A statistical forecast of zero can cause lots of confusion for forecasters, especially when the historical demand is non-zero. Sure, it’s obvious that demand is trending downward, but should it trend to zero? When the older demand is much greater than the more recent demand and the more recent demand is very low volume (i.e., 1,2,3 units demanded), the answer is, statistically speaking, yes. However, this might not jive with the planner’s business knowledge and expected minimum level of demand. So, what should a forecaster do to correct this? Here are three suggestions:
- Limit the historical data fed to the model. In a down trending situation, the older data is often much greater than the recent data. When the older much higher volume demand is ignored, the down trend won’t be nearly as significant. You’ll still forecast a down trend, but results are more likely to be line with business expectations.
- Try trend dampening. Smart Demand Planner has a feature called “trend hedging” that enables users to define how a trend should phase out over time. The higher the percentage trend hedge (0-100%), the more pronounced the trend dampening. This means that a forecasted trend will not continue through the whole forecast horizon. This means the demand forecast will start to flatten before it hits zero on a downtrend.
- Change the forecast model. Switch from a trending method like Double Exponential Smoothing or Linear Moving Average to a non-trending method such as Single Exponential Smoothing or Simple Moving Average. You won’t forecast a downtrend, but at least your forecast won’t be zero and thus more likely to be accepted by the business.
Use actuarial forecasts. Demand falls as installed base decreases and as old-age actuarial rates decrease. Time series forecasts are like driving while looking backwards and may require fudging.