to correct all of those horrid things that marketers usually have to spend their time manually correcting in unwilling spreadsheets – missing postal codes, incorrect salutations, duplicate records, invalid email addresses and telephone numbers. These algorithms cut a huge chunk of workload off of the marketers’ average day-job and can even cope when salespeople do ther inexplicable data entry faux pas like ‘dead@dontsendemail.com’.

Services like USTech Solutions’ Big Data Skunkworks mean that marketers are able to get up and running with their truly holistic view of customers remarkably quickly and start to show their metal by doing the great things that marketers joined the profession to do rather than the tedious data crunching stuff that drives them to distraction.

SO YOU WANTED A SINGLE VIEW OF YOUR CUSTOMERS – WELL NOW YOU”VE GOT ONE! SO WHAT CAN YOU DO WITH IT?

I’ve only been experiencing the impact of CRM data-marts through ENCANVAS deployments over the last few months and so (even though I’ve been waiting for 20-years to see the day!!). I’m only now getting my hands on the sort of data and tools that I dreamt of as a spotty marketing assistant back in the day. The results I’ve experienced have so far been outstanding (I may well up!). Using the interactive charting and mapping tools that are available now to marketers in CRM data-mart platforms it’s now possible to dive into views of data presented in charts or maps and see the related records below to see the detail. It’s also possible to click on the data that DOESN”T have an email, that DOESN’T have a scheduled reminder or scheduled follow-up – so action can be taken to act on what’s missing by resolving the poor working practice. One can even filter the source of poor quality data to an original system, sales team or sales person! There’s nowhere to hide for poor quality or incomplete data.

Having the ability to identify patterns and buyer behavior segments is proving extremely useful. Having defined rules in the system of what constitutes a BAND A customer. or a BAND B customer, the platform will again manage these rules so that, any time a customer inherits these characteristics, they pop into the appropriate group. Customer data can then be analyzed, sorted, formed into campaign lists (or whatever) by adding this additional ‘filter’. From a practical perspective this means that marketers can be far more granular with their campaign straegies; they can select customers with or without certain data attributes, by band, by location, by date last contact, by income, by spend, by shopping behavior – gosh it’s fun!!!

Another factor that feels like it’s taking a load-off happens when I see poor quality data and I want to tackle it. Instead of having to export ALL of the records that have no email address or no Cell/SMS number, I can now concentrate efforts on tackling the BAND A customers that have no email and make sure the most likely sources of business impact are handled first. Very handy.

One thing I wasn’t expecting is that the data in the cloud data-mart is consistently good even when the data held in sourcing systems remains poor. This is because the extraction tools that automate the population of the CRM data-mart cloud will install sorting, de-duping, cleansing and enriching treatments not just once but everytime a data upload takes place. This means that if you’ve instructed the platform to look through your emails and kill any non-conforming data, it does so every time the source data is uploaded – so the result is the cloud always stays PURE.

Does this mean the world of the marketer has changed forever? Not on a base level; the same old instincts, methods and skills apply. What is different is the IMPACT pragmatic marketing can make on business POWERED by private-cloud CRM data-marts. It’s and accelerator to marketing innovation. Of course it also saves me LOADS of time by not having to be knee deep in dodgy data which now allows me to go home at the same time as my sales colleagues that were probably the folk who put the poor quality data in the CRM database in the first place!! Thanks guys – I forgive you (now).

Another big player in 'big data'

noreply@blogger.com (Anonymous) — Wed, 14 Aug 2013 19:28:00 +0000

This article announces Goldmans' US$100m investment into big data analytics firm APT. APT's description of its service is a dead-ringer for Data Investment Management and puts APT, WPP's Fabric (Fabricxx) and Encanvas on different parts of the same page.

Without question, harvesting data, analyzing it and acting on the things that matter is the hottest ticket in IT at the moment. Whereas APT and Fabric are in the 'big corporate' market playing with big data, Encanvas serves the mid-market and harvests data from anywhere to build customer analytics.

Other notables in this space are Locationary, recently purchased by Apple, Teradata's Aster Data analytic platform, Dataspark in Australia and the people that started it all DunnHumby.

Disappointingly, a focus on the Big Data buzz is somewhat distracting as people seem to be confusing the world of Google, Facebook and Amazon dealing with HUGE DATA (let alone 'big') with the need by organizations to adopt Data Investment Management solutions that can discover data, analyze and act on it.

I.

