Course Introduction
Supply Chain Analytics and Inventory Intelligence Training Course provides a practical and comprehensive framework for using data, analytics, forecasting, and business intelligence to improve supply chain performance. The course focuses on transforming procurement, inventory, warehouse, sales, supplier, logistics, and demand data into actionable insights that support better planning, replenishment, service levels, and working-capital decisions across modern supply networks.
This training develops the analytical capabilities required to understand inventory behavior across products, locations, suppliers, warehouses, channels, and time periods. Participants learn how to structure supply chain datasets, establish meaningful KPIs, identify data-quality issues, analyze inventory movements, and distinguish between demand signals, supply constraints, excess stock, shortages, and operational exceptions. Modern inventory analytics environments can combine on-hand, supply, demand, scheduled receipts, gross requirements, and projected balances to provide a more complete view of inventory position.
A major component of the course is demand and inventory forecasting. Participants explore historical demand patterns, seasonality, trends, forecast accuracy, uncertainty, and the relationship between predicted demand and future inventory requirements. Current Business Central inventory forecasting capabilities, for example, project future inventory quantities using historical data and allow forecasting parameters such as forecast length, seasonality, period, and confidence interval to be adjusted in Power BI.
The course also develops practical inventory intelligence techniques including ABC classification, inventory segmentation, safety-stock analysis, reorder-point analysis, stockout monitoring, excess and obsolete inventory analysis, inventory turnover, days of supply, service-level analysis, and replenishment prioritization. ABC analysis can classify items according to sales contribution and help organizations focus inventory resources on higher-value items while identifying products where different stocking policies may be appropriate.
Participants further learn how to connect supply chain analytics with procurement, warehouse operations, logistics, production planning, and commercial demand. They examine supplier performance, lead-time variability, purchase-order behavior, inventory allocation, warehouse utilization, stock transfers, and supply-demand imbalances. Inventory analytics can be examined across locations, items, document types, bins, lots, and serial numbers, creating opportunities for more detailed operational monitoring and exception management.
By the end of the five-day program, participants will be able to design practical supply chain analytics solutions that support inventory visibility, demand planning, replenishment, supplier management, operational performance, and strategic decision-making. The course emphasizes hands-on analytical thinking, KPI design, forecasting interpretation, dashboard development, scenario analysis, and an integrated capstone exercise that connects supply chain data to measurable business outcomes.
Duration
5 days
Who Should Attend
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Supply chain analysts responsible for monitoring operational performance, inventory movements, and supply-demand relationships.
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Inventory managers seeking analytical methods for controlling stock levels, availability, excess inventory, and working capital.
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Demand planners responsible for forecasting customer requirements and translating demand signals into planning decisions.
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Supply planners involved in replenishment, material planning, inventory allocation, and supply-demand balancing.
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Procurement professionals analyzing supplier performance, purchasing patterns, lead times, and procurement effectiveness.
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Warehouse managers who need better visibility into inventory quantities, locations, movements, utilization, and operational exceptions.
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Logistics and distribution professionals analyzing transportation, fulfillment, stock movements, and service-level performance.
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Operations managers responsible for improving supply chain efficiency, inventory productivity, and operational decision-making.
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Business intelligence professionals developing supply chain dashboards, reports, and analytical models.
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Data analysts working with ERP, warehouse management, procurement, sales, and inventory datasets.
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Finance and working-capital professionals analyzing inventory investment, carrying costs, turnover, and inventory-related financial exposure.
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Supply chain consultants and transformation professionals designing data-driven planning and inventory improvement initiatives.
Course Objectives
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Develop a structured understanding of supply chain analytics and apply analytical frameworks to procurement, inventory, demand, logistics, warehouse, and operational datasets.
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Build reliable supply chain KPI frameworks covering inventory turnover, days of supply, stock availability, service levels, forecast accuracy, lead times, and replenishment performance.
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Analyze historical demand and inventory movements to identify trends, seasonality, volatility, abnormal behavior, and emerging supply-demand imbalances.
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Apply inventory segmentation techniques such as ABC classification and value-based prioritization to differentiate stocking policies and management attention.
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Develop practical approaches for calculating and interpreting reorder points, safety stock, inventory coverage, replenishment quantities, and stockout risk.
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Evaluate demand forecasts using appropriate accuracy measures and interpret uncertainty so that planning decisions account for forecast limitations and variability.
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Analyze supplier and procurement performance using purchasing history, lead-time behavior, delivery reliability, order quantities, price changes, and supplier-level performance indicators.
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Design interactive supply chain dashboards that allow managers to monitor inventory health, demand trends, supply availability, warehouse performance, and critical exceptions.
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Apply scenario analysis and analytical modeling to evaluate alternative replenishment strategies, inventory policies, allocation decisions, and operational constraints.
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Integrate supply chain analytics into a practical inventory intelligence framework that supports continuous improvement, cross-functional collaboration, and evidence-based decision-making.
Comprehensive Course Outline
Module 1: Supply Chain Analytics and Inventory Intelligence Foundations
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Understanding the supply chain data ecosystem across procurement, suppliers, inventory, warehouses, sales, production, transportation, customers, and financial systems.
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Defining inventory intelligence, supply chain visibility, analytical maturity, operational analytics, strategic analytics, and data-driven supply chain decision-making.
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Mapping the relationships between demand, supply, inventory position, lead time, service levels, working capital, operational costs, and customer fulfillment.
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Establishing analytical objectives, business questions, stakeholder requirements, data requirements, governance principles, and measurable supply chain improvement targets.
