Forecasting Mistake Number 1: Forecasting to the Wall

In today’s session at CFO Magazine’s 2011 Corporate Performance Management Conference, speaker and author Steve Player, of The Player Group and North American Director of the Beyond Budgeting Round Table, brought out lots of valuable information about the need for organizations to move from a once-a-year, top-down “budgeting” process and into an ongoing process of rolling forecasts.

In doing so, he employed a striking analogy.

Player asked the attendees: Would you be happy with a new car, if, when you first bought it, the headlights gave you a good view of the road ahead—shining out maybe a 600 feet ahead of you. But after three months, the headlights only gave you visibility for 450 feet; and after owning for six months, the headlights only showed you 300 feet of the road before you?

Of course not! No one wants a car like that.

Nevertheless, that is precisely the kind of performance being actively supported with the function of traditional methods of budgeting and forecasting. First the company is looking forward a full twelve months. Three months later, the company is looking only nine months into the future. And, after another three months, their view into the future—their forecast or their budget—gives them only six months of guidance.

What is worse is the fact that the one-year forecast was likely put together from statistics collected and judgments made three to six months earlier. So, by the time the firm’s forward-looking view is obscured beyond six months, the six months they are seeing in the forecast is now nine to twelve months old and out-of-date.

Is it any wonder that such a firm’s “budget” is considered little more than a well-intentioned joke—or perhaps just something to satisfy the executives—by the workers who are all too frequently being measured against the budget?

Steve Player calls this approach “forecasting to the wall,” where no one has a clear vision beyond the 12-month “wall.” He also calls it, “Forecasting Mistake Number One.”

Forecasts, when used, ought be updated as often as necessary; and certainly every time there is a significant change in the mathematical, statistical or intuitive elements underlying the existing forecasts. Forecasts should also be rolled into the future far enough and frequently enough to allow the management changes they are intended to guide to take effect for driving ongoing improvement.

“Mistake Number One” – Think about it.

How do forecasts fail? Let me count the ways…

The only certainty about forecasts is that they will be wrong. So, let’s start to enumerate some of the reasons forecasts are wrong:

1. Frequently, they aren’t forecasts at all; they are only guesses
2. As W. Edwards Deming said, “Wherever there is fear, you will get wrong numbers.”
3. Forecasts are not prophecy and were never intended to give the actual answer to, “How many units will be sold next month?”
4. Forecasts are always based on assumptions and frequently the assumptions are wrong
5. Forecasts attempt to predict variable behavior into the future
6. Forecasts cannot take into consideration every potential variable that might affect the result for two reasons: a) we don’t know all the variables, and b) even if we did, there isn’t enough computing power in the universe to take them all into consideration
7. Forecasts almost always are given as a single number (in the business context) when, in fact, they should be expressed (at a minimum) as a number and the standard deviation surrounding that number
8. Many forecasts originate with salespeople
9. The salesperson provided his “best guess” forecast
10. The salesperson provided what he/she thought he/she could sell
11. The salesperson provide a “safe number,” so that he/she can “hit her target”
12. The salesperson provided an “average” calculated from who knows what—last year? last three months? extrapolated from last week?
13. The salesperson provided a “big number” and will try to hit it because of pressure from sales management
14. We try to forecast too far into the future—say, three months instead of three days
15. The forecast is based on the assumption that—except for the things we specifically know will change—everything else will remain the same (but it never does)
16. Our suppliers’ lead times are unreliable, so we don’t know the actual period our forecast needs to cover
17. We forgot to carry the 2 when doing the math
18. Our Excel™ spreadsheet formulas and references are off, but we haven’t noticed it yet
19. Our forecasts for our finished goods are pretty good, but when MRP blows down through our multi-level BOMs, the forecast explodes due to our minimum batch sizes, percent-over and other production policies
20. Some departments just can’t get their homework done on time and we have to produce a number from somewhere

Go ahead, feel free to leave your comments adding to the list.

[Cross-posted a Kinaxis Supply Chain Community]