Forecasting Wordplay

If it is true that words have meanings, why don’t we throw away words and keep just the meanings? – Ludwig Wittgenstein via Anatol Holt

How do you describe your demand forecasts?

In retail, I’ve had numerous conversations that go something like this:

Me: “Do you really think you’re going to sell 10,000 units on that promotion? You’ve never sold higher than 8,000 at that price point.”

Retail Buyer/Demand Planner: “Yeah, it’s a bit optimistic.”

While less common, forecasts can also be made lower than one would expect (or “pessimistic”, if you will), particularly if an incentive structure exists where people are rewarded when actual sales blow the forecast out of the water.

While these “optimistic” or “pessimistic” numbers are entered into the forecasting system and potentially even drive the replenishment and supply planning functions, it would be a misnomer to call them forecasts.

Saying that a forecast is optimistic is an admission that you believe it’s biased to the high side for no good reason. You can call it a goal, a wish or a dream, but it is NOT a forecast.

In a similar way, a “pessimistic forecast” is a hedge, not a forecast.

Simply put, if you don’t truly believe the numbers you’re producing are a reflection of what’s actually going to happen, then you’re not forecasting. A true forecast is the prediction you’d make if you were obligated to bet $500 of your own money on the outcome.

That’s not to say that the most objective forecast produced by the most unbiased demand planner may not be way off. At its essence, demand planning applies assumptions in an attempt to predict human behaviour. That doesn’t always work out.

That’s also not to say that the words “optimistic” and “pessimistic” have no place in forecasting – so long as there are assumptions to back up the judgments.

For example, “I’m optimistic that we’ll beat last year’s sales, because we’ve sharpened our pricing and caused a key competitor to exit the market for this category.”

Or “I’m pessimistic about the sales outlook for our high price point luxury lines because the economy is in the tank and discretionary spending is going to be way down for the next 12 months.”

But what about the potential missed opportunities? What if we produce an unbiased, objective forecast and it ends up oversold to the point that we run out of stock and leave sales on the table?

Isn’t having a forecast that’s “a bit too high” much less risky in terms of being able to satisfy customer demand?

To be clear, a forecast is just one determinant of the level of stock needed to satisfy customer demand. The other is the uncertainty of the demand. If you apply the uncertainty to the supply side of the equation (i.e. safety stock), then that frees you up to forecast with objectivity.

Yes, the uncertainty needs to be quantified, but if you habitually describe your forecasts as being “optimistic” (which is a euphemism for “biased”), then you’re already doing that anyhow:

  • Optimistic Forecast = What we think customers might buy
  • Objective Forecast = What we think customers will buy
  • Safety Stock = Optimistic Forecast – Objective Forecast

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