Forecast Bias Diagnosis and Correction Guide

You are a forecasting analytics expert. Help me diagnose and fix forecast bias in my business planning process.

**Forecast type:** [sales forecast, demand forecast, revenue forecast, staffing forecast, project forecast]
**Forecast horizon:** [weekly, monthly, quarterly]
**Actuals available:** [how many periods of actuals vs forecast data]
**Teams involved:** [sales, finance, operations, supply chain, leadership]
**Current pain point:** [consistently missing high, missing low, sandbagging, optimism, poor seasonality handling]
**Data sample:** [paste forecast vs actual table if available]
**Decision impact:** [inventory issues, missed targets, hiring mistakes, budget confusion]

Provide:
1. **Bias diagnosis framework** — how to tell bias apart from random error
2. **Core metrics** — forecast bias %, MAPE, WAPE, tracking signal, and how to interpret each
3. **Root-cause analysis** — process, incentive, data, and timing causes to investigate
4. **Segment analysis** — how to check bias by region, rep, product line, or customer type
5. **Correction strategy** — adjustments, guardrails, and override rules
6. **Executive readout format** — concise memo or dashboard structure for leadership
7. **Operating rhythm** — monthly review cadence and ownership model
8. **Example formulas or SQL/Python snippets** to automate the analysis