Sales & Demand Forecast Workspace — example input brief

Purpose: connect historical demand, transparent baseline/driver forecasts, human adjustments, review and immutable published versions.
This is a tutorial input brief, not a complete data export or production dataset.
Project: https://b108f71609be448d949c9f5b6f17f610.prod.enterapp.pro/app/overview

Input tables: Sales History; Stores; Products; Channels; Stockouts; Calendar/Promotions; Baselines; Driver Factors; Overrides; Reviews; Published Versions; Actual Results; Accuracy Reviews; Users.
Fields: week, store_id, SKU, channel, units, revenue, stockout_days, lost_demand, driver_type, uplift, scope, evidence, baseline, driver_impact, approved_override, final_forecast, uncertainty_range, version_id.
Rules: final = baseline + driver impact + approved override. Pending adjustments are excluded. Preserve lineage, reconcile hierarchy totals, freeze published snapshots, compare actuals only when available; never use future actuals.
Workflow: inspect forecast -> trace drivers -> submit justified override -> manager review/publish -> compare version and later actuals.
Roles: Planner proposes; Demand Planning Manager reviews/publishes; scoped users read relevant forecasts.

Observed example, 2026-09-11: Seattle Downtown, W+1 (2026-09-13). Current draft baseline 4,067 + drivers 847 = 4,914. Jamie Brooks requested +180 -> 5,094, Pending review; current override remains 0. Existing FY26 Q3 Baseline v1 snapshot for the same store/week is 4,788. These are separate states, not contradictions. Future actuals must not be fabricated.
If additional demo data is needed, generate clearly labelled synthetic records with consistent IDs and dates.