Sterno: Predictive Procurement & Raw-Material Planning

The business challenge

Raw-material purchasing had to account for much more than current inventory. Production requirements, sales forecasts, BOM/MRP demand, supplier performance, transportation, pricing, international sourcing variables and warehouse constraints all affected whether material would actually be available when production needed it.

The solution

Designed a predictive procurement tool in a Microsoft, SQL and Python environment. The solution evaluated future material requirements and sourcing alternatives, then produced purchase recommendations and advance alerts so procurement and operations could act before a projected shortage affected production.

• Microsoft
• SQL
• Python

Implementation

• Demand forecast

  Forecast future production and material demand from sales forecasts, sales accuracy and the production plan with its capacity limits.

• BOM/MRP translation

  Translated production requirements into raw-material needs: required quantities and timing.

• Inventory constraints

  Compared projected needs against inventory, minimum/maximum levels, storage limits and expected scrap.

• Vendor & sourcing intelligence

  Evaluated available vendors and international sourcing options using SLA, capacity, location, pricing, tariffs, transportation distance and currency conversion.

• Predictive engine

  Identified when projected supply would no longer cover production requirements and recommended the required purchasing action, triggering alerts up to six months in advance.

Business results

• Planning visibility

  Projected material shortages could be identified up to six months ahead.

• Procurement productivity

  Reduced manual analysis by consolidating multiple operational and sourcing variables into one decision process.

• Production continuity

  Purchasing recommendations considered production requirements, inventory coverage, scrap and warehouse constraints.

• Smarter sourcing

  Purchasing alternatives could be evaluated across vendors and locations using cost, logistics, SLA and availability factors.

• Actionable alerts

  The system shifted procurement from reacting to shortages toward planning before the risk materialized.