Coke versus Pepsi, New York versus Chicago style pizza, The Red Sox versus The Yankees – we all have the right opinions and know the other side is obviously wrong and have lost their minds. We could easily add to this list our own continuous debates of IBP versus S&OP, opinions on one number forecasts, and now Demand Driven versus Demand Planning. With any of these debates it seems to become an either/or discussion and in the case of Demand Driven MRP (DDMRP), it has started to devalue forecasting, and doesn’t understand its value or potential.

It seems people have drawn their proverbial line in the sand and taken one side or the other. On one extreme, there is an argument which states forecasts are always wrong, “why do them at all?”. At the other end of the spectrum is the argument that, when it comes to forecasting, in the land of the blind the one-eyed man is King, and that forecasts are the only way to see what is going to happen next.

I am never short on opinions, so here’s what I think.

Demand Driven MRP Vs Forecasting: Who Wins?

So, what is the right answer? To be fair and in full disclosure, I have an obvious bias. To better understand my perspective: I have been in the Demand Planning field for over fifteen years, I am a Certified Professional Forecaster, I won the 2016 Business Forecasting & Planning award, and I am currently Director of Thought Leadership at the Institute of Business Forecasting – so I may have a slight prejudice. That said, you may also decide after reading this article that my background may just add credibility to my sentiments. In this article, I have attempted to put those biases aside and address the concepts of Demand Driven and Demand Planning. What’s more, I will discuss why my own profession is responsible for this debate.

Demand Driven Plans For What Is Known, Rather Than Anticipating Unknowns

One of the main arguments I hear in support of Demand Driven is that forecasts are always wrong. To fix this, a Demand Driven approach is employed where downstream activities such as production or supply are based on actual orders rather than forecasts. This means a company reacts to known demand rather than anticipating it. This in theory would eliminate the dependency on forecasts, at least operationally. I have no problem with the underlining concept, and there is no doubt that a bird (or an order) in the hand is worth two (forecasted orders) in the nest.

So far so good for Demand Driven MRP.

Demand Driven Dismisses Value of Forecasting Whilst Simultaneously Relying On It

Things start to get cloudier when you begin to place inventory as buffers using historic actuals. I do not care what you try to call it – what you have is a forecast. Using an average daily usage, for example, is a crude, naïve forecast. Adding a seasonal index or factor to this is a rudimentary seasonal random walk, or another type of unsophisticated forecast. Adding other variables such as promotional lifts, trends, or other factors and you are recreating a different forecast for operations that may be disconnected from the rest of the organization.

Unfortunately, by not calling this a forecast, we do not apply the same scrutiny as we do to demand plans. We are even unaware how much more inaccurate we may be, or be ignorant of the variability or bias we may be adding with our assumptions.

Demand Driven therefore seeks to debase forecasting but still uses forecasts, but ends up with forecasts that are unproven and may not be fit for purpose.

Demand Planning Can See Beyond Just The Order

Yes, it is true that the demand plan will always be wrong, but what we have seen is that taking an average of historical demand then layering on assumptions is no longer actual demand either. Demand Planning is defined as “using forecasts and experience to estimate demand for various items at various points in the supply chain.” A good demand plan or planner injects discipline into the process to minimize error and bias for a proven and tested signal. Demand Planning best practices should use performance indicators such as Forecast Value Added (FVA) and measure against naive. If naive is better, the demand plan should use it. If not, it uses better statistical or judgmental models, or probabilistic forecasts.

Naturally, you also want to use the truest form of demand that is available to you. In many cases that may very well be sales orders. It could also be vendor managed inventory demands, point-of-sale, or even unstructured data such as website or social media interactions. A well-developed demand planning or forecasting process will drive beyond just orders even closer to consumer demand to provide even greater insights.

So far so good for Demand Planning.

Few Companies Actually Use Downstream Data

The problem (according to 2015 data) is that less than 15% of companies are able to exploit the use of downstream data for any advantages. In a 2012 SAS article, under 50% said they used any point-of-sale to create their forecast. In addition to these, there are some that are even worse and are still generating constrained forecasts based on shipments or supply chain constraints, or trying to use their profit or budget plan as the operational plan.

