Spare Parts Rationalization Helped Reduce Inventory Costs

CASE STUDY

Spare Parts Rationalization Helped Reduce Inventory Costs

SUMMARY

The client’s operations were spread across different geographies and IT systems. It resulted in duplicate information across systems, sub-optimal inventory positions, and escalating inventory costs. Sancus helped harmonize the data from different systems and create an AI/ML-based layer of demand forecasting and machine failure prediction that helped reduce inventory cost.

APPROACH

De-duplication of parts data using Sancus:

Identify parts with different names that are the same/similar in terms of description and usage
BoM intervention – by redesigning BoM to minimize parts (principles of concurrent engineering)

Data enrichment – using supplier/manufacturing/other databases to provide holistic information about items, thus enabling Spare parts consolidation/rationalization
Category wise Demand forecasting of spare parts
Prediction of Machine failures to optimize spare part inventory levels and minimize downtime
Integration with existing IT systems for seamless adoption

KEY BENEFITS

Wholistic view of spare parts inventory from 41 plants across the globe, recorded in multiple languages
Enabled utilization of spares across plants

RESULTS

Savings to the tune of $1.2 M in inventory costs

Download this Case Study