What Are Actionable Insights?

noreply@blogger.com (Ian Tomlin) — Fri, 26 Jul 2013 14:21:00 +0000

I was delighted when so many sites picked up this simple presentation I've put together to describe what Actionable Insights are.

I think there is a great deal of confusion at the moment around the entire technology space because people are hearing whispers of BIG DATA, CLOUD, PREDICTIVE AND SOCIAL BUSINESS INTELLIGENCE and the like... and what they really want to know is what any or all of these technologies have to do with their business.

For Business Intelligence Software vendors, it's not always easy to answer the 'So What?' questions when it comes to applying their technology; particularly when the people making the introductions are enthusiasts of technology - and they generally are. If you are passionate about technology like me, you just want to shout out to everyone in the world "Hey, give this a try!" but every business, and business user has a different perspective on 'what insights matter most to them'. Failing to appreciate and land on the specific insights useful to buyers and instead making a general technology silver-bullet pitch is an all too familiar Lion Pit that Business Intelligence vendors fall into.

This presentation covers descriptions of types of Business Intelligence software and the key outcome areas that are driving demand for Actionable Insights. I've covered a lot of the background and technology issues in this presentation that I think are most helpful in understanding the general topic area. What I haven't done is to even start to describe the road-blocks and organizational design issues that are probably going to make the biggest difference to the value of Actionable Insights to early adopters of the technologies designed to source them.

These are about:

Changing attitudes and behaviors.
Appreciating that IT systems have focused for years inwardly on processes that exist WITHIN AND ACROSS the enterprise but rarely beyond it. That means to really get to grips with harvesting and assimilating actionable insights new technologies need to be introduced along with new thinking on security governance, data governance, scaling and analysis tooling.
Accepting that some Actionable Insights that are most valuable to an enterprise aren't being captured today at all (such as 'soft-measures').
Some Actionable Insights don't have any specific role in the enterprise responsible and accountable for making use of them.

Operational Analytics: Best Software For Sourcing Actionable Insigh...

noreply@blogger.com (Ian Tomlin) — Mon, 22 Jul 2013 14:24:00 +0000

Operational Analytics: Best Software For Sourcing Actionable Insights:

In this article I summarize the buying options for businesses looking to source actionable insights - data views and reports that give managers cause to take action to improve the way they work and achieve double-loop learning results.

I hope you find it helpful!

Ian.

Talent Leaders Can Learn From Customer Science - To Foster 'Loyalty Beyond Reason'

noreply@blogger.com (Ian Tomlin) — Fri, 19 Jul 2013 07:18:00 +0000

'Loyalty' by Sherry Ezhuthachan

Stepping across from the world of marketing and brands into talent management has helped me to appreciate there are more common areas than I'd previously realized. To be high achievers in the talent industry, HR and talent leaders will need to learn the lessons of brand managers.

...

"Loyalty Beyond Reason? - That's a funny name for a blog.."

I often get funny looks when I tell people about my new blog title.

I came across Loyalty Beyond Reason when reading one of my favourite books for the second or possible third time and I was reminded how central it is to running business in the noughties. The book,written by Kevin Roberts, then CEO Worldwide of Saatchi and Saatchi, is called Lovemarks: The Future Beyond Brands. It's a slightly annoying book because it's better than the three books on business I've written myself. Anyway, reading the book you realize Kevin is one of those guys that 'understands' how customers and markets work at an 'organic' rather than 'theoretical' level, a bit like Richard Branson.

The key argument introduced in the book is that industry and commerce has moved from a focus on products, to (but products have become very similar, companies need to protect their IP some how and therefore we have..) trademarks, to (but customers don't connect to trademarks so we have..) brands to (but now we even have too many brands to think about so we need to give customers reasons to grow 'loyalty beyond reason' so we're heading towards..) 'Lovemarks'.

It isn't difficult for me to buy into the idea that companies don't own their brands anymore and - if they want their brands to be successful - they need their customers to take them on, buy into them, promote them. Just look at brands like Apple and the passion users have for their products. This isn't just a cold, calculating buying decision at work here. Nope. These boys and girls LOVE their brand. No matter how many advertising dollars go into Microsoft I don't see the same thing happening with that brand. Now I know some of the guys at Microsoft in the product marketing teams and I have to say they're an exceptional bunch of folk. They know their stuff when it comes to Outcome Driven Innovation and all the latest thinking and approaches on Product Management and how to deliver world class products. Recent launches show there's nothing wrong with their products. Yet they don't engender the same passion and loyalty in their customers as Apple has managed to do. They are failing to create Loyalty Without Reason.

Spending my time in the talent industry over the past few months I've learned that the need for Loyalty Beyond Reason is missing in many employer:employee relationships, let alone contractor:contracted relationships. The relationship between a customer and and a supplier very often only becomes contractual when the customer chooses their brand. Before that they can go anywhere. Perhaps employers think that because they have an employment contract in place they can within reason 'do what they like' when it comes to their relationship with staff and contractors - but this is a pipe dream. Even when there are contracts and agreements, these don't create great productivity and game-changing ideas. Like any contract, it's only really there for when the relationship breaks down. No, if talent leaders want high performing workforce and world class talent, they're going to have to forget about contracts and compliance, using performance appraisals as a way of formalizing how the carrot and stick are applied, they're going to have to find better ways of creating loyalty beyond reason.

The brand industry knows that you can't tell customers to buy your products, you can't even ask them nicely. You have to get customers to want to buy. And the buying decision isn't all about facts, analysis and reason, the last 9-yards is pure emotion; how it makes you feel to own a product or use a service. I fly Virgin Atlantic because they play T-Rex when you walk down that long isle on the plane past the nouveau riche to economy. Makes me feel good.

Talent leaders need to invest in their people 'in a certain way' - not the Microsoft way, the Apple way. As with the Customer Science industry, the starting point is to invest time in understanding 'the individual' and applying actionable insights to draw out the things people care about emotionally, on the edge of reason. Any business can do this - big or small, accountants or engineers. You just have to start in the right place.

I.

Actionable Analytics Trends: 'Will Be Driven by Mobile, Social and Big Data' Says Gartner

noreply@blogger.com (Ian Tomlin) — Wed, 17 Jul 2013 14:21:00 +0000

Gartner Says Actionable Analytics Will Be Driven by Mobile, Social and Big Data Forces in 2013 and Beyond:

The Gartner article is interesting because it starts to evidence what most practitioners in the business intelligence field have I suspect known for some time - that instead of examining 'dead' data that has been purposely shaped, organized and crunched for the purpose of analyzing performance, we are heading into an era where the really useful 'So What?' type of analytical metrics will come from the live workspace environment. Users of mobile phones, tablets, and PCs will contribute data unknowingly through their clicks and taps into the big data cloud while others will find their movements, preferences and locations picked up through sensors - on doors, on billboards, on product labels, on shopping trollies and vehicles.

Whilst this all sounds terribly 'big brother' to some generations, the techno savvy youth of today a leading a charge towards the 'thoughtful web' (as I describe it in my book 'Social Operating Systems') will think nothing of a few more sensors and clicks being monitored. Most will have no choice if they want to afford to pay for motor insurance or use social networking sites like Facebook. You either agree to the supplier terms or are cast off.

Analytics is moving into the clouds to make this possible. Platforms like Streaminsights from Microsoft and BusinessIntel from Encanvas enable data to be captured as it travels, or where it resides without needing to build data marts or purchase BI platforms.

It's going to be interesting to see how businesses adapt their thinking to take advantage of these new innovations and new ways of working.

I.

Benefits of Profiling Customers For Motor Dealers - And How To Do It

noreply@blogger.com (Ian Tomlin) — Tue, 16 Jul 2013 14:52:00 +0000

Customer Science - ...building deeper, richer, more personalized customer experiences by applying customer insights to better understand what customers care about, how they think and act, how they make buying decisions, how they want suppliers to communicate with them, how they want to be treated, what they expect from their suppliers... and more. But does it work (is it working?) in Motor Retail? Is it being used successfully to turn 'sleepy customer data' into a dynamo for new reasons to speak to customers, turning clicks and visits into cash?

...

Since the 1980's I've watched with interest as the methods adopted by marketers to engage customers and prospects have adapted as new technologies and created approaches have come of age. More than in any era before, the noughties has required marketers to take on a cacophony of new techniques to engage customers that want the perfect mix of a personalized customer service experience and relevant, timely offers while not wanting to be barraged by suppliers with direct marketing and unwanted contact. The growing impact of the Internet, mobile communications, social networking and a more techno savvy customer communities is changing the rules for marketers on how to get the biggest impact from their marketing spend.

By now, the marketing industry has worked out that it's vital to gather information on customers 'as part of the day job' to build up a profile and persona on each and every customer so the customer enjoys a personalized 'shopping' experience. Companies like Tesco and Amazon have shown the way in exploiting customer data to sensitively give shoppers what they want rather than forcing them with a strong hand down paths they don't necessarily want to follow.

