Description

This curriculum spans the breadth and rigor of a multi-workshop operational diagnostic, addressing data, process, and system interdependencies across supply chain functions as typically encountered in large-scale internal capability assessments.

Module 1: Defining Scope and Stakeholder Alignment

Determine which tiers of the supply chain (e.g., Tier 1 suppliers to end customers) require inclusion based on regulatory exposure and operational criticality.
Negotiate access to supplier data systems while respecting confidentiality agreements and intellectual property boundaries.
Map decision rights across procurement, logistics, manufacturing, and sales to identify conflicting objectives in inventory policy.
Establish escalation protocols for discrepancies between regional operations and corporate supply chain strategy.
Document legacy system dependencies that constrain data availability for cross-functional analysis.
Identify key performance indicators (KPIs) that align with both financial targets and operational feasibility.
Resolve conflicts between demand planning assumptions and sales forecast inputs during consensus forecasting sessions.
Define thresholds for materiality when selecting SKUs for deep-dive analysis in multi-product environments.

Module 2: Data Inventory and System Landscape Assessment

Inventory all ERP, WMS, TMS, and PLM instances across business units and assess data schema compatibility.
Classify data sources by reliability, update frequency, and ownership (e.g., supplier-managed vs. internal).
Identify shadow IT systems used for logistics tracking or inventory reconciliation outside central platforms.
Document API limitations in legacy systems that prevent real-time data extraction for analytics.
Assess data lineage for critical metrics like on-time delivery rate to determine calculation consistency.
Map master data discrepancies (e.g., SKU numbering, location codes) across merged organizational units.
Evaluate the feasibility of retroactively cleaning historical data for trend analysis given storage constraints.
Determine whether batch processing schedules introduce latency in supply visibility reporting.

Module 3: Demand and Forecasting Process Evaluation

Analyze forecast accuracy by product category and horizon to isolate structural weaknesses in statistical models.
Review sales and operations planning (S&OP) meeting outputs to assess alignment between financial and supply plans.
Compare consensus forecast adjustments against actual demand to quantify bias introduced by commercial teams.
Assess the impact of promotional calendars on baseline forecast stability and model retraining frequency.
Identify instances where forecast overrides are applied without documented rationale or audit trail.
Evaluate the granularity of demand signals (e.g., POS data, channel shipments) used in forecasting models.
Determine whether new product introduction (NPI) forecasts rely on analogous product rollouts or qualitative inputs.
Measure forecast consumption logic accuracy in ATP (Available-to-Promise) systems during order promising.

Module 4: Supplier and Procurement Network Mapping

Classify suppliers by spend, risk exposure, and substitutability to prioritize due diligence efforts.
Validate supplier lead time data against actual inbound shipment performance over 12-month period.
Assess dual-sourcing status for critical components and document single-source dependencies.
Review purchase order acknowledgment and deviation rates to identify compliance gaps.
Map sub-tier supplier locations for high-risk materials to evaluate geopolitical exposure.
Quantify payment term mismatches between supplier contracts and actual cash flow cycles.
Identify consignment inventory agreements and assess their impact on inventory ownership reporting.
Evaluate the use of blanket orders versus discrete POs and their effect on demand signal clarity.

Module 5: Inventory Strategy and Stock Optimization

Classify inventory by role (cycle, safety, hedge, obsolete) and measure carrying cost implications.
Validate safety stock calculations against actual stockout events and service level targets.
Assess ABC/XYZ segmentation consistency across regions and its impact on replenishment logic.
Identify locations where minimum order quantities (MOQs) distort inventory profiles.
Measure obsolescence risk by analyzing write-off history and shelf-life constraints.
Evaluate the impact of batch tracking requirements on inventory pooling and allocation flexibility.
Compare target stock levels in ERP with those used in manual planning spreadsheets.
Determine whether transshipment policies between warehouses are formally defined and enforced.

Module 6: Logistics and Distribution Network Analysis

Map all inbound, outbound, and reverse logistics lanes with associated cost and transit time data.
Compare actual transportation costs against contracted rates to identify billing discrepancies.
Assess warehouse capacity utilization trends to determine need for network restructuring.
Review cross-dock efficiency metrics to evaluate throughput versus storage trade-offs.
Identify freight billing errors due to incorrect zone classifications or weight reporting.
Evaluate the use of 3PLs versus owned assets and their performance against SLAs.
Analyze dwell times at distribution centers to detect bottlenecks in order fulfillment.
Measure last-mile delivery performance by region and channel to isolate service gaps.

Module 7: Technology and Automation Readiness

Assess integration depth between planning systems and execution platforms (e.g., MES, TMS).
Identify manual data entry points in order-to-cash and procure-to-pay workflows.
Evaluate the reliability of RFID or barcode scanning in inventory accuracy processes.
Review change management logs for recent system upgrades affecting supply chain modules.
Measure system uptime and response times for critical planning applications during peak cycles.
Assess data latency between physical events (e.g., shipment dispatch) and system updates.
Determine whether automation initiatives (e.g., robotic picking) have achieved projected throughput gains.
Identify custom scripts or macros used to bridge system gaps and assess maintenance risk.

Module 8: Risk Exposure and Resilience Assessment

Map single points of failure in transportation routes and warehouse locations.
Review business continuity plans for critical suppliers and test recovery time objectives.
Quantify exposure to customs delays based on import volume and country of origin mix.
Assess insurance coverage adequacy for high-value inventory in transit and storage.
Measure historical recovery time from supply disruptions (e.g., port closures, supplier outages).
Identify regulatory compliance risks (e.g., REACH, FDA) tied to specific product flows.
Evaluate currency hedging strategies for procurement contracts in volatile markets.
Review cybersecurity controls for systems managing logistics and supplier data.

Module 9: Performance Measurement and Continuous Improvement

Validate the accuracy of fill rate calculations by comparing shipped vs. ordered quantities.
Assess cycle time metrics from order receipt to delivery across customer segments.
Identify KPIs that incentivize local optimization at the expense of network efficiency.
Review root cause analysis documentation for recurring supply chain exceptions.
Measure planning cycle duration and compare against forecast horizon requirements.
Track inventory turnover trends by product line and warehouse location.
Evaluate the frequency and impact of expedited shipments on logistics costs.
Assess the effectiveness of corrective actions from previous internal audits.