Protected: Five Best Practices for a Demand Plan Sanity Check

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An S&OP Insignt in 45 Seconds

I decided, in the end, to make a post this Friday, but of a slightly different nature.  Click on the picture to watch 45 seconds of my interview with Supply Chain Brain from September.  This may be something you haven’t thought about before.  

Thanks again for stopping by. 

For those in the U.S., I hope that you and yours are enjoying a really good Thanksgiving time.

My Thoughts from the IBF Leadership Conference in Las Vegas

Although it is not yet Friday, I want to take this opportunity to share my thoughts on what I heard at the Institute of Business Forecasting and Planning’s Leadership Business Planning and Forecasting Forum.  I was privileged to spend a couple of days with a rather distinguished group of practitioners, software vendors, academics, and consultants exploring three major areas of interest to most supply chain managers and planners – best practices in Leveraging Integrated Demand Signals, Sales and Operations Planning and Demand Planning.  I managed to leave my notes in my hotel room, but here are a few of my thoughts in no particular order that you may find immediately useful (some completely original, some borrowed, some modified from something I heard):

  • Make use of syndicated data as a leading indicator.  More and more of this is available.  Determine what is available and match it to your business needs, leveraging econometric models.
  • Collaboration is still partly a function of bargaining position.
  • Before you collaborate, make sure you have done your analytical homework so that you understand the total opportunity and how much you need to capture and how much you can afford to give away.
  • A “forecastability” or “reasonability” analysis allows demand planners to be more efficient by highlighting areas where they can engage their education, training, and experience rather than sifting through data is becoming a best practice. 
  • Two key performance indicators that might not have been in your textbook probably ought to be part of your demand planning process:

              √ Forecast Value Added (mean absolute percentage error for new forecast approach  – mean absolute percentage error for old (or possibly naive) forecast approach)

              √ Cost of Inaccuracy (margin and lost goodwill * units underforecasted less safety stock) + (cost of holding inventory * units overforecasted) all summed over the relevant time period

  • Consider engaging finance in the demand planning process.
  • Know the difference between your financial or sales objective and the demand plan.
  • Many companies struggle with the harmonizing of qualitative and quantitative forecasting.  A generally helpful concept here is that qualitative input tends to be best from a top-down  perspective and allocated down;  quantitative forecasting tends to be at a lower, if not the lowest level and rolled up.
  • Forecast both shipments and end-customer consumption and the difference.  In  the consumer goods industry, this is essentially “trade inventory”.
  • Microsoft Excel is still the predominant planning software.  It is how people and organizations innovate quickly.  However, building models in Excel, itself, is problematic in terms of scale, maintenance and process standardization.  A useful improvement would be getting IT or a consultant to create your model in Visual Basic, leveraging Excel as the user interface. 
  • Enterprise software is useful, but customers and users need to demand more from their software vendors.
  • Fit both your model and your metrics to the nature of the business and the data.

While we are on the topic, allow me to also point you to my blog post of a few days ago (September 9) where I outline some of the differences between forecasting per se and a robust demand planning process.

Careful, Comprehensive Inventory Management (Part 1)

Manufacturers and distributors usually spend most of their cash on inventory.  In fact, many service organizations like utilities and health care delivery organizations spend lots of money on materials.  But in the case of manufacturers and distributors, just look at the cost of goods sold as a proportion of sales, compared to any other item.  Given that reality, the better part of wisdom mandates a careful and comprehensive approach to managing inventory.

As a memory aid, I use A56σ to represent such a careful, comprehensive, and corporate approach to inventory management.  Each component of A56σ is essential for achieving sustainable, continuous improvement in inventory efficiency.  There are five concepts which I will alliterate with the letter “A” and the tools of six sigma.  Here is the first “A”.

Anticipate – anticipate market requirements

The more you are able to accurately anticipate the demand by your end customer in the marketplace, the more you will be able to move, make, buy and store the inventory that will sell quickly.  This may seem like a self-evident axiom, but this is not easy and the benefits of incrementally better anticipation go directly into additional revenue as well as more efficient inventory and use of cash. Large bodies of knowledge have been built around this subject from rigorous quantitative models for forecasting to methodologies for collaborative forecasting, both within an organization and across organizations.  The point of diminishing returns can be reached fairly quickly, but if you are not there, it may be your most significant leverage for improved supply chain performance.

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