Supply Chain Analytics: Forecast, Optimization & Performance

Name: Supply Chain Analytics: Forecast, Optimization & Performance
Rating: 4.9 (60 reviews)

Supply Chain Analytics A-Z: Analytics for Operational Excellence, Decision Intelligence, Metrics, Modeling and Insights.

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Created byForce Academy

Last updated 5/2026

English

English [Auto],

What you'll learn

Understand the fundamentals of supply chain analytics and its role in modern business decision-making
Learn the supply chain analytics maturity model and data-driven operational strategies
Analyze supply chain data architecture, governance standards, and data quality principles
Measure supply chain performance using key operational and financial metrics
Map material and information flows across end-to-end supply chain networks
Evaluate order fulfillment performance and service reliability using industry-standard KPIs
Understand cash-to-cash cycle analysis and financial performance measurement
Apply benchmarking techniques to assess and improve supply chain efficiency
Measure forecast accuracy and identify forecasting bias using statistical metrics
Measure warehouse throughput, productivity, and operational efficiency
Analyze transportation strategies, freight consolidation, and mode selection
Perform total landed cost analysis for supply chain decision-making
Identify supply chain risks and perform scenario-based risk modeling
Evaluate sustainability metrics and carbon footprint analysis in supply chains
Develop analytical thinking for solving real-world supply chain challenges

Course content

6 sections • 23 lectures • 1h 27m total length

The Role of Analytics in Modern Supply Chain Management3:55
Leverage supply chain analytics to transform data into actionable insights, using descriptive and diagnostic techniques to synchronize the flows of products, information, and finances for end-to-end visibility.
The Supply Chain Analytics Maturity Model3:31
The supply chain analytics maturity model provides a roadmap from descriptive to cognitive analytics, guiding organizations to move from historical data and dashboards to predictive insights and prescriptive decisions.
Data Architecture and Intelligence for Supply Chains3:41
Design a robust data architecture that ingests, cleanses, and unifies diverse sources into a data warehouse or lake, enabling real-time supply chain intelligence through democratized, self-service analytics.
Data Quality and Governance Standards3:38

Mapping Material and Information Flows3:52
Measuring Reliability with Order Fulfillment Metrics3:45
Improve supply chain reliability with metrics like perfect order rate and OTIF to ensure on-time deliveries. Break cycle time into order entry, processing, picking, and transit to locate delays.
Financial Analytics and the Cash-to-Cash Cycle3:40
Benchmarking Supply Chain Performance3:50
Benchmark against internal, competitive, and functional leaders using the SCOR model (plan, source, make, deliver, return) to drive data-driven improvements, gap analysis, and continuous learning.

Qualitative and Quantitative Forecasting Methodologies4:00
Blend qualitative insights from Delphi method and market research with quantitative forecasting using moving averages and exponential smoothing to produce a consensus forecast for demand planning and supply chain performance.
Analyzing Trend, Seasonality, and Cyclicality in Demand3:40
Uncover demand drivers by analyzing trend, seasonality, and cyclicality through time series decomposition. Align production, labor, and inventory with these patterns to improve forecast accuracy and strategic planning.
Statistical Metrics for Forecast Accuracy and Bias3:51
Collaborative Planning and Forecasting Frameworks3:38

The Trade-off between Holding Costs and Service Levels3:43
Safety Stock Determination and Lead Time Variability3:43
Multi-Echelon Inventory Optimization Principles3:50
Apply multi-echelon inventory optimization to view the supply chain as an integrated network, using postponement and real-time demand signals to minimize total inventory while maximizing service levels.
Measuring Warehouse Throughput and Efficiency3:43
Measure warehouse throughput as the volume of units received, put away, picked, and shipped to reveal bottlenecks and drive continuous improvement through labor productivity, space utilization, and inventory accuracy.

Strategic Network Design and Facility Location Factors4:08
Design strategic supply chain networks by balancing costs with demand forecasts to locate near key customers and suppliers, using center of gravity modeling and geospatial analytics to optimize coordinates.
Total Landed Cost Analysis Framework3:44
Assess the total landed cost framework to uncover hidden expenses beyond unit price, including ocean freight, duties, taxes, and inventory carrying costs, to optimize global procurement profitability.
Mode Selection and Freight Consolidation Strategies3:52
Select transport mode by balancing speed, cost, reliability, and value-to-weight ratio, and use freight consolidation and intermodal strategies with a transportation management system and real-time data analytics to cut costs.
Routing and Scheduling Optimization Concepts3:41
Optimize routing and scheduling to minimize total distance and maximize vehicle utilization while honoring capacities, driver hours, and delivery windows. Use dynamic rerouting to reduce total cost to serve.