The type of relationship customers want - location-centric, timely, fine-grained, event-driven offers personalized to their particular wants and preferences - can only be achieved in my opinion by taking every opportunity to learn about customers through each and every interaction. Customers don't want to be contacted out of the blue, or left standing in service receptions JUST SO THAT DEALER CAN CAPTURE DATA TO SELL TO THEM. For Motor Dealerships that means not only investing time into collecting data 'as part of the day job' but also investing in the PROCESS of 'digital persona-lization'.

In an odd way, customers generally WANT suppliers to build and know their digital persona because they want that type of personalized experience (with the suppliers they want to buy from). What they definitely DON'T WANT however are relationships with suppliers that abuse their trust or over-bite on the level of relationship they want.

Marketers in most industries profile their customers these days, but 'Customer Sciences' are only now appearing in the Motor Retail sector. This is partly no doubt down to the fact that in certain countries and regions, dealerships with the right franchise have very little local competition for the brand they promote. While it's always silly to generalize, the feedback I get is that this is changing and levels of competition are growing in most geographies.

Understandably, dealer principles want to know:

How does profiling help me to sell more?
How do I build up profiles and personas from my data?
How do I enrich my data when it's poor?
How do I channel dialogue opportunities to encourage sales people to engage customers at the right time and for the right reasons?
Where do I start?

So here I attempt to answer these questions:

How does profiling help me to sell more?
When dealers have a better idea of the sorts of customers they sell to they become more adept at appreciating the types of offers that work. Knowing the affluence of customers on your database for example means that you can find out (from third party agencies like www.improvemydata.com) the addressable market in your locality by mapping these target customers against your existing database. Marketers and dealer execs can use the profiles they hold about their customers to understand how to maximize their revenue potential per customer - to then work out which customers are not achieving their anticipated life-time value. Sometimes enriching data can seem like a 'painting the Fourth Bridge' experience where you need to start again every time you think you've finished. Focusing on the most important customers first and devising marketing strategies to grow value in the customer segments that matter most allow marketers to drive optimal value from the smallest efforts.

How do I build up profiles and personas from my data?
There are many ways you can profile customers - the most obvious being:
(A) Life-time value - It's quite easy to derive a value for each customer based on assumptions of what they should spend over their lifetime. Many motor manufacturers hold and share these insights for each model they sell. Comparing your revenue per model against the forecasted return helps to qualify 'where things are going wrong or could be improved. Seeing this data, dealerships can realize that some makes and models are more reliably generating the life-time revenues they should than others; perhaps because some makes and brands face more local aftersales competition than others.
(B Buyer behaviour - At NDMC we define the buyer behaviour of private vehicle buyers through fourn buying personas:

Cherished Teddies > Loyal buyers that consistently reach within 20% of their future planned life-time value. Typically these customers will purchase service or loyalty plans (often with additional insurances or paint protection options) to make sure their dealership can look after their needs. For this group dealers should have a very complete picture of the customer profile. Cherished Teddies need looking after because they are the group most likely to recommend others buy their vehicles from your dealership!
Loyal Dogs > Vehicle buyers that purchase after-sales products but don't achieve the future planned life-time value. Understanding why this group doesn't achieve their future life-time spend is helpful because it can point to weaknesses in your offerings or aspects of local competition that you're not aware of. At the same time, it pays to contrast buyer behaviour with affluence ratings given that it may well be that Loyal Dogs WANT to be Cherished Teddies - they just can't afford to be ;-)
Cats > Buyers that have purchased a vehicle from you but only come back for aftersales services when it suits them. Just like cats you can't rely on their loyalty and you have to work harder to get their attention. Cats are harder to love because they're not around as much. The obvious thought is 'What does it take to turn a Cat into a Loyal Dog?'
Neighbours' Cats > Buyers that haven't bought from your dealership but have bought services or parts. Perhaps these customers are 'sampling your dealership' to understand how well they get treated. If you pay them more attention, perhaps they will become your Cat in time.

