First to market, PTC’s Advanced Inventory Optimization is the most effective inventory optimization software available today, and it keeps getting better. Acting on lessons learned from the largest global install base of service parts management customers, PTC continuously enhances our software’s ability to meet customers’ requirements. Advanced Inventory Optimization goes beyond the spare parts inventory planning methods supported by other solutions by taking into account:
- Parts costs, usage rates, criticality, procurement, and repair lead times.
- Multiple location coordination and transit times.
- Differentiated customer requirements and service contracts.
- An intelligent blend of proactive and reactive planning.
Our best-in-class Inventory Optimization capabilities reduce inventory investment by 30% or more and ensure the highest service return from every dollar invested in inventory by:
- Determining optimal service part stocking levels.
- Creating stocking plans designed to support service contracts.
- Honoring business rules and practical constraints.
- Ensuring an actionable, stable plan.
PTC clients experience inventory cost reductions of 10-35% and improve part availability by 10-25%- better than the industry average. Customers like Metso and Pratt & Whitney have seen substantial improvements in planning using PTC’s industry-leading inventory optimization. Click on the company names to learn more.
Multi-Echelon Inventory Optimization
PTC’s Multi-Echelon Inventory Optimization (MEO) provides a network fill rate approach to reach a trade-off between parts and locations by understanding the parts costs, demand and combined, most effective lead times to determine where to invest the next piece of inventory in the network. This marginal analysis approach enables you to achieve target network fill rates while ensuring the correct mix of parts. This technique has proven to be effective in reducing inventories by up to 30% while simultaneously increasing service levels. MEO ensures the most efficient service performance possible at the lowest cost by:
- Planning across multiple levels, locations and parts, to provide the lowest-possible inventory for a target service level.
- Optimizing the entire distribution network to benefit all subordinate locations without compromising their ability to meet demand.
- Providing extensive capability to optimize a service strategy differentiated by products, geography, customers and part characteristics.
- Combining service level targets with new buy budget and investment targets to generate optimal stocking plans
- Enabling scenario-based optimization supports easy “what-if” analyses that simulate multiple service strategies and operating levels.
- Ensuring configurable threshold base reviews and acceptance of inventory plans.
Harness the tradeoffs in your supply chain to meet service levels and manage costs.
Making the Trade: Service Parts Management Across Echelons
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PTC’s Multi-Indenture, Multi-Echelon
PTC’s Multi-Indenture, Multi-Echelon (MIME) capability takes the MEO trade-off approach for parts and locations and adds a further level of granularity to ensure asset availability rates. This is important because maintaining good fill rates across your parts population does not ensure good availability of your assets or systems. For customers who need to ensure that an availability-based contract is met and that the asset under contract consistently meets the contracted uptime rates, MIME provides the optimal stocking policy (by location, by contract, by customer) to support all the specific systems under service to ensure a set level of uptime or availability by:
- Enabling a further level of granularity to ensure asset availability rates - i.e. the additional trade-off between core parts and sub-component parts needed to ensure the turnaround time for core components.
- Supporting rotable pool optimization with flexible global and regional pools, pool-based constraints, and service targets.
- Providing analytics and modeling for system or fleet-based activity, budgeting and planning.