Business problem

Demand Planning & Forecasting

How wrong the forecast is, in which direction, and where the error is worth fixing.

Metrics

Computable definitions from the KPI Dictionary — every decision switch made explicit, with the formula behind it.

KPI	Formula	What it answers
Forecast Accuracy — WAPE & MAPEK-03	$\begin{aligned} \text{WAPE} &= \frac{\sum_{i} \lvert F_i - A_i \rvert}{\sum_{i} A_i} \\ \text{MAPE} &= \frac{1}{n} \sum_{i} \frac{\lvert F_i - A_i \rvert}{A_i} \\ \text{Accuracy} &= \max\!\left(0,\; 1 - \text{WAPE}\right) \end{aligned}$	How far off was the forecast — and is your accuracy a volume-weighted error, or an average of per-item percentages that lets the smallest items dominate the number?
Forecast BiasK-04	$\text{Bias}\,\% = \frac{\sum_{i} F_i - \sum_{i} A_i}{\sum_{i} A_i}$	Does the forecast systematically run high or low — and is bias a signed percentage, a tracking signal, or a streak count, with which sign convention?

Forecast error is easy to compute and easy to compute wrongly. The number moves with the grain it is measured at, the lag it is measured from, and whether errors are weighted by volume before they are averaged — so two teams can report the same forecast as accurate and as poor without either being mistaken. The definitions here make each of those switches explicit and name the house convention; the monthly-cycle and plan-vs-actual patterns carry the same discipline into the review meeting, where the harder question is whose plan the actual is being scored against. The reference builds run the full chain over simulated data — from the forecast override that makes accuracy worse, through the cycle review that locks a plan, to the planner-grade instrument that splits a miss into volume, mix, price and timing.

Reference builds

Reference builds for this business problem, implementing the definitions above wherever one exists, running over frozen, simulated data. Not a resource and not a case study — no client data, and no client named.

In the references

Where this data lives in each source system. A way into the ERP references, not an index of them — every reference landing lists all of its modules.

SAPAdvanced Planning & Optimization JDERequirements Planning D365Master Planning M3Planning EBSPlanning NetSuitePlanning

The other business problems

Inventory & Working Capital — What you're holding, why it's there, and what it costs to hold it.
Customer Service & Fulfillment — Whether the order arrived complete, on the date you committed to.
Procurement & Supply — What's on order, when it lands, and how the supplier actually performs.
Manufacturing & Production — Whether the plant built what the plan said it would build.
Data Foundation & Governance — Landing ERP data in a lakehouse without losing deletes, history, or control of who reads it.

See this domain in the whole library