(C) Affluence - How much money people earn is a good indication of how much disposable income they have to spend on a vehicle and indeed the sort of vehicle they might want to purchase. Consumer data can tell you a great deal about who your current customers are and the target people in your area most likely to be willing and able to purchase a vehicle from you.
(D) Contact activity and preferences - It helps to understand these days 'HOW' customers want to communicate. There is a significant shift to social media and mobile methods. Assumptions that 'mobile and Internet' tools are for the young are usually baseless. Many 'people that want to be young' are avid smartphone and Facebook users (My mum twitters all the time!).
(E) Location - Location awareness is a powerful market tool. These days it's quite possible to focus events and campaigns to target specific geographies that have a proven bias towards your brand based on affluence or locality. Consumers can also be targeted 'on the hoof' if you have the means to engage them when mobile.
(F) Arbitrary Banding - Even when all of the above fail, marketers can start their entry into Customer Sciences by thinking about their own arbitrary bands based on a selection of customer metrics and see what falls out. Dealer execs have a very good feel normally about their customers and what works and doesn't work. Exploring these perceptions and seeing if the 'data' backs up the assumptions can be a good place to start for organizations that have never experimented with Customer Sciences before.

One other thought - unsurprisingly, when you compare these different aspects of profiling together it helps to build up a visual image of the 'persona' of the buyer and this can help to further develop the rapport with the customer through a 'deep support' understanding of their wants and needs.

Building up profiles is a question of understanding key data metrics and then validating where the data needs to be sourced from. Sometimes data is already held in admin systems (like Dealer Management, Showroom or Service Management systems), while other times it will need to be captured by installing new systems or methods. Not all methods require manual data entry. These days, customers are often prepared to enter their own data provided there are rewards for doing so (such as gaining free access to an online portal that provides details on their vehicle valuation and the impact of their driving behaviour).

The life-cycle for Customer Science (i.e. creating and leveraging profiles) goes something like:
(1) Harvest - Gather and cleanse data from its various latent sources
(2) Make Connections - Build new connections between data items to produce new metrics
(3) Personalize - Apply the learning lessons to personalize the dialogue with customers and create new reasons to interaction with more relevant and timely offers
(4) Learn - Measure the effectiveness of personalized interactions and learn from them to source new ways of bringing value

Like most processes in business, the first job is to recognize that the process needs to exist and, having formalized it, it becomes something that can be measured and improved to become progressively more effective.

How do I enrich my data when it's poor?
In the motor dealership arena, the most frequent response I encounter is 'Sounds great but my customer data quality is so poor it wouldn't work for us." Wrong, wrong, wrong. It's not that difficult to improve the quality of data these days. The weapons marketers can use to enrich data include:
(1) Paying external agencies to manually enrich data (very expensive)
(2) Progressively improving the quality of data over time by becoming more robust in making sure members of staff complete records more consistently; some of which can be enforced with changes to software
(3) Exploiting 'big data' to cleanse your data by straining it through a source of 'good data' such as an industry database, consumer insights database or postcode database.

How do I channel dialogue opportunities to encourage sales people to engage customers at the right time and for the right reasons?
Systems like NDMC's LeadGenerator360 enable dealers to upload/mine their existing data from administrative systems and build up a pipeline of reasons to speak to customers when they want you to (I'm sure there are other systems that work in a similar way out there ;-). Such systems generate a pipeline of reasons to engage customers 'one customer at a time' based on key events like vehicle birthdays, service plan expiries, warranty expiries, MOT reminders etc. that ensure every single worthwhile opportunity to engage customers is not overlooked. At the same time, leads are allocated and load-balanced in a way that avoids sales people from becoming overburdened. Linking lead pipeline to customer profiling builds a virtuous circle of 'using insights to capture insights' that reduce the need for contact 'expressly to capture data we should already know about our customers' or spurious sales calls that customers hate because they feel they're being sold to.

Where do I start?

The best way to start the journey towards Customer Science based marketing methods like profile and persona building is to perform an audit of the 'net present state' of your customer insights and the extent to which your dealership is exploiting its dealer insights.

NDMC (www.ndmc.uk.com) ... and again, I'm sure there are other supplier companies out there... offer a 'CRM Diagnostic' service and system. This is a one-time reporting cycle where key data is extracted from existing DMS and administrative systems to a secure space, where it is cleansed, normalized, analyzed, and then - from the connections made in the Customer Science Engine - out pops a series of online (still secure) 'drill-downable' reports and views. This type of diagnostic service will qualify how complete and consistent the customer data is, and the number of 'meaningful reasons to engage customers' against what the dealership should be capable of based on the size and characteristics of their customer database.

- ends -

The eight word phrase that every salesperson should know

noreply@blogger.com (Ian Tomlin) — Tue, 16 Jul 2013 11:58:00 +0000

The eight words that every salesperson should know!! The article attached is a fascinating look into how it's possible to invoke positive reactions from people simply by choosing the right words. It's well worth a read for any sales person!

Why behavior change apps fail to change behavior