Customer story · Agentic automation

A global mining company halves its GR/IR discrepancies with a bot that sorts them and contacts vendors

A global mining company had a 40% discrepancy rate in its procure-to-pay process, far above the 2 to 5% industry benchmark, and three analysts were managing more than 2,000 vendors. TSP built a custom bot that classifies discrepancies and sends consolidated emails to vendors and internal buyers. Discrepancies fell by 50%, and analysts now focus on the complex cases.

  • Mining
  • Global mining company
  • Worldwide
  • Procure to pay (GR/IR)
Supply officer checking deliveries with a tablet in the supply yard of an open-pit mine
  • 50%fewer GR/IR discrepancies
  • 40%discrepancy rate before, against a 2 to 5% benchmark
  • <5%discrepancy rate targeted

01 · The challenge

Three analysts, 2,000+ vendors

The company’s procure-to-pay discrepancy rate was 40%, far above the industry benchmark of 2 to 5%. Analyst capacity was limited, with three analysts managing more than 2,000 vendors. Discrepancies were classified by hand, and each analyst made 27 emails or calls every two weeks. As a result, 1,920 vendors received minimal attention.

02 · The approach

A bot that sorts discrepancies and does the outreach

TSP replaced manual classification and vendor emailing with a custom bot.

What the bot does

  1. Classifies

    Sorts each discrepancy into one of three categories: MRNI, IR with no GR, and mismatch.

  2. Contacts

    Sends consolidated emails to vendors or internal buyers for each category.

  3. Frees analysts

    Leaves the complex discrepancies to people.

03 · The results

Half the discrepancies, and time back for analysts

  • 50% reduction in GR/IR discrepancies
  • Significant time savings for procurement analysts
  • Analysts focused on resolving complex discrepancies
  • Next: fewer than 1,500 open discrepancies and a rate under 5%, with automated ticketing and follow-ups, a focus on 30 to 89 day items, and no items over 90 days

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