Tom's IT Sandbox

Small Values

Flag unusually small quantities that may reflect real niche demand or data defects.

← Back to Reports
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.
  • Small values deserve scrutiny because they can represent either legitimate demand or bad data.
  • Use this page as a targeted data-quality and exception review tool.
  • The objective is not to eliminate small values, but to explain them.
SCQA / Context

Situation: some forecast rows have very small quantities. Complication: these can be valid, but they can also come from import or mapping errors. Question: which small values should be reviewed before the plan is trusted? Answer: isolate sub-threshold values and investigate systematically.

Issue Tree / Diagnosis
  • Potential data anomalies
  • Legitimate low-volume demand versus errors
  • Prioritization of cleanup effort
Analysis & Insights
  • Sub-threshold values are disproportionately important in data validation.
  • The business should focus first on small values in important items or near-term periods.
  • Repeated unexplained tiny values usually point to a process issue.
Recommendations
  • Define a review threshold by item family or business rule.
  • Investigate small values on high-priority items first.
  • Document whether the exception was real demand or corrected data.
KPIs
  • Count of sub-threshold rows
  • Resolved exception rate
  • Share of small values on high-priority items
  • Repeat occurrence rate
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.
10 row(s) returned.
Analysis output

Data Table

Use the table below to validate the hypothesis, size the issue, and identify the items or periods that need action.
ForecastBatchIDItemCodePeriodDateForecastQty
8300FX11/9/20252
8V25255AX11/9/202551
9M300AX1/11/20267
9VS20255X2/1/202668
9VSF30264X1/25/202656
10WSF20264X3/15/202648
11DM20254MX3/22/202668
11WSF20264X3/15/202648
14VS20255X2/15/202674
15VX071555/17/202628