One of the largest global tools manufacturers in North America faced challenges with their spare parts business. Parts were frequently out of stock at stores which caused problems with customer loyalty and retention. It also tied up working capital.
The spare parts availability and fill rates problems were due to obsolete forecasting and planning. This had also started affecting contractual arrangements with vendors and required too many manual processes.
The tool manufacturer sought a demand planning and forecasting solution that would:
- Maximize spare parts availability
- Improve fill rates
- Improve customer loyalty and satisfaction
- Reduce inventory levels
- Minimize obsolescence
- Decrease write-offs and increase working capital
- Reduce manual processes
- Reduce order lead times
- Decrease costs of expediting
- Generate business cases to support buy versus internal transfer decisions
The tool company engaged CT Global Solutions to build a forecasting and demand planning solution built on SAS DDPO. The solution has three core capabilities: Demand Planning and Forecasting; Inventory Optimization; Order Generation and Order Management.
Features of CT GLobal’s SAS DDPO solution:
- Multi-echelon forecasting for product families, SKUs, and all location combinations.
- Automated statistical forecasting and modeling for the most accurate forecast.
- Flexible hierarchical capabilities to view and create forecasts at any level of region, country, distribution center, SKU, and more.
- Selects a champion model from 64 possible models.
- Conducts seasonality and trend analysis by location and region.
- Built-in models detect seasonal patterns by product/groups and by location/groups.
- Accounts for substitutes, supercessions, replacements, phase-in/out and lost sales.
- Allows users to create “what if” demand scenarios and update forecasts.
- Consensus planning using a collaborative method integrating statistical baselines with business judgment.
- Reports & key performance indicators (KPI’s) for key users
Users can also query a service parts inventory optimization module and receive fact-based answers to questions like:
- What is the optimal inventory range by SKU and location to achieve a specific service level?
- Which items have crossed policy thresholds and should be reordered?
- How much inventory should be ordered and when? (based on current inventory, demand, service levels, network, and other criteria)
CT GLobal’s SAS DDPO solution significantly improved forecast accuracy and consensus planning, reduced inventory levels and handling costs, reduced expediting costs inventory, reduced manual efforts, achieved a 22% reduction in inventory and obsolescence, a 4% improvement in service levels, and attained the target fill rates and service levels. The company can now visualize global stock levels, rebalance inventory and optimize inventories for each item at each retail location or distribution center. Projected savings over 4 years is estimated at more than $60M.
SAS Demand Planning and optimization is now SAS Intelligent Planning Suite.