Everybody knows that it’s impossible to forecast with 100% accuracy. This simple truth inevitably leads to a lot of discussion about what is the “right” level of accuracy.

If it’s a “bread and butter” item with a high rate of sale, is 80% accuracy good enough? What level of accuracy should I expect on a seasonal product? Or a slow mover? Or an item that’s promoted frequently?

Look, we’re not in elementary school anymore. There is no grading system for forecasts. Sometimes 80% accuracy is a poor result and under a different set of circumstances 30% accuracy may be good enough.

Your achievable level of accuracy depends on two things: 1) the level of random variation in the demand pattern you're trying to predict (and which is largely out of your control); and 2) the business process you follow to produce forecasts. If you are consistently following a good process, then your accuracy will be as good as it possibly can be.

So how do you know if you're following a good business process?

The Ten Commandments

The Ten Commandments are recognized by Judaism, Christianity and Islam as an important set of rules for guiding human behaviour. No matter what your religion, if you followed the commandments, particularly the ones pertaining to how we interact with each other (Thou Shalt Not Kill, Thou Shalt Not Steal, Thou Shalt Not Bear False Witness, etc.), then you could safely say that you’re not an evil person.

Over the years came many more laws based on the Commandments. It didn't take long for this to deteriorate into a complex web of rules and regulations, many of which contradicted each other. It became more and more difficult to know how to be good.

Then, about 1,000 years after the original Commandments were given to Moses, a young carpenter from Galilee boiled them down nicely into a single Golden Rule:

“Do unto others as you would have them do unto you” (or, alternatively, “Treat others as you yourself would like to be treated”).

If you were to follow this one rule, you would have at least six of the Ten Commandments covered.

The Rules of Good Forecasting

It’s fairly well documented that good supply chain forecasting processes have the following characteristics (or, if you will, commandments):

1) Thou Shalt Be Free of Procedural Bias – This means that there aren’t steps designed into the process itself that cause habitual overforecasting or underforecasting.

2) Thou Shalt Be Free of Organizational Bias – In other words, performance measures are aligned with the goal of your operational forecasting process, so that people aren’t given incentive to intentionally “sandbag” the numbers one way or the other.

3) Thou Shalt Account For Time, Place and Magnitude – You can’t schedule your supply chain around an operational forecast that says you’re “going to sell 10,000 units across all locations over the next 8 weeks”. It needs to be very specific with respect to timing, location and quantity to be of any operational use.

4) Thou Shalt Not Buffer – This is often the toughest to detect, because it’s caused by the best of intentions. In a nutshell, this is the practice of forecasting “a little bit extra, just in case” to guard against service failures.

Like the Ten Commandments, volumes of material has been written in support of these rules. But if you adopt one simple Golden Rule in your forecasting process, you won’t have to worry about being one of the contributors to forecast error.

The $500 Rule

The $500 Rule of Forecast Management States:

“The operational forecast that runs your supply chain is the one on which you would bet $500 of your own money.”

Think about it. Suppose you were obligated to enter a forecasting competition and pay a $500 entry fee. You can use any resources and information at your disposal. But for a particular item in a particular week, whoever comes closest - in absolute terms - to the actual number wins the pot.

If these were the rules of the contest, would you be inclined to take steps that inflate the number beyond what is realistic? Would you simply average a big number across a number of weeks? Would you forecast what the facts are telling you “plus a little bit extra”?

While there’s no antidote for random error and completely unforeseeable events, you can still choose to spend your time and energy (i.e. money) on coming up with forecasts that are as honest as possible (i.e. you’d plunk down 500 bucks of your own money on it).

The great part is that, to your organization, the benefits of unbiased forecasting will make $500 look like chump change.