EKG Catalog
Estimate vs Actual & Lessons Learned
EKGF/ekg-catalog

Estimate vs Actual & Lessons Learned

Complex Construction Project Quotations Knowledge Capture & Continuous Improvement Document Ingestion & Knowledge Extraction Estimate vs Actual & Lessons Learned SME Knowledge Capture Traceability & Provenance
Complex Construction Project Quotations Knowledge Capture & Continuous Improvement Document Ingestion & Knowledge Extraction Estimate vs Actual & Lessons Learned SME Knowledge Capture Traceability & Provenance
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Estimate vs actual and lessons learned closes the feedback loop by comparing bid assumptions and estimated costs against actual project outcomes, explaining variances, and feeding validated insights back into cost libraries and SME knowledge. This use case aligns actuals to the original WBS/BoQ using EKG relationships, explains drivers of variance with traceable evidence using GenAI, updates unit rates and productivity factors, and maintains governed improvements for reuse in future quotations.

Close the loop by comparing bid assumptions and estimated costs against actual project outcomes, explaining variances, and feeding validated insights back into cost libraries and SME knowledge.

  • Typical inputs: project actuals (costs, quantities, productivity), change orders, schedule performance, bid baseline
  • Typical outputs: variance analysis, updated unit rates and productivity factors, reusable lessons learned, risk calibration
  • EKG + GenAI: align actuals to the original WBS/BoQ, explain drivers of variance with traceable evidence, and keep improvements governed for reuse.