Performance & Help

Planning Performance and KPI Interpretation

Read mature service, forecast-quality, inventory, and planning-impact evidence with explicit formulas and data-quality states.

Planning Performance uses durable snapshots and incremental fact tables. It does not calculate several years of analytics when the dashboard opens and it does not use current Action Lines as historical evidence.

Full Odoo Planning Overview Inventory and Service tab showing KPI values, sample counts, formulas, and data-quality labels
Read every KPI together with its sample count, formula, period, and data-quality state.

Inventory & Service

  • Unit Fill Rate compares eligible delivered quantity with ordered quantity under the documented maturity rule.
  • Customer On-Time Delivery and OTIF use original promise dates captured before later rescheduling can erase lateness.
  • Supplier On-Time Receipt and lead-time reliability use original planned receipt dates and actual receipts.
  • Inventory Turnover is value-based only when dependable COGS and average valuation are available; Unit Turnover remains separately labeled.
  • Stockout Rate, Excess Inventory Value, and Dead-Stock Value use explicit eligibility and valuation rules.

Forecast Quality

  • WAPE is the primary portfolio accuracy KPI: total absolute error divided by total actual demand for mature eligible observations.
  • Bias stays signed: positive is over-forecast, negative is under-forecast.
  • MAPE - Non-Zero Actuals excludes zero actuals and displays coverage.
  • Backend confidence is a separate model signal, never realized accuracy.
  • Stockout-censored observations are separated so unavailable stock does not make a forecast look falsely high.

Planning Impact

  • The impact ledger links recommendations, overrides, ignores, RFQs, POs, transfers, due dates, and mature outcomes.
  • Purchase Spend Deferred is not profit or permanent savings.
  • Estimated Stockout Exposure and Estimated Stockout Value Protected remain labeled estimates with assumptions and evidence quality.
  • Estimated ROI appears only with configured cost, mature benefit evidence, and sufficient samples.

Operational Perfect Order Rate

In the current implementation this card is effectively an OTIF-style measure because return qualification is not yet populated in the fact builder. Do not interpret it as a verified no-return perfect-order rate.

Data-quality states

  • Reliable, Partial Coverage, Approximate, Collecting Baseline, Stockout-Censored, Missing Cost Data, and Insufficient Samples explain whether a value is decision-ready.
  • Open the information panel for the formula, exclusions, maturity rule, numerator, denominator, and source status.
  • Use the drill-down to reconcile the card with its underlying population.

Collecting Baseline is not zero

Forecast horizons, promise dates, deliveries, receipts, valuation, and outcome windows need time to mature after analytics is enabled.