Demand Planning and Forecasting

Forecasting spare parts demand is critical for meeting service and customer requirements. Accurately predicting parts demand, especially when intermittent and unpredictable, is imperative to avoid equipment downtime, high operational costs and poor customer service, all of which result in lost revenue.

PTC Service Parts Management offers the most sophisticated demand planning and forecasting capabilities on the market, addressing low-volume and sporadic demand, new product introduction and end-of-life, and a rapidly changing install base with frequent engineering changes.

An extensively tested, field-proven forecasting approach

PTC Service Parts Management creates the most accurate forecast possible for every level of the service supply network by:

  • Using statistical algorithms, installed-base data, causal factors and maintenance requirements.
  • Providing sophisticated causal forecasting scenarios and forecasting specific workflows.
  • Addressing highly sporadic, intermittent and low volume demand.
  • Employing an automated best-fit process specifically designed for service parts that chooses the appropriate method to minimize forecasting errors.
  • Providing the ability to incorporate multiple causal factors e.g. operating hours, power cycles, adaptive failure rate/MTBF estimation and use of time phased failure rates.
  • Including maintenance event-based forecasting and life-limited part forecasting.
  • Providing a graphical view of forecast information and performing what-if simulations on different forecasting techniques.
  • Enabling the categorization and segmentation of parts based on demand patterns to allow for specific forecast techniques.
  • Utilizing data directly from connected assets to forecast and optimize service inventory.

Advanced demand planning and forecasting significantly impacts service delivery through:

  • Accurate forecasts that incorporate product configurations and respond rapidly to changes.
  • Reduced component inventory by optimizing stocking levels based on part attributes and supply times.
  • Faster response time through fewer stock outs and pooling benefits from centralized holdings.
  • Reduced downtime and faster return to service time based on quicker response and higher service levels.
  • More productive planners that can focus on strategic and proactive planning

Learn how Metso realized EUR 11.6 million in inventory cost reductions and an 18% increase on inventory turns.

Metso Implements SPM in the Cloud

Metso Implements SPM in the Cloud

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