Client:
Global transportation company
Industry:
Manufacturing services
Business need addressed:
To improve the overall inventory management of a spare parts business suffering from high aging, high ordering costs, and frequent stock-outs
Genpact solution:
- Reimagined supply chain processes with focused use of technology and Data-to-Action AnalyticsSM
- Validated inventory turns and customer service versus the client’s peers using external benchmarking
- In-depth value stream mapping of the client’s as-is inventory planning and process
- Reengineered process for planning and procurement
- Set up visibility management and control processes
- Leveraged Genpact’s proprietary Inventory Optimizer solution as a bolt-on with a three-phased roll-out plan across proof-of-concept (POC), beta, and full-scale roll-outs
Business impact:
- Improved customer service levels with 85% reduction in stock-outs
- 30% reduction in aged inventory
- 30% reduction in ordering cost
- 25% productivity released toward customer service activities
Business challenge
Due to poor customer service and sub-optimal inventory management, the client faced frequent stock-outs of on-hand inventory, which resulted in high penalty charges and impacted their cash flow and bottom line negatively. The client followed a highly decentralized regional supply chain structure to manage these complexities and maximize customer service.
This configuration made the procurement process inefficient and costly. Insufficient inventory monitoring and control measures were also a problem, as decentralization led to a lack of planning, resulting in high aged inventory. Localized min-max was the main inventory management tactic, which prevented proper handling of seasonality and regional variations.
The client relied on a mainframe-based ERP system to manage inventory and procurement. Master data accuracy issues regarding key inventory parameters, such as lead times and standard costs, led to higher buffer stocks. The IT system lacked sufficient forecasting and optimization capability, pushing them into ad-hoc excel sheets.
Genpact solution
The Data-to-Action AnalyticsSM loop enables companies to generate insight and drive management visibility (the Data-to-Insight process) and then subsequently embed the insight to enable specific, granular actions that affect company effectiveness (Insight-to-Action), such that it can be used at scale, to drive execution. The end-to-end process view across Data-to-Insight and Insight-to-Action can help design effective analytics solutions and provide targeted change management to embed them into business processes.
Provide visibility and steer effectiveness
- Data collection, data extraction, transformation, and loading/staging extract-transform-load (ETL) process to establish accurate data requirements, along with operational definitions was implemented. Seamless integration with an existing mainframe was ensured through an automated bi-directional ETL process.
- Visibility management through set up and production of standardized reports for monitoring and controlling on-hand inventory at the plant, planner, and part levels. This was done to track excess inventory, inventory aging, part lead time variance, and monitoring performance
- Inventory classification through multidimensional inventory segmentation to implement a three-tiered customized replenishment strategy (forecast-based, re-order point (ROP)/safety stock (SS), and min-max)
- Inventory optimization by implementing ‘Inventory optimizer’, Genpact’s proprietary cloud-based solution for demand forecasting, inventory optimization, and visibility management
Improve execution practices
Setting up smarter processes for demand planning and inventory management, i.e., a framework for problem identification, performance baseline, and improvement:
- Centralized planning and procurement for top 15% stock keeping units (SKUs) with accounting for 80% of monthly volumes
- Demand forecasting, engine that helped the business capture seasonality and regional variations and carry out exhaustive exception management
- Inventory management with supply chain planners, buyers, and warehouse managers to identify excess inventory and balance service levels and on-hand inventory at the parts level
Continuous learning
The resulting intelligent supply chain and inventory management operations have the capability to sense and respond to changes in the operating conditions. Continuous improvement initiatives based on the learnings from experience led to further refined analytical methods:
- Increase the number of centrally managed SKUs from 15% to 50% of the SKU base
- Manage complex supply chain planning problems with heuristics-driven inventory planning and policy setting for SKUs where common statistical models fail, such as SKUs with intermittent demand
- Warehouse space/bin size constraints modeled into inventory planning parameters like minimum order quantity (MOQ) and ROP
- Tolerance limits to be defined to reduce the number of small changes suggested
Business impact
Financial impact
- Improved customer service levels with 85% reduction in stock-outs
- 30% reduction in aged inventory
- 30% reduction in ordering costs
- 25% productivity released toward customer service activities, i.e., reducing the administrative time of the field staff for more “face time” with customers
Operational performance
- Standardized processes across other global equipment plants, leading to higher ROI from technology/ERP investment
- Enabled better collaboration with the client’s supply chain partners
- Increased visibility into obsolete, non-moving, and slow-moving inventory
Customer testimonial
“This is great progress and is evidence of a very professional team. Your efforts are greatly appreciated by many business locations. So beyond the stock-out savings, this is a big win from a shop efficiency perspective. Keep up the attention to details that you are performing every day, great work.” - Executive, Pricing