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What this page is for

Forecast accuracy answers a simple question: how close was the forecast to what actually sold? Spherecast compares a past snapshot of your plan against actual sales and scores the miss. You can measure any metric on the ladder, and you can control how far in advance the forecast was made.
This may be a feature some companies don’t have turned on. If you don’t see it, it isn’t enabled for your company.

What you need first

Accuracy needs snapshots — frozen copies of the plan taken in the past. If none exist yet, there’s nothing to compare against. Create snapshots from the demand plan (see Building consensus).

The accuracy metrics

MetricFull nameWhat it tells you
MAEMean Absolute ErrorThe average size of the miss, in units
MAPEMean Absolute Percentage ErrorThe average miss as a percentage
Bias (Abs.)Absolute biasWhether you systematically over- or under-forecast, in units
Bias %Percentage biasThe same systematic lean, as a percentage
MAE and MAPE tell you how far off you were. Bias tells you which direction you consistently lean — a positive bias means you keep forecasting too high, a negative bias too low. Each metric can be measured for Target, Baseline, Baseline Adj., or Consensus, so you can see which row of the ladder was most reliable.

Lag: how far ahead the forecast was made

A lag is the number of months between when the forecast was made and the month it was forecasting.
  • Lag 1 = the forecast made one month ahead.
  • Lag 3 = the forecast made three months ahead.
You pick which snapshots to use by lag. Unavailable lags are greyed out — you can only compare lags for which a snapshot exists.

Compare lags to month

This choice controls how each month lines up with its snapshot:
SettingWhat it does
CurrentEvery month uses the snapshot from the same number of months ago
EachEach month shows the forecast that was made that many months in advance of it

Plotting over time

You can also chart snapshot time-series — for example Baseline (Snapshot) and Consensus (Snapshot) — against actuals, so you can see visually where the plan drifted.

Step by step: check last quarter’s accuracy

  1. Confirm snapshots exist for the period you want to review.
  2. Open forecast accuracy and choose the metric — for example MAPE.
  3. Choose the ladder row to score — for example Consensus.
  4. Pick the lag (grey lags have no snapshot).
  5. Set Compare lags to month to Current or Each.
  6. Read the score, and optionally plot the snapshot series against actuals.

Example

A planner checks Consensus at Lag 1 for last quarter. MAPE comes back at 12%, and Bias % is +4%, meaning the plan was usually a little high. At Lag 3 the MAPE rises to 21% — the further ahead they forecast, the less accurate they were. Plotting Consensus (Snapshot) against actuals shows the gap widened during a promotion month.
Tip: Accuracy only works if you take snapshots consistently — ideally every planning cycle. A missed snapshot means a greyed-out lag you can never recover. See Building consensus to make snapshots a habit.