Posts Tagged ‘integrated planning’

Integrated Planning & Control – New Perspectives from Oliver Wight

Published October 11th, 2012 by Trevor Miles @milesahead 0 Comments

Oliver Wight has long been at the forefront of Sales and Operations training and consulting – even to the point that many companies will tell you very proudly that they have attained Ollie Wight Class A certification for a variety of processes. Oliver Wight has also spawned several off-shoots, including Ling-Coldrick, who has done some really great work in getting S&OP started in many organizations. Oliver Wight promotes the concepts of their ‘Proven Path Methodology’ on a ‘Journey to Business Excellence’, which I have captured below. This is a business process maturity chart, ultimately ending up in integrated business processes.

Integrated Planning & Control – New Perspectives from Oliver Wight

Maybe it is just me being impatient, but whenever I look at this diagram, I cannot help wondering who is going to embark on a 10 year process. In the current market conditions who can afford to wait that long? Anyway, Ollie Wight has been doing process consulting and change management for a lot longer than me, so perhaps they are correct.  But it must be nice for Oliver Wight to get someone to commit to a 5-10 year project. Wow.

Having been around supply chain management since the early 1990’s, I wonder how many companies have progressed to Phase 3, and are nibbling at Phase 4.  Perhaps the answer lies with a different maturity model promoted by Roddy Martin, formerly of AMR Research, which is now part of Gartner’s Supply Chain Management practice.  Notice how there is a different value trajectory for the companies that are beyond Stage 3, when the focus is more on business value than operating efficiency.

 

 

Comparing these two maturity models I would say that Stage 2 of Roddy’s model equates to Phase 3 of Oliver Wight’s model, which is the focus on functional excellence supported by the automation of functional processes. Roddy contends that most companies are at 2.5 on the maturity curve, and some have reached 3.0, with Proctor & Gamble ahead of the pack at 4.7. In other words many companies have reached Phase 3 of the Oliver Wight model and a few have progressed into Phase 4.

It is in this context that I was fascinated by a recent daily email feed I get from George Palmatier of Oliver Wight in which he describes principles he wishes he had understood earlier in his life. (You can sign up for the daily feed here.)

It is the ‘Integrated Planning and Control’ aspect that I find really different and interesting. This equates to Roddy’s notions of ‘Demand Driven’ (Stage 4) and ‘Value Translation’ (Stage 5). Fundamentally it is the recognition that while planning is necessary, planning alone is insufficient. One point on which I disagree with George is that he refers to ‘changes in the market’ without acknowledging that most of these are not changes but rather evidence that we did not have 100% knowledge of the market in the first place, and we never will. The significance is that by using the term ‘changes in the market’ there is an implicit assumption that a perfect plan that captures market conditions exactly can be created. We all know that any plan we create is aspirational, especially the long term plans, which is why, to me, ‘control’ sounds too much like measuring a supply chain’s performance based upon Plan Conformance. If the plan was never 100% right in the first place, why are we forcing the supply chain to follow it? Instead of ‘control’ I would use Gartner’s term ‘Profitable Response’ (see the diagram below), which is the core message of the middle paragraph in George’s principle. The diagram is from a recent Gartner article titled ‘Elevate Your S&OP Process From Traditional to Demand-Driven’ (subscription required) published by Todd Applebaum and Jan Kohler in which they recommend that companies

Create a vision for S&OP that moves beyond operational planning to drive business value by driving profitable demand responses based on trade-offs and conscious choice.

Sounds to me like they are making the same point that George is making: Planning and XYZ. The important bit to me is the association of profitable response with demand sensing and demand shaping. What I like about the term demand sensing is the implicit recognition that we did not have a complete understanding of demand in the first place, whether in the long term, medium term, or short term. Obviously some of the need for demand sensing can be put down to ‘changes in the market’, not just lack of knowledge.

But what goes into being able to sense and shape demand, and then provide a profitable supply response? The strength of a large organization like Gartner is that there is often some really interesting work going on in multiple related areas. In June 2011 Roy Schulte, Janelle Hill, Nigel Rayner of Gartner published a report titled ‘The Trend Toward Intelligent Business Operations’ (subscription required) in which they address the Sense-Shape-Respond need from techy perspective, but the messages are consistent with what both Todd and Jan write (Gartner), and what George writes (Oliver Wight), and in which I believe. The key findings of the Gartner report on Intelligent Business Operations are

  • The adoption of integrated analytics is increasing as business managers and knowledge workers are asked to make faster and better decisions, and thus need improved visibility into their operations and environments.
  • “Real-time” operational intelligence serves different needs and uses different design patterns than tactical and strategic business intelligence (BI) and performance management (PM).
  • There are two fundamental styles of real-time operational intelligence: analytic services that run on request and active analytics that continuously monitor conditions in a company and its environment.
  • Organizations that pursue the business process management (BPM) approach to implementing systems are among the most enthusiastic and successful adopters of intelligent business operations, because business people and analysts can readily see where analytics and decision management should be used, and the project team has a commitment to explicit business process modeling and continuous process improvement.

My conclusion is that Gartner is seeing the need to plan, monitor, and respond in multiple business areas, not just supply chain management.  The necessary technical capabilities they describe are captured in the following diagram.

