Company Overview
PrecisionParts Ltd is a Tier-2 automotive components supplier based in Pune, manufacturing precision-engineered parts for major OEMs including Tata Motors, Mahindra, and Maruti Suzuki. With two manufacturing plants and over 500 SKUs, they process thousands of orders monthly.
The Challenge
PrecisionParts was caught in a classic manufacturing paradox: high inventory coupled with frequent stockouts. The root causes were deeply embedded in their planning processes.
₹8Cr Raw Material Inventory
Fear of stockouts led to over-ordering of raw materials. Steel sheets, aluminum billets, and specialized alloys sat in warehouses for months, tying up working capital. With volatile commodity prices, this inventory often depreciated before use.
Production Line Stoppages
Despite high inventory, critical components frequently ran out. A missing ₹50 bearing could halt a production line making ₹50,000 assemblies. The team spent countless hours expediting emergency shipments.
Overtime and Rush Orders
Poor demand visibility meant production schedules changed constantly. Workers regularly pulled overtime to meet last-minute orders, driving up labor costs and affecting morale.
"Our MRP system was only as good as the forecasts we fed it — and our forecasts were basically guesses. We'd order 3 months of material 'just in case' and still run out of the one thing we needed."
— Vikram Kulkarni, Plant Manager, PrecisionParts
The Solution
PrecisionParts implemented Decisio to transform their demand planning and inventory management:
1. Demand-Driven MRP
Instead of relying solely on customer forecasts (which were often inflated), Orion analyzed actual consumption patterns, OEM production announcements, and automotive industry trends to create more accurate demand signals.
- Connected to OEM portals for real-time order visibility
- Integrated industry news for model launch and phase-out signals
- Created probabilistic forecasts with confidence intervals
2. Multi-Tier Inventory Optimization
Nova analyzed the entire bill of materials to optimize inventory at each level — raw materials, work-in-progress, and finished goods — with different service levels based on criticality.
- ABC-XYZ classification for differentiated stocking policies
- Lead-time aware reorder points for each supplier
- Safety stock based on demand variability, not arbitrary weeks
3. Production Scheduling Intelligence
Decisio recommended optimal production sequences to minimize changeovers and balance workload across shifts, reducing overtime and improving throughput.
Implementation Approach
Results After 6 Months
Inventory Transformation
- ₹2.4Cr inventory reduction without increasing stockouts
- Raw material turns improved from 4x to 7x annually
- Obsolete inventory write-offs reduced by 65%
Cost Savings
- 28% reduction in total inventory carrying cost
- Emergency freight costs down by 75%
- Overtime hours reduced by 40%
Service Level Improvement
- On-time delivery to OEMs improved from 88% to 97%
- Production line stoppages due to material shortages: near zero
- Customer complaints about late deliveries dropped 80%
"The freed-up working capital from inventory reduction was more than our entire annual IT budget. We've reinvested it in new CNC machines that are growing our capacity. Decisio didn't just save money — it funded our growth."
— Vikram Kulkarni, Plant Manager, PrecisionParts
Key Success Factors
- Executive sponsorship: CFO championed the project as a working capital initiative
- Data quality focus: Cleaned up BOM and supplier lead time data first
- Change management: Trained planners to trust AI recommendations
- Continuous refinement: Adjusted models quarterly based on forecast accuracy