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Sem 5 Prep
← OperationsForecasting: what and why

Formulas for this chapter

Naive forecast

F(t) = A(t-1)

As a zero-cost benchmark, and when the series has no trend or seasonality worth modelling. Every other method must beat it to justify itself.

F(t)
Forecast for period t
A(t-1)
Actual demand in the most recent period

Forecast error

Error = Actual - Forecast

Step 6 of the process, every period. Keep the sign in the table; drop it only when computing absolute measures.

Actual
Demand that actually occurred in the period
Forecast
What was predicted for that period, before it happened
Step 4 of 23
The real wordsTheory

The four features common to all forecasts

  1. Techniques assume some underlying causal system that existed in the past will persist into the future
  2. Forecasts are not perfect: random variation is always present, so some residual error remains even when every other factor is accounted for
  3. Forecasts for groups of items are more accurate than those for individual items
  4. Forecast accuracy decreases as the forecasting horizon increases

Features 3 and 4 are the ones an exam question turns on: forecast a category rather than a stock-keeping unit, and forecast next month rather than next year.

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