Predictive Raw Material & Packaging Planning
Business Context & Operational Challenge
A multi-plant industrial manufacturer suffered recurring production line stoppages due to unexpected shortages of specialized raw packaging materials. Procurement teams operated reactively, struggling with lead-time volatility and fragmented supplier updates.
Existing Process & Limitations
Material requirements were calculated through weekly static spreadsheet exports from legacy ERP systems. Plant managers placed emergency purchase orders with short delivery windows, resulting in expensive expediting premiums and idle plant capacity.
Solution Architecture & Technology
Sambhav designed and deployed Python-based statistical forecasting models coupled with consumption-driven procurement planning. The platform ingests real-time plant production rates, supplier transit milestones, and historical seasonal variances to project inventory requirements days in advance.
Data Integration: Consolidated raw material consumption records across multiple plant ERP databases.
Model Calibration: Engineered statistical time-series forecasting models calibrated against historical seasonal demand.
Procurement Integration: Configured automated threshold triggers that notify buyers before buffer stocks deplete.
Deployment & Training: Rolled out executive and plant-level planning dashboards with weekly feedback loops.
Measured Outcomes & Governance Methodology
Enhanced planning visibility allowed procurement teams to proactively schedule vendor purchase orders, substantially lowering plant downtime and emergency freight costs.
Loss reduction was quantified by comparing annual shortage-driven downtime and emergency expediting freight expenses between FY24–25 (pre-implementation) and FY25–26 (post-deployment).
Documented client metric across FY24–25 to FY25–26 multi-plant production deployment.
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