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Production Planning in Service Parts Management

Production Planning in Service Parts Management

$250.00
How you learn:
Self-paced • Lifetime updates
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Course access is prepared after purchase and delivered via email
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Toolkit Included:
Includes a practical, ready-to-use toolkit containing implementation templates, worksheets, checklists, and decision-support materials used to accelerate real-world application and reduce setup time.
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What does the Production Planning in Service Parts Management course cover?

Production Planning in Service Parts Management is covered here in 8 modules: Demand Forecasting for Service Parts, Inventory Stratification and Classification, Service Level and Stocking Policy Design and 5 more. The outline lists 48 specific topics, opening with selecting between intermittent demand models (Croston, SBA) and machine learning approaches based on part history sparsity and SKU criticality.

How do you approach Production Planning in Service Parts Management step by step?

The work is sequenced in 8 stages. It starts with Demand Forecasting for Service Parts, moves through Inventory Stratification and Classification and Service Level and Stocking Policy Design, and ends at Systems and Data Governance. Each stage carries its own topic list, so the sequence is followed rather than summarised.

What is in Module 1 of the Production Planning in Service Parts Management course?

Module 1 is Demand Forecasting for Service Parts. It works through selecting between intermittent demand models (Croston, SBA) and machine learning approaches based on part history sparsity and SKU criticality., adjusting forecast parameters for parts affected by product end-of-life or sudden warranty campaign announcements., integrating field failure data from service reports to recalibrate failure rate assumptions in forecasting engines. and 3 more.

How is the Production Planning in Service Parts Management course delivered?

The Production Planning in Service Parts Management course is fully self-paced with immediate online access after enrolment. Access does not expire and future updates are included at no cost. It can be taken on any device, and a certificate of completion is issued by The Art of Service when you finish.

How much does the Production Planning in Service Parts Management course cost?

The Production Planning in Service Parts Management course is $250 as a one time payment. There is no subscription, no per seat licence and no hidden fee. Enrolment carries a 30 day satisfied or refunded guarantee, so it can be assessed in full before you commit.

Closely related courses: Parts Planning in Service Parts Management, Material Planning in Service Parts Management, Parts Planning in Service Integration and Management Kit.

More answers: what you get with every course, refund policy, all help answers.

This curriculum spans the technical and operational complexity of a multi-phase service parts planning initiative, comparable to an enterprise’s internal program for redesigning inventory policy across global service networks.

Module 1: Demand Forecasting for Service Parts

  • Selecting between intermittent demand models (Croston, SBA) and machine learning approaches based on part history sparsity and SKU criticality.
  • Adjusting forecast parameters for parts affected by product end-of-life or sudden warranty campaign announcements.
  • Integrating field failure data from service reports to recalibrate failure rate assumptions in forecasting engines.
  • Handling demand spikes caused by external factors such as weather events or regulatory recalls without overfitting models.
  • Defining statistical safety stock inputs while accounting for forecast bias observed in historical forecast vs. actual consumption reports.
  • Coordinating forecast updates across regions when shared parts support global equipment fleets with differing usage profiles.

Module 2: Inventory Stratification and Classification

  • Implementing multi-dimensional ABC-XYZ classification combining value, demand variability, and lead time instead of revenue-based A/B/C alone.
  • Revising part criticality rankings when OEMs discontinue support for legacy equipment models.
  • Assigning stocking policies based on operational downtime cost, not just part cost, for high-impact service parts.
  • Managing classification exceptions for low-turn parts that are mission-critical in healthcare or aviation settings.
  • Aligning inventory segmentation with warehouse slotting and picking strategies to reduce fulfillment latency.
  • Updating classification rules quarterly to reflect shifts in service contract portfolios and product retirements.

Module 3: Service Level and Stocking Policy Design

  • Setting differentiated fill rate targets for parts based on equipment criticality, contract SLAs, and customer tier.
  • Calculating optimal cycle service levels that balance stockout costs against carrying costs for long-lead imported parts.
  • Defining multi-echelon stocking policies for central depots, regional warehouses, and field vans with lateral transshipment rules.
  • Adjusting reorder points when suppliers extend lead times due to geopolitical disruptions or raw material shortages.
  • Managing push vs. pull inventory deployment for pre-positioning parts ahead of seasonal demand peaks.
  • Validating policy effectiveness through backtesting against historical stockout and expediting events.

Module 4: Multi-Echelon Inventory Optimization

  • Configuring demand pooling logic across warehouses to reduce safety stock while maintaining local availability.
  • Implementing stock transfer protocols between regional hubs during localized demand surges or supply delays.
  • Modeling the impact of centralizing slow-moving parts on overall system availability and response time.
  • Integrating repair turnaround time into echelon-level inventory positioning for reusable service parts.
  • Optimizing push quantities from central to regional facilities based on forecasted regional workload and failure trends.
  • Reconciling system-recommended positions with warehouse capacity constraints and transportation cost thresholds.

Module 5: Supplier and Procurement Integration

  • Negotiating consignment or vendor-managed inventory (VMI) agreements for high-cost, low-turnover parts to reduce ownership risk.
  • Establishing minimum order quantities (MOQs) and batch size rules that align with consumption rates and storage limitations.
  • Managing procurement lead time variability by incorporating supplier performance data into safety stock calculations.
  • Coordinating with suppliers on end-of-life (EOL) notifications and last-time buy decisions for obsolete parts.
  • Integrating supplier capacity constraints into replenishment planning during global component shortages.
  • Validating supplier lead time updates in the planning system after logistics network changes or port disruptions.

Module 6: Obsolescence and Lifecycle Management

  • Triggering last-time buy analysis when product phase-out dates are confirmed by engineering or product management.
  • Calculating retirement forecasts for parts supporting equipment past its mean time between failures (MTBF).
  • Transferring excess stock of retiring parts to service partners or secondary markets to avoid write-offs.
  • Updating stocking policies for parts transitioning from warranty to post-warranty service phases.
  • Coordinating with finance on inventory reserve provisions for parts with diminishing demand trajectories.
  • Archiving planning parameters for discontinued parts while retaining traceability for regulatory audits.

Module 7: Performance Monitoring and Continuous Improvement

  • Designing KPI dashboards that track inventory turnover, stockout frequency, and expediting costs by part category.
  • Conducting root cause analysis on recurring backorders to identify planning parameter misalignments.
  • Validating forecast accuracy by exception reporting, focusing on parts with MAPE above operational thresholds.
  • Revising safety stock parameters after process changes such as new supplier onboarding or warehouse consolidation.
  • Aligning planning cycle frequency (e.g., weekly vs. monthly runs) with demand volatility and supply lead time stability.
  • Integrating feedback from field technicians on part substitution effectiveness into master data management processes.

Module 8: Systems and Data Governance

  • Enforcing data quality rules for lead time, MOQ, and unit cost fields in the ERP to prevent flawed replenishment outputs.
  • Mapping part master attributes to planning logic, such as identifying repairable vs. disposable parts in the BOM.
  • Managing system integration between ERP, EAM, and advanced planning tools to ensure synchronized demand signals.
  • Defining ownership for maintaining planning parameters across supply chain, service operations, and IT teams.
  • Implementing change control procedures for modifying service level targets or classification rules.
  • Archiving historical planning data to support audit requirements and long-term trend analysis.
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