Aphorism 3: Organizational Policies and Politics Can Have a Significant Impact on Forecasting Effectiveness

We just saw how demand volatility reduces forecastability. Yet our sales, marketing, and financial incentives are usually designed to add volatility. We reward sales spikes and record weeks, rather than smooth, stable, predictable growth.

The forecast should be an unbiased best guess of what is going to happen in the future. It should be based on a rational, objective, and dispassionate evaluation of the historical facts (what has been sold and under what conditions) and future plans and expectations (about pricing, promotional activities, the competitive environment, supply considerations, and the like).

Unfortunately, real-life business forecasting is often contaminated by the wishes, wants, and personal agendas of the forecasting process participants. Although the managers, executives, and sales force of your firm may be stellar citizens of the highest moral fiber (unless you work for Wells Fargo), you cannot assume they are trustworthy when it comes to forecasting.

• Will your sales people forecast low during quota setting time, to make it easier to achieve their bonuses?
• Will a product manager forecast high for a proposed new product, to make sure it meets the hurdles for approval?

You need to consider the ultimate motive of anyone providing or approving forecasts. And then track their performance using tools like FVA.

Aphorism 4: You May Not Control the Accuracy Achieved, But You Can Control the Process Used and the Resources You Invest

You can’t just buy a better forecast. There is no guarantee—no matter how much you spend on people, process, technology, and analytics—that you will achieve the accuracy your organization desires. So focus on what you can do, such as:

• Determine what level of accuracy is reasonable to expect given the nature of your demand patterns.

Morlidge’s articles have good ideas on how to do this.

• Direct all efforts toward achieving that level of accuracy with the least cost in time and company resources.

This is where FVA analysis, and Morlidge’s considerable enhancements to the FVA approach, can direct your efforts to the best opportunities for streamlining your forecasting process, and for accuracy improvement.

• Automate, automate, automate wherever possible.

Large-scale automatic forecasting software (such as SAS Forecast Server) is available, and can deliver forecasts about as accurate as can reasonably be expected, with minimal analyst involvement. Automation can minimize the human touch points, reducing the chance for bias, politics, and personal agendas to contaminate the forecast. And as a Corollary:

• Do not squander organizational resources in pursuit of unrealistic accuracy goals.

When the forecast is good enough for decision making purposes, or has reached the limit of achievable accuracy, no need to waste any more time trying to improve it…move on to something else.

Aphorism 5: Minimize the Organization's Reliance on Forecasting

We forecast not because we want to, but because we have to. Yet it may be possible to reduce an organization’s need for highly accurate forecasts. This can be achieved, for example, by improving the speed and flexibility of the supply chain.

Things like reducing lead times.  Going from make-to-stock to make-to-order. Or at least postponing final product configuration until an order comes in.

So you can react to demand rather than have to anticipate it.

It’s getting yourself out of the business of forecasting.

[See all 12 posts in the business forecasting paradigms series.]