IMM 8th ed Ch 8

Introduction to Materials Management

  • This document is the 8th edition of "Introduction to Materials Management" by Chapman, Arnold, Gatewood, and Clive (Copyright © 2017 by Pearson Education, Inc).

  • Focus topic: Forecasting and Demand Management.

Chapter Overview

  • Key topics covered include:

    • What demand needs to be forecasted

    • Demand Management strategies

    • CPFR (Collaborative Planning, Forecasting, and Replenishment)

    • Understanding demand patterns

    • Principles and techniques of forecasting

    • Comparison of Lagging trends vs. Random Variation

    • Insights into forecast errors and bias

Demand Classification

Independent Demand

  • Originates from external sources, beyond control of the organization

  • Requires forecasting or order management

  • Commonly relates to end products or service parts.

Dependent Demand

  • Derived from internal sources; its quantity is calculated rather than forecasted

  • Typically relates to materials used in manufacturing or assembly of products

  • Managed through Material Requirements Planning (MRP).

Demand Management

  • Aim: Recognize and manage demand across all products:

    • Key Activities:

      • Accurate forecasting

      • Promising orders

      • Delivery promises and scheduling

      • Interfacing with planning, control, and the marketplace

      • Incorporating various demands (quality, marketing, engineering, etc.)

    • Market Segmentation: Classifying customer segments and identifying factors that could affect demand (e.g., economic conditions, regulations, competition).

    • Prioritization: Focused on best opportunities to satisfy demand efficiently.

Market-Driven Demand Management

  • Actively detecting and shaping demand through marketing efforts:

    • Use marketing strategies (advertising, pricing, promotions)

    • Respond to market requirements effectively.

CPFR (Collaborative Planning, Forecasting, and Replenishment)

  • Establishes partnerships within the supply chain to develop collective business plans and forecasts.

  • It enables better demand management through:

    • Joint planning

    • Effective communication of forecasts

    • A closed-loop information system for evaluation post-execution.

Advantages of CPFR

  • Cost reductions

  • Enhanced supply chain integration

  • Improved forecast accuracy and customer service

  • Revenue growth opportunities

Challenges of CPFR

  • Integration costs

  • Changes in processes

  • The need for training teams in collaborative processes.

Demand Forecasting

  • Involves projecting future demand based on past data and experiences.

  • Details may include:

    • Individual products

    • Product families

    • Product categories

    • Market sectors

    • Resource allocations.

Demand Patterns Analysis

  • Typical patterns include:

    • Trend Analysis: Understanding upward or downward demand shifts.

    • Cyclicality: Account for economic cycles like booms and recessions.

    • Seasonality: Recognize seasonal demand changes.

    • Random Variations: Sudden increases or decreases without clear patterns.

Forecasting Principles

Why Forecasting is Imperative

  • Planning requires starting with demand projections.

  • Critical considerations include:

    • The potential inaccuracies of forecasts

    • How the plan accommodates expected inaccuracies.

Basic Forecasting Concepts

  • Expectations of forecasting data:

    • Forecasts tend to be less accurate with more variables.

    • Accuracy improves when looking at broader product family levels or nearer time frames.

    • Every forecast should estimate potential errors.

Forecasting Data Collection

  • Collect data relevant to demand:

    • Net sales evaluations

    • Backorders and customer requests

    • Segregate demands by customer segments for precision.

Forecasting Techniques

Qualitative Techniques

  • Depends on judgment, intuition, and informed opinions.

  • Ideal for new product forecasts, or when past data is insufficient.

Quantitative Techniques

  • Uses historical data for extrapolating future demand.

    • Extrinsic: Based on outside indicators correlating to demand (e.g., demographic data).

    • Intrinsic: Uses internal historical data to generate forecasts.

Seasonal Indices and Their Application

  • Seasonal indices help adjust forecasts based on periodic demand variations:

    • Seasonal demand management involves computing indices based on average demands.

    • Apply to forecast future demands for specific seasons effectively.

Forecast Error Measurement

Understanding Forecast Errors

  • Forecasts should be tested through:

    • Mean Absolute Deviation (MAD) calculations: Helps evaluate forecast accuracy by looking at absolute deviations.

Bias and Its Implications

  • Systematic biases indicate consistent over or under-projection of demand.

  • Evaluating biases leads to better forecasting methodologies.

Summary of Content

  • Key concepts to be covered include:

    • Demand forecasting needs and strategies

    • Importance of effective demand management

    • Collaborative approaches to forecasting (CPFR)

    • Various demand patterns and forecasting principles

    • Techniques, errors, and biases associated with forecasting.