Demand Management in SCM

Presented by Radio Heads

Presented to: Mr. Abdullah Al-Amin

Supply Chain Management

Introduction

– focused efforts to estimate and manage customers’ demand

– with the intention of using this information to shape operating decisions

Objectives• Gathering and analyzing information about

consumers, their problems, and their unmet needs

• Identifying partners to perform the functions needed in the demand chain

• Moving the functions that need to be done to the channel member that can perform them most effectively and efficiently

Objectives• Sharing with other supply chain members

information about consumers and customers, available technology, and logistics challenges and opportunities

• Developing products and services that solve customer’s problems

• Developing and executing the best logistics methods to deliver products and services to consumers in the desired format

Types of Demand Management

• Professor John Mentzer and Mark Moon introduced different types of demand

• Independent demand: Independent demand is the amount of product demanded (by time and location) by end-use customers of the supply chain.

• Dependent or derived demand: An item whose demand is tied directly to the demand or production level of another item.

Independent Demand VS Dependent Demand

• Independent demand items are generally finished goods while dependent demand items are generally components or sub assemblies.

• Independent demand items are forecasted while dependent demand item requirements can be derived based on demand for finished goods.

• Example:You would forecast demand for refrigerators but you would calculate how many crisper drawers are needed (2 drawers per fridge, 10 fridges next week therefore need 200 crisper drawers.)

What is Forecasting?• Forecasting is the art and science of predicting

future events– Historical data– Future projection–Mathematical model

• It may be subjective or intuitive prediction

• Combination-mathematical model and manager’s judgment.

Forecasting Time Horizons• Classified on the basis of future time horizon

– Short-range forecast [less than one year]Example: Planning purchasing, job scheduling, workforce levels, job assignments and production levels

– Medium-range forecast [one to three years]Example: Sales planning, production planning and budgeting, cash budgeting and analyze operating plans

– Long-range forecast [more than three years]Example: Planning for new products, capital expenditures, facility location or expansion and R&D

Types of Forecast

1. Economic Forecast : address the business cycle by predicting;

» Inflation rates»Money supply»Housing starts»Other planning indicators

Types of Forecast

2. Technological forecast: concerned with rates of technological progress which results in;– Birth of new exciting products– Requiring new plants and equipment

Types of Forecast

3. Demand forecast: Projects demand for a company's products or services– Sales forecast– Production, capacity ad scheduling systems– Serve as inputs to financial, marketing and

personnel planning

Strategic Importance of Forecasting

Human Resource• Hiring, training and laying off workers• Hiring of additional workers affects training and

qualityCapacity• Inadequate capacity results – Undependable delivery– Loss of customers– Loss of market share

Strategic Importance of Forecasting

Supply-Chain Management• Good relations with suppliers• Ensuing price advantages for materials and

parts

Seven Steps in the Forecasting System

1. Determine the use of forecast2. Select the items to be forecasted3. Determine the time horizon of the forecast4. Select the forecasting models5. Gather the data needed to make the forecast6. Make the forecast7. Validate and implement the results

Forecasting Approaches1. Qualitative analysis

» Jury of Executive opinion» Delphi Method» Sales Force Composite» Consumer Market Survey

2. Quantitative analysis» Time-series Models

• Naïve Approach• Moving Average• Exponential Smoothing• Trend Projection

» Associative Models• Regression Analysis

Qualitative Methods1. Jury of Executive opinion– Group of high-level experts or managers– In combination with statistical models– Arrive at a group estimate of demand

2. Delphi Method– 3 different participantsa) Decision makers: group of 5-10 expertsb) Staff personnel: assist decision makers by preparing,

distributing, collecting and summarizing questionnaires and survey results

c) Respondents: provide inputs to the decision makers before forecasting

Qualitative Methods

3. Sales Force Composite– Estimation of each salesperson– Revision to ensure– Combined at district and national levels– To reach an overall forecast

Qualitative Methods

4. Consumer Market Survey– Input from customers or potential customers– In regards of their future purchasing plans– Helpful in preparation of forecast– Improving product design and planning for new

products– Overly optimistic forecast arising from customer

input

Quantitative Methods

• Time-series Models: – Prediction on the assumption that the future is a

function of the past– It includes:

» Naïve approach» Moving averages» Exponential smoothing » Trend projection

Decomposition of a Time Series

• Analysis of time series requires:– Breaking down past data into components– And then projecting them forward

• A time series has four components:»Trend»Seasonality»Cycles»Random variations

Decomposition of a Time Series

• Trend: Gradual upward and downward movement of the data over time

• Seasonality: Data pattern that repeats itself after a period of days, weeks, months, or quarters

• Cycles: Patterns in data that occur every several years

• Random variations: Blips in data caused by chance and unusual situations

Quantitative Methods

1. Naïve Approach– Assumption that the demand in the next period will be

equal to demand in the most recent period

2. Moving Averages– Use a number of historical actual data values to

generate a forecast– Useful if we can assume that market demands will stay

fairly steady over time– Moving average = ∑ Demand in previous n periods

n

Quantitative Methods

3. Exponential Smoothing– Involves very little record keeping of past data– New forecast = Last period’s forecast + α (last

period’s actual demand-last period’s forecast)

4. Trend Projections– Fits a trend line to a series of historical data point– Projects the line into the future for forecasts

Quantitative Methods

Associative Models:– Incorporate the variables or factors that might

influence the quantity being forecasted.

1. Linear Regression Analysis• A straight line mathematical model• Describes the functional relationship between

independent and dependent variables