A potentially even bigger problem is the dirty little secret that most forecasts are not only wrong, but they are not even beating the naive. There have been studies that show everything humans keep trying to do to improve the forecast is often making things worse. So, as far as Demand Planning and our forecasts are concerned some of the criticism from Demand Driven about forecast is justified – “we have been weighed, we have been measured, and we have been found wanting.”
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Which Approach Is Better, Demand Driven MRP Or Demand Planning?

When there is a void in business operations, there is a natural instinct and obligation to try to fill it. The Demand Driven approaches have all been inspired out of necessity – that there is a known gap in planning and it was going unfilled.

In many ways, I cannot blame them. If you think about it, it is our fault.  Demand Driven was inspired because demand planning has not done its job. Demand planning across a lot of organizations – either out of ignorance or indolence – is falling short of its capabilities. We were not delivering what the business needed to be more responsive and operate more efficiently. Even worse, the basic principles of Demand Planning and best practices in many companies are still being neglected or abandoned entirely.

Demand Planners Need To Wake Up And Start Doing Their Jobs

I do not know how else to say this or sugarcoat it, but the answer is simple: we must start doing what we are being paid to do. We cannot bury our heads in the sand and refuse to accept that we, as a profession, have failed to live up to our potential.

We must take proactive steps to deliver the results we are capable of delivering. Here’s how:

Plan According To What You Know    

We need to plan according to more of what we do know, and get as close as possible to the source of demand. We are uniquely positioned to go further upstream, sort through the noise and scrutinize the demand signals and look at probabilities to offer the best picture of what is happening. In the operational planning horizon, demand sensing (the use of predictive analytics and pattern recognition) can replace rules-based consumption to drive better replenishment.

Focus on Forecasts Beings Accurate, Not Precise

Knowing we are wrong, we need to work on being more accurate rather than being precise. Many Demand Planners get hung up on the forecast number and neglect the forecast range. Ranges are more accurate and many supply chains can absorb some variability. Focusing on demand flow and setting up buffers helps with this, but we need to work in collaboration to determine optimal levels based on the greatest precision, as well as the accuracy we can attain.

Eliminate Latency

We need to try to eliminate latency in our process. If it requires a monthly process to produce the forecast for next week, you might have a problem. Demand Planning needs to be lean and become more agile and responsive. Utilize more demand sensing techniques to help identify demand trends, provide advanced warning of problems, and remove the latency between plan and operational response.

Go Beyond Forecasts

Understand it is not all about forecasts. There is more to the Demand Planning role than just creating a forecast number – we must intimately get to know our data and attributes. Use error to improve, not just to measure. We need to better understand the drivers and flow of demand. Understanding demand drivers and error, as well as demand flows, helps with building ‘what-if’ capabilities. If we are truly intimate with what is happening and why, we have the ability to do one better than demand-driven: we can actually drive demand through prescriptive analytics and figure out how to make demand happen.

So Where Do We Go From Here?

The first step is admitting we have a problem. One of the reasons there is even a debate between Demand Driven and Demand Planning is because Demand Planning was not living up to their side of the bargain. It is not that one is better, but we need to (at least) do better than we have. For Demand Planning, this means both companies and professionals. To do this we need to continue to learn, share, and advance:

  • Learn new techniques as well as best practices. You can stay current with articles in publications like the Journal of Business Forecasting, and engage with the wider forecasting and planning community. (I’d love to see more of you at our IBF conferences and tutorials.)
  • Better understand the role of Demand Planner and learn how to structure your team and recruit the best employees, and maximize their potential. Assess and improve your current capabilities through demand-planning functional maturity models.
  • Share with other functions what you can do and how you can add value to their processes. Share your learning with other professionals so that together we can continue to grow.
  • Not just individually or as a profession, but as a company. Between Demand Driven and Demand Planning, it is not that one is better than the other; as we learn better practices and collaborate, we advance together and find the right answers.

Ultimately this debate comes down to everyone working together and putting the pieces together.  There are principles and techniques in Demand Driven that drive value and there are principles and techniques (if we apply them) in Demand Planning that drive value. Entrenching yourself on one side of the debate doesn’t help anyone.