Module 2: Supply Chain Data Architecture and Data Preparation
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Designing analytical datasets that integrate product, inventory, transaction, purchase order, sales order, supplier, location, warehouse, and calendar information.
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Preparing transactional supply chain data by addressing missing values, duplicates, inconsistent product identifiers, abnormal transactions, and unreliable timestamps.
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Building analytical dimensions and measures for products, suppliers, locations, inventory movements, purchase transactions, customer demand, and supply events.
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Creating data-quality validation procedures that improve consistency, traceability, reconciliation, refresh reliability, and confidence in supply chain analytics.
Module 3: Inventory KPIs and Performance Analytics
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Calculating and interpreting inventory turnover, inventory days, stock value, inventory accuracy, availability, service level, fill rate, and stockout indicators.
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Analyzing on-hand inventory, scheduled receipts, gross requirements, projected available balances, purchase orders, production requirements, and inventory movements.
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Developing KPI hierarchies that connect executive supply chain indicators with operational measures for procurement, warehouses, planning, and inventory teams.
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Identifying inventory performance gaps through variance analysis, trend analysis, exception analysis, location comparisons, product comparisons, and time-based performance reviews.
Module 4: Demand Analytics and Supply-Demand Intelligence
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Analyzing historical demand by product, customer, location, channel, region, time period, and other business dimensions to identify meaningful demand patterns.
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Separating trend, seasonality, volatility, promotions, unusual events, structural changes, and other demand drivers that influence inventory requirements.
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Comparing demand forecasts with supply forecasts and inventory positions to identify potential shortages, surpluses, capacity constraints, and replenishment risks.
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Building analytical workflows that connect demand forecasts with supply planning and inventory decisions, including forecast-driven planning and planned-order analysis.
Module 5: Inventory Segmentation, ABC Analysis and Stock Classification
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Applying ABC analysis to classify inventory according to sales contribution, value, movement, or other business criteria and establish differentiated management priorities.
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Combining ABC classification with demand variability, criticality, lead time, profitability, and service requirements to create multidimensional inventory segmentation.
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Identifying high-value, slow-moving, obsolete, excess, dormant, fast-moving, and stockout-prone items using analytical classification techniques.
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Translating inventory segmentation results into differentiated replenishment rules, review frequencies, service targets, purchasing priorities, and working-capital strategies.
Module 6: Inventory Forecasting, Replenishment and Safety Stock
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Developing inventory forecasts using historical data, demand patterns, seasonality, forecast horizons, and appropriate statistical or business forecasting techniques.
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Understanding safety stock concepts, demand variability, lead-time variability, service-level requirements, reorder points, and replenishment thresholds.
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Evaluating forecast accuracy using appropriate metrics and comparing forecast results with actual demand to identify systematic planning errors.
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Connecting inventory forecasts to procurement and operational planning so that anticipated changes in stock levels can inform replenishment and resource decisions.
Module 7: Procurement, Supplier and Lead-Time Analytics
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Analyzing supplier performance using purchase-order history, delivery reliability, lead-time variation, quantity adherence, pricing behavior, and purchasing frequency.
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Measuring supplier lead-time variability and examining its effect on safety stock, replenishment reliability, production continuity, and customer service performance.
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Developing supplier scorecards that combine delivery, quality, cost, responsiveness, availability, and risk indicators into actionable procurement intelligence.
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Identifying procurement opportunities through supplier comparisons, order-pattern analysis, purchase consolidation, exception detection, and inventory-cost analysis.
Module 8: Warehouse, Distribution and Inventory Flow Analytics
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Analyzing inventory by warehouse, location, bin, lot, serial number, movement type, and operational status to identify flow constraints and availability problems.
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Evaluating warehouse stock distribution and identifying opportunities for inventory transfers, replenishment, slotting improvements, and location-level balancing.
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Monitoring warehouse activities such as picks, put-aways, adjustments, available quantities, and bin-level inventory conditions through operational analytics.
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Connecting warehouse analytics with broader supply chain performance to identify how inventory positioning, fulfillment operations, and distribution decisions affect service levels.
Module 9: Supply Chain Dashboards, Visualization and Decision Intelligence
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Designing executive and operational dashboards that combine inventory position, demand, supply, forecasting, procurement, warehouse, and service-level indicators.
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Creating interactive analytical views that allow users to drill from enterprise-level supply chain performance into products, locations, suppliers, warehouses, and individual exceptions.
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Developing exception-based dashboards that highlight stockouts, overstock, slow-moving inventory, supply shortages, forecast deviations, and critical replenishment requirements.
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Applying visualization and storytelling principles to transform complex supply chain datasets into concise management insights and clearly defined operational actions.
Module 10: Advanced Inventory Intelligence, Scenario Analysis and Capstone
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Developing supply chain scenarios to evaluate alternative safety-stock levels, replenishment policies, supplier lead times, demand changes, allocation strategies, and inventory constraints.
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Applying predictive and prescriptive analytical thinking to identify potential inventory risks, estimate future requirements, and evaluate alternative operational responses.
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Building an integrated inventory intelligence solution that combines data preparation, KPI analysis, forecasting, segmentation, replenishment analysis, supplier analytics, and dashboard reporting.
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Completing a practical capstone project in which participants analyze a realistic supply chain dataset, identify inventory and supply-demand issues, develop analytical recommendations, and present decision-ready findings.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808
Training Venue
The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.
Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Upskill certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808
Terms of Payment:
Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.
