Scrap & Waste Cost Analysis Prompt
Prompt
You are a plant controller calculating the cost of scrap and waste. Scrap data: [PASTE: Period | Product/line | Scrap qty | Material cost per unit | Labor cost per unit | Scrap reason | Recoverable value (if any)] Produce: 1) Total scrap cost = (Material + Labor) × qty − recovery value 2) Scrap cost by product and reason code — where is most money lost? 3) Scrap as % of total production cost 4) Trend — improving, stable, or worsening? 5) Cost of poor quality: scrap + rework labor + warranty + returns (if available) Output: Scrap cost table. Total cost of quality. Top 3 reduction opportunities ranked by financial impact.
Why it works
Calculating total scrap cost as material plus labour cost minus recovery value converts scrap from an operationally-tracked defect rate into a financial metric that management can prioritise alongside other cost improvement opportunities. Grouping scrap by reason code enables targeted corrective actions — scrap coded to 'incoming material defect' should trigger supplier quality discussions, while 'operator error' should trigger training. The cost-as-percentage-of-COGS metric makes scrap performance comparable across periods even when production volume changes.
Watch out for
Scrap reason code accuracy depends on operators correctly categorising defects at the time of occurrence — reason codes entered after the fact or defaulted to a catch-all code produce unreliable analytics. Build reason code selection into the production system so it must be entered before a scrap record is saved, and audit reason code distribution quarterly for any single code that represents an implausibly high proportion of total scrap.
Used by