A calibrated BOM engine cut new-SKU BOM time from 1.5 days to 30 minutes and took the guesswork out of copper and compound buys.
Figures indicative; validated metrics available on request.
With 33,000+ SKUs across house wires, power, control and specialty cables, the BOM was the procurement plan. It was built by hand, one SKU at a time.
Engineers recalculated kg/km by hand for every new SKU or tender. A single BOM took one to two days.
Upper-tolerance thickness plus a flat safety margin at each step. Copper and PVC were over-bought and sat as inventory.
The same cable code carried different BOMs across plants and files. No single version matched the approved construction.
Material plans used BOMs that missed spec changes and real scrap rates. The result was compound shortages and spot buys.
Engineering owns the physics. Procurement owns the buffers. The engine makes both visible.
Select a step to see what happened.
We sampled 200 high-volume SKUs and checked each BOM against actual consumption.
Deliverable: Variance baseline by product family and material.
Standard construction logic for each family, aligned to the relevant IS specifications.
Deliverable: Calculation rulebook and parameter master.
Python calculates the BOM. Engineers keep working in Excel.
Deliverable: BOM engine, Excel front-end, variance dashboard.
The highest-value family went first, with engineering and procurement reviewing together.
Deliverable: Pilot sign-off and variance thresholds.
Rolled out family by family, with calibration built into the monthly cycle.
Deliverable: Runbook, trained owners, governance cadence.
Pick a construction, then toggle between the manual and engineered BOM. Hover a layer or bar to see how it is calculated.
Material prices and allowances indicative. Construction parameters simplified for illustration.
Most of the saving came from removing stacked margins. Turnaround dropped from days to minutes in every family.
Per ₹100 of material bought on manual BOMs · axis starts at 90
Hours per new SKU BOM, before → after (log scale)
Figures indicative; validated metrics available on request.
Geometry and density are fixed. Buffers are a business decision. Keep them in separate tables so each can be challenged.
Use actual issue data to set allowances. Opinions about scrap are usually higher than scrap.
One accountable owner for the parameter master kept 33,000 SKUs consistent long after go-live.