For the less technically minded, the acronyms used in the diagram are as follows:

  • BAM – Business Activity Monitoring refers to the aggregation, analysis, and presentation of real-time information about activities inside organizations and involving customers and partners.
  • CEP – Complex Event Processing is event processing that combines data from multiple sources to infer events or patterns that suggest more complicated circumstances. The goal of complex event processing is to identify meaningful events (such as opportunities or threats) and respond to them as quickly as possible.
  • CBO – Constraint-Based Optimization, in the context of supply chain management, is essentially what we have called planning, and is focused on functional excellence.
  • BPMT – Business Process Management promotes business effectiveness and efficiency while striving for innovation, flexibility, and integration with technology.
  • Sim. – Simulation is the imitation of the operation of a real-world process or system over time. The act of simulating something first requires that a model be developed; this model represents the key characteristics or behaviors of the selected physical or abstract system or process. The model represents the system itself, whereas the simulation represents the operation of the system over time.

But we can see all the elements of the integrated planning and control discussed by Oliver Wight and Gartner’s Sense-Shape-Respond. Both capture the essential point that while planning is necessary, it is not sufficient on its own.

Likewise processes and systems, such as event management, that can only alert you when a particular metric is out of whack without being able to tell you the downstream or upstream impact are insufficient. Similarly predictive analytics processes and systems that are based upon statistical analysis without any notion of the underlying model are insufficient.  This is the point brought out in the definition of ‘simulation’. And what better model of the supply chain do you have than the model you used to generate the plan in the first place?

Most supply chain planning systems fail to address the needs for ‘intelligent business operations’ described by Gartner because their entire focus is on creating the perfect plan. The term ‘supply chain planning’ indicates their focus. They do not provide the capabilities to monitor, manage, and control the business once planning is “done”. Where supply chain planning systems fail is in being able to

  • identifying the upstream and downstream impacts of events
  • directing the alerts to the people responsible for the impacts
  • orchestrating the multi-functional simulation of ways to resolve the issues
  • incorporating both operational and financial metrics in the comparison of simulations
  • incorporate human judgment as the key element of making trade-offs across functions and competing metrics
  • doing all of this quickly

Doing some of this is not enough. Doing all of it slowly is not enough. Doing all of it quickly provides the Sense-Shape-Respond capabilities described by Gartner that are required to satisfy the needs expressed by George Palmatier of ‘Integrated Planning and Control’.

 

Posted in Control tower, Control Tower Concepts, Demand management


Is Forecasting Fatally Flawed?

Published March 24th, 2011 by Trevor Miles @milesahead 7 Comments

Believe it or not, I didn’t plan the alliteration. But that is my central point: So much of actual demand is unplanned. Which is fine as long as it is near to what was expected in terms of items purchased, period in which purchased, and the customer/region in which the purchase took place. But this does not appear to be the situation in many cases. So is forecasting fatally flawed?

Lora Cecere has been writing about forecasting, principally within the CPG industry for many years. She has worked in industry, for a software vendor, and most recently as a highly respected analyst. In a recent blog Lora states that

 

Mean Absolute Percentage Error (MAPE) for a one month lag was 31 percent + 12 percent.  Data eight years ago for the same companies was an average of 36 percent + 10 percent MAPE.

This made me sit up and listen.  Especially when she went on to quote from her research while at AMR Research that

Based on AMR Research correlations, a six percent forecast improvement could improve the perfect order by 10 percent and deliver a 10-15 percent reduction in inventory.

In other words, there is a lot of benefit to getting the forecast right.  But a range of highly respected CPG companies cannot do better than 31 percent MAPE, with a range of 19 percent to 43 percent?  That caught my attention.  Mostly because I am more familiar with the High-Tech/Electronics industry which has much shorter product life cycles than CPG and therefore more volatile or variable demand patterns. Of course it is difficult to be precise with industry classifications. Does Consumer Electronics fall into CPG, High-Tech/Electronics, or both?  However we slice it, things like cell phones, tablets, cameras, etc have shorter product life cycles, greater seasonal variations in demand, and greater demand variability than do nearly all categories of CPG such as soap, washing powder, etc.  In Consumer Electronics, and more generally High-Tech/Electronics I hear from companies that they seldom get their forecast accuracy, as measured by MAPE, above 50 percent, which is consistent with my observations about the characteristic differences with CPG.  Higher demand variability/volatility would imply a lower forecast accuracy.

Before anyone jumps down my throat, especially Lora, let my state unequivocally that everyone MUST forecast and that all companies should be demand driven.  But …

But where is the discussion about how best to satisfy the missing 31 percent demand in the case of CPG and 50 percent in the case of High-Tech/Electronics?  Where is the discussion about the profitable response to the demand that is not anticipated? I feel as we are only having half the conversation.  The half about forecasting.  But if the best we can do is improve forecast accuracy from 64 percent to 69 percent over eight years in an industry segment with relative stable demand, I think we should be talking about supply chain agility and responsiveness.  What amazes me is that since the early 1990’s we have been applying optimization engines, typically Linear Programming (LP), to the supply side.  Ignoring for the moment the inherent issue of using linear models to represent highly non-linear systems, if you are basing your optimizations on inputs that are best 69 percent correct, are you not focusing on the wrong problem?  Should you not be focusing on systems that enable you to detect true demand early and determine the best way to satisfy the unanticipated demand using the competing requirements of profitability and customer service?  Of course you will need a supply chain that can execute in an agile and responsive manner consistent with your decision.

Here is the rub: All our resources are limited. Time. Cash. People. So in this zero-sum game, where are you going to apply your energies?  Spending eight years to improve the forecast by five percent, or working on the manner in which you satisfy the unanticipated demand in the most timely and profitable manner?

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Posted in Demand management, Milesahead, Response Management