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Program Overview and Learning Objectives

Course Orientation: Branch Warehouse Demand Fundamentals and Outcomes

Foundations of Branch Warehouse Demand

Defining Branch Warehouse Demand and Demand Signals

Data Quality and Master Data for Replenishment Accuracy

Forecasting Branch Warehouse Demand

Diagnosing Demand: Seasonality, Trend, and Causals

Forecast Models for Branch Warehouses

Inventory Policy and Replenishment Design

Safety Stock and Service-Level Design for Branches

Reorder Points, Order Quantities, and Constraints

Execution, Exceptions, and Network Considerations

Replenishment Execution and Exception Management

Multi-Branch Network Design and Financial Alignment

Systems, Data Pipelines, and Operating Model

Demand Planning Systems and Data Pipelines for Branch Replenishment

Operating Model and Continuous Improvement

Capstone and Applied Practice

Capstone Workshop: End-to-End Branch Warehouse Demand Strategy

Knowledge Checks

Quiz 1: Warehouse Demand Concepts and Signals

Quiz 2: Master Data and Data Quality

Quiz 3: Demand Diagnostics and Segmentation

Quiz 4: Forecast Models and Accuracy

Quiz 5: Safety Stock and Service Levels

Quiz 6: Reorder Points and Order Quantities

Quiz 7: Execution and Exceptions

Quiz 8: Network and Financial Alignment

Quiz 9: Systems and Data Pipelines

Quiz 10: Capstone Synthesis

Branch Warehouse Demand Mastery: Forecasting, Replenishment, and Operating Model is a practitioner-built program for supply chain, operations, and planning leaders who run multi-branch networks. If you manage availability, working capital, and service levels across branches or distribution centers, this course gives you the end-to-end toolkit: defining branch-level demand signals, building accurate forecasts, designing inventory policies, and executing replenishment at scale. You will learn how to translate business goals into statistical targets, tune safety stock for volatile and intermittent demand, and set reorder points and lot sizes that respect lead-time variability, constraints, and cost-service trade-offs. The program also covers exception management, network allocation during scarcity, and the financial linkages that matter to CFOs—turns, cash-to-cash, reserves, and write-offs. Finally, you’ll operationalize it: systems architecture, clean data pipelines, planner workflows, and governance with S&OE/S&OP cadences. Through hands-on diagnostics, model selection, and a capstone strategy build, you will leave with a deployable 90-day roadmap to improve fill rate, reduce backorders, and release working capital—without compromising customer experience.

Branch Warehouse Demand Mastery: Forecasting, Replenishment, and Operating Model

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            <p>Branch Warehouse Demand Mastery: Forecasting, Replenishment, and Operating Model equips supply chain leaders to translate demand signals into executable policies that raise availability, protect working capital, and lower total cost. The program begins by defining branch warehouse demand in the context of multi-branch networks and clarifying how it differs from customer, transfer, and dependent demand. We map course goals directly to business outcomes—service levels, inventory turns, and cash-to-cash—while setting the scope across item classes, lead-time variability, and network constraints. You will see how each module aligns to four pillars: forecasting, inventory policy, execution, and governance, ensuring that concepts move beyond theory into measurable operational impact.</p>
<p>Foundational modules establish the data bedrock: demand signals such as historical issues, POS, transfers, returns, and substitutions; SKU-Branch-Time structures; and master data for SKU, branch, and supplier attributes. With data quality and ownership defined, the course advances to demand diagnostics—intermittency, lumpy profiles, and seasonality—then to model selection, including exponential smoothing and Croston-family methods, hierarchy reconciliation, and forecast accuracy metrics tied to service attainment. Inventory policy design covers safety stock translation from service goals, non-normal and intermittent demand approaches, and multi-branch risk pooling. Replenishment execution focuses on reorder points, lot sizing under MOQs and case packs, and capacity and freight constraints, along with exception management and KPIs. We extend into network design decisions, scarcity allocation, and financial integration, before turning to systems architecture, data pipelines, lead-time modeling, and an operating model with clear RACI, S&OE/S&OP linkages, and continuous improvement routines. The capstone synthesizes forecasting, policy, execution, and financials into a deployable plan, complete with a policy matrix, exception playbook, governance dashboard, and a 90-day rollout roadmap supported by staged knowledge checks throughout the journey.</p>
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