Requirements

No prior experience in supply chain analytics is required
A willingness to learn data-driven decision-making concepts
Interest in supply chain management, logistics, operations, or business analytics

Description

|| Unofficial Course ||

This course contains the use of Artificial Intelligence.

In today’s fast-changing global business environment, supply chains have become more complex, interconnected, and data-driven than ever before. Organizations across industries rely on analytics to improve efficiency, reduce costs, enhance customer satisfaction, and make smarter strategic decisions. This course is designed to provide you with a complete and practical understanding of supply chain analytics, equipping you with the knowledge and analytical frameworks needed to transform supply chain data into actionable business intelligence.

This comprehensive course takes you through the full spectrum of supply chain analytics, beginning with the foundational concepts that define modern analytical supply chain management. You will understand the critical role analytics plays in decision-making, explore the supply chain analytics maturity model, and learn how data architecture, governance standards, and quality management create the backbone for effective analysis.

As you progress, you will dive deep into descriptive analytics and performance measurement techniques used by organizations to monitor and improve operational performance. You will learn how to map material and information flows, evaluate service reliability through key order fulfillment metrics, analyze financial performance using cash-to-cash cycle analysis, and benchmark supply chain performance against industry standards.

The course then explores predictive analytics, where you will master demand forecasting concepts essential for accurate planning. You will study qualitative and quantitative forecasting methods, analyze trends, seasonality, and cyclical demand behavior, measure forecast accuracy using statistical techniques, and understand collaborative forecasting frameworks that align supply chain stakeholders for better decision-making.

Inventory and warehouse analytics are covered extensively, helping you understand how to balance service levels with inventory carrying costs. You will learn safety stock calculations, lead time variability analysis, multi-echelon inventory optimization principles, and warehouse efficiency measurement techniques that support operational excellence.

Transportation and network design analytics form another critical component of this course. You will gain insights into facility location decisions, strategic network design, total landed cost analysis, transportation mode selection, freight consolidation strategies, and routing optimization concepts that drive cost-effective logistics operations.

Finally, the course introduces strategic optimization and risk analytics, enabling you to understand advanced analytical decision-making techniques such as linear programming, scenario modeling, supply chain risk identification, and sustainability measurement through carbon footprint analysis. These concepts will help you address real-world supply chain challenges with confidence and analytical precision.

Whether you are a student, supply chain professional, operations manager, business analyst, or someone looking to build expertise in data-driven supply chain management, this course provides the practical knowledge and strategic insights needed to excel in today’s competitive business landscape.

By the end of this course, you will have a strong command of supply chain analytics concepts and the ability to apply analytical thinking to forecasting, inventory management, transportation planning, performance measurement, optimization, and strategic decision-making across complex supply chain environments.

Thank you

Who this course is for:

Students who want to build a strong foundation in supply chain analytics
Supply chain professionals seeking to enhance their analytical and decision-making skills
Logistics and operations managers looking to improve efficiency through data-driven strategies
Business analysts interested in applying analytics to supply chain performance optimization
Demand planners and inventory managers who want to strengthen forecasting and inventory optimization expertise
Procurement and sourcing professionals aiming to better understand supply chain performance metrics
Warehouse and transportation professionals seeking analytical approaches to operational improvement
Managers and decision-makers responsible for supply chain strategy and optimization
Professionals transitioning into supply chain management or analytics roles
Anyone interested in learning how data and analytics transform modern supply chain operations

Supply Chain Analytics: Forecast, Optimization & Performance

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Course content

Foundations of Supply Chain Analytics4 lectures • 15min

Descriptive Analytics and Performance Measurement4 lectures • 15min

Predictive Analytics for Demand Planning4 lectures • 15min

Inventory and Warehouse Analytics4 lectures • 15min

Transportation and Network Design Analytics4 lectures • 15min

Strategic Optimization and Risk Analytics3 lectures • 12min

Requirements

Description

Who this course is for: