Description

This curriculum spans the design and operational execution of inventory optimization programs comparable to multi-workshop advisory engagements, covering data integration, policy configuration, and cross-functional alignment across procurement, supply chain, and finance functions.

Module 1: Demand Forecasting and Data Integration

Selecting between statistical forecasting models (e.g., exponential smoothing, ARIMA) based on historical data availability and product lifecycle stage.
Integrating ERP demand data with external signals such as market trends, promotions, and supply chain disruptions into forecasting engines.
Establishing data governance rules for master data consistency across SKUs, locations, and organizational units.
Defining forecast granularity (e.g., SKU-location-week) and balancing accuracy with computational load in enterprise systems.
Implementing forecast error tracking mechanisms (e.g., MAPE, WMAPE) to trigger model recalibration cycles.
Coordinating forecast ownership between procurement, sales, and finance to resolve conflicting volume assumptions.

Module 2: Inventory Classification and Segmentation

Applying ABC analysis using annual consumption value while adjusting thresholds for strategic or risk-critical items.
Extending classification with multi-dimensional frameworks (e.g., ABC-XYZ) to account for demand variability and lead time.
Assigning service level targets per segment based on financial impact and customer contract obligations.
Handling classification exceptions for low-volume, high-criticality items (e.g., safety spares) that defy standard rules.
Automating classification updates in response to shifting demand patterns or product phase-outs.
Aligning inventory segmentation with procurement sourcing strategies (e.g., JIT for A-items, bulk for C-items).

Module 3: Safety Stock Modeling and Service Level Design

Choosing between service-level-driven (e.g., cycle service level) and cost-optimized safety stock calculations.
Estimating lead time variability using historical supplier performance data, including transit and customs delays.
Adjusting safety stock for intermittent demand using methods like bootstrapping or Croston’s model.
Allocating safety stock across a multi-echelon network (e.g., central warehouse vs. regional depots).
Validating model outputs against actual stockout frequency and expediting costs.
Revising safety stock policies during supply chain disruptions or supplier transitions.

Module 4: Replenishment Strategy and Policy Configuration

Selecting reorder point (ROP) vs. periodic review (P, s-S) policies based on supplier ordering constraints and demand stability.
Configuring min/max levels in ERP systems with dynamic adjustments for seasonality and promotions.
Implementing vendor-managed inventory (VMI) agreements with clear SLAs for restocking frequency and responsibility.
Managing lot-sizing trade-offs between ordering costs and carrying costs, including EOQ adjustments for volume discounts.
Defining reorder triggers for consignment inventory and tracking consumption for invoicing accuracy.
Integrating replenishment logic with MRP parameters while avoiding system-induced bullwhip effects.

Module 5: Supplier Collaboration and Lead Time Management

Negotiating lead time reduction clauses in contracts and measuring supplier adherence through KPI dashboards.
Mapping supplier lead time components (production, transit, customs) to identify improvement opportunities.
Implementing shared visibility tools (e.g., supplier portals) for real-time order and inventory status updates.
Coordinating forecast sharing with key suppliers while protecting competitive data.
Establishing buffer strategies for suppliers with high lead time variability or geopolitical risk exposure.
Managing dual sourcing decisions based on lead time reliability and total cost of ownership.

Module 6: Obsolescence and Excess Inventory Control

Defining obsolescence triggers based on product lifecycle milestones, such as end-of-life notices or design changes.
Calculating write-down provisions for excess stock using net realizable value (NRV) assessments.
Implementing cross-functional disposition processes for excess inventory (e.g., reassignment, liquidation, donation).
Integrating phase-out planning into new product introduction (NPI) workflows to avoid overlap.
Tracking inventory aging reports and setting escalation paths for stale stock beyond threshold periods.
Adjusting procurement approvals for sunset products to prevent inadvertent reordering.

Module 7: Technology Integration and System Configuration

Configuring inventory optimization modules in ERP (e.g., SAP IBP, Oracle SCM) to reflect actual business constraints.
Designing data pipelines between procurement systems, demand planning tools, and warehouse management systems.
Validating algorithm outputs through back-testing against historical inventory performance.
Setting user roles and approval workflows for parameter changes (e.g., service levels, lead times).
Implementing alerts for out-of-policy inventory positions and automating root cause tagging.
Managing version control and change logs for inventory models during system upgrades or organizational changes.

Module 8: Performance Monitoring and Continuous Improvement

Defining KPIs such as inventory turnover, stockout rate, and carrying cost as part of procurement scorecards.
Conducting root cause analysis on inventory variances between plan and actual consumption.
Establishing cadence for inventory policy reviews aligned with business planning cycles.
Using scenario modeling to assess impact of demand shifts, supply constraints, or network changes.
Integrating audit findings into process updates, particularly around compliance with financial reporting standards.
Facilitating cross-functional workshops to align procurement, logistics, and finance on inventory trade-offs.