Tom's IT Sandbox

Compare Item Period

Pinpoint exactly what changed between two forecast versions by item and period.

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Executive framing

Executive Summary — Answer First

Decision rule: review this page first, then move to deeper drill-down only when the result is economically meaningful.
  • This is the root-cause report for forecast change.
  • Use it to distinguish true demand movement from simple portfolio or timing shifts.
  • The management question is not whether the forecast changed, but where and why.
SCQA / Context

Situation: multiple forecast versions exist. Complication: total changes alone do not explain what moved. Question: which item-period combinations changed, and how materially? Answer: compare current and prior batches at the most granular decision-relevant level.

Issue Tree / Diagnosis
  • Magnitude of change by item and period
  • Nature of change: added, removed, increased, or reduced demand
  • Implications for execution and stakeholder alignment
Analysis & Insights
  • This view is the fastest way to isolate forecast deltas.
  • Use quantity and percent change together; large percentage changes on tiny volumes may not matter.
  • Escalate large absolute changes in near-term periods first; they carry the highest execution risk.
Recommendations
  • Investigate the top absolute changes before approving a revised forecast.
  • Require business explanations for material item-period shifts.
  • Use this page as the core of forecast version-control governance.
KPIs
  • Absolute change by item-period
  • Percent change by item-period
  • Count of changed rows
  • Near-term changed volume
Implementation Roadmap
Phase Key action Owner Success metric
1. Review Run the report and isolate the highest-value exceptions. Planning / Operations Material issues identified within one review cycle.
2. Validate Confirm whether the result reflects real business change, timing shift, or data-quality issue. Forecast owner Exceptions explained and documented.
3. Act Translate validated findings into supply, capacity, purchasing, or governance actions. Cross-functional team Action owners assigned with due dates.
Risks, Gaps, and Next Steps
  • Do not treat a statistical exception as a business conclusion without validating the commercial or operational driver.
  • Where economics are missing, pair this page with item margin, lead time, or inventory exposure before escalating.
  • Use the summary line above the grid to confirm row volume; unexpected row counts often indicate filter or data issues.
Analysis output

Data Table

Use the table below to validate the hypothesis, size the issue, and identify the items or periods that need action.