My experiences in a variety of industry settings certainly support the position that models and statistical methodology are important but not sufficient to create reliable forecasts and plans. The models and statistical methodology address the systematic issues of the past inherent in the historical data. They can bring a factual basis important to a systematic evaluation and discussion of the future outlook in the forecasting and planning processes. But they have to be supplemented with market information, judgment, and business assumptions about the future. This can only be done with a well functioning, cooperative, and participative process. The companies with which I have worked that are having difficulties in their forecasts and plans may be experiencing technical difficulties, but most often are being affected by process problems that are overwhelming all of their other forecasting and planning activities. Process is more important than statistical methodology and systems, although one needs all working together and in the right proportions to get the best results. The process is the more challenging element of the forecasting and planning mix because of the many human interaction factors and qualitative issues that can be affecting it. A lethal problem, of course, is a process which does not have management support. I quite enjoy the technical side and would enjoy nothing more than to spend most of my time there. But as important as models and methodology might be, one cannot afford to underestimate the importance of a well designed, well managed, and well performing business planning and forecasting process.

Mark Lawless
Managing Principal
Marlaw Business Advisory Services

“How can you say we don’t forecast? We already have a great forecasting capability in our ERP system! We simply plug in the product we need to build, and it blows out each item we need to buy or build and even lead-time.”

I guess this kind of statement coming from someone from a large corporation won’t surprise you. We have made a progress over time with respect to forecasting and planning, but still a long way to go.

Chaman
St. John’s University

These are great points you bring out about forecasting. Fundamentally what it comes down to is that we can never incorporate all the influences on demand nor can we build models that represent these influencers accurately. Human judgment must be brought to bear because the human brain has a great ability of understanding contextual nuances, machines do not. Most companies that are doing a reasonable job of forecasting understand that the statistical forecast is a starting point, not the end point, becuase they understand that the forecast can never be 100% accurate.

I have to admit though that I find the demand side of the house to be more in tune with the idea that “life is fuzzy”. The supply side of the house, on the other hand, tends to believe that the output from their ERP and associated planning systems are accurate and, even worse, optimized. The results of these systems are taken as “marching orders” for the supply side, even though the primary driver for the supply side, the forecast, is understood not to be a 100% accurate representation of demand. First of all, it may be optimized, but for demand that never materializes. In addition, while undoubtedly manufacturing efficiency has improved greatly over the past 20 years, there are still machine failures and quality problems from tools breaking, raw material defects, incorrect inventory counts and a host of other reasons that make the output from a manufacturing site variable.

Yet faced with this situation of variable demand and variable supply, many companies assume the output from their planning systems is optimized and accurate. I think they should be heeding your advise on forecasting and applying it to the supply side too. The plan produced by ERP and planning systems should be treated as a starting point to which human judgement is applied.

Regards
Trevor Miles
Kinaxis