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4 Forecasting

PowerPoint presentation to PowerPoint presentation to accompany accompany Heizer and Render Heizer and Render Operations Management, 10e Operations Management, 10e Principles of Operations Principles of Operations Management, 8eManagement, 8e

PowerPoint slides by Jeff Heyl

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What is Forecasting?What is Forecasting? Process of

predicting a future event

Underlying basis of all business decisions Production Inventory Personnel Facilities

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Short-range forecast Up to 1 year, generally less than 3

months Purchasing, job scheduling, workforce

levels, job assignments, production levels

Medium-range forecast 3 months to 3 years Sales and production planning, budgeting

Long-range forecast 3+ years New product planning, facility location,

research and development

Forecasting Time HorizonsForecasting Time Horizons

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Influence of Influence of Product Life CycleProduct Life Cycle

Introduction and growth require longer forecasts than maturity and decline

As product passes through life cycle, forecasts are useful in projecting Staffing levels Inventory levels Factory capacity

Introduction – Growth – Maturity Introduction – Growth – Maturity – Decline– Decline

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Product Life CycleProduct Life CycleIntroduction Growth Maturity Decline

OM Strategy/Issues

Little product differentiationCost minimizationOvercapacity in the industryPrune line to eliminate items not returning good marginReduce capacity

Figure 2.5

1.costs are very high2.slow sales volumes to start3.little or no competition4.demand has to be created5.customers have to be prompted to try the productmakes no money at this stage

1.costs reduced due to economies of scale2.sales volume increases significantly3.profitability begins to rise4.public awareness increases5.competition begins to increase with a few new players in establishing marketincreased competition leads to price decreases

1.costs are lowered as a result of production volumes increasing and experience curve effects2.sales volume peaks and market saturation is reached3.increase in competitors entering the market4.prices tend to drop due to the proliferation of competing products5.brand differentiation and feature diversification is emphasized to maintain or increase market shareIndustrial profits go down

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TypesTypes of Forecasts of Forecasts Economic forecasts

Address business cycle – inflation rate, money supply, housing starts, etc.

Technological forecasts Predict rate of technological progress Impacts development of new products

Demand forecasts Predict sales of existing products and

services

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Strategic ImportanceStrategic Importance of Forecastingof Forecasting

Human Resources – Hiring, training, laying off workers

Capacity – Capacity shortages can result in undependable delivery, loss of customers, loss of market share

Supply Chain Management – Good supplier relations and price advantages

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Seven Steps Seven Steps in Forecastingin Forecasting1. Determine the use of the

forecast2. Select the items to be

forecasted3. Determine the time horizon of

the forecast4. Select the forecasting model(s)5. Gather the data6. Make the forecast7. Validate and implement results

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Forecasting ApproachesForecasting Approaches

Used when situation is vague and little data exist New products New technology

Involves intuition, experience e.g., forecasting sales on

Internet

Qualitative Qualitative MethodsMethods

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Forecasting ApproachesForecasting Approaches

Used when situation is ‘stable’ and historical data exist Existing products Current technology

Involves mathematical techniques e.g., forecasting sales of

color televisions

Quantitative Quantitative MethodsMethods

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Overview of Overview of Qualitative MethodsQualitative Methods

1. Jury of executive opinion Pool opinions of high-level

experts, sometimes augment by statistical models

2. Delphi method Panel of experts, queried

iteratively

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Overview of Overview of Qualitative MethodsQualitative Methods

3. Sales force composite Estimates from individual

salespersons are reviewed for reasonableness, then aggregated

4. Consumer Market Survey Ask the customer

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Involves small group of high-level experts and managers

Group estimates demand by working together

Combines managerial experience with statistical models

Relatively quick ‘Group-think’

disadvantage

Jury of Executive OpinionJury of Executive Opinion

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Sales Force CompositeSales Force Composite

Each salesperson projects his or her sales

Combined at district and national levels

Sales reps know customers’ wants

Tends to be overly optimistic

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Delphi MethodDelphi Method Iterative group

process, continues until consensus is reached

3 types of participants Decision makers Staff Respondents

Staff(Administering survey)

Decision Makers

(Evaluate responses and

make decisions)

Respondents(People who can make valuable judgments)

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Consumer Market SurveyConsumer Market Survey

Ask customers about purchasing plans

What consumers say, and what they actually do are often different

Sometimes difficult to answer

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Overview of Overview of Quantitative ApproachesQuantitative Approaches

1.Naive approach2.Moving averages3.Exponential

smoothing4.Trend projection5.Linear regression

time-series models

associative model

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Set of evenly spaced numerical data Obtained by observing response

variable at regular time periods Forecast based only on past

values, no other variables important Assumes that factors influencing

past and present will continue influence in future

Time SeriesTime Series Forecasting Forecasting

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Trend

Seasonal

Cyclical

Random

Time SeriesTime Series Components Components

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Components of DemandComponents of DemandDe

mand

for

pro

duct

or

serv

ice

| | | |1 2 3 4

Time (years)

Average demand over 4 years

Trend component

Actual demand line

Random variation

Figure 4.1

Seasonal peaks

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Persistent, overall upward or downward pattern

Changes due to population, technology, age, culture, etc.

Typically several years duration

TrendTrend Component Component

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Regular pattern of up and down fluctuations

Due to weather, customs, etc.

Occurs within a single year

Seasonal Seasonal ComponentComponent

Number ofPeriod Length SeasonsWeek Day 7Month Week 4-4.5Month Day 28-31Year Quarter 4Year Month 12Year Week 52

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Repeating up and down movements Affected by business cycle,

political, and economic factors Multiple years duration Often causal or

associative relationships

CyclicalCyclical Component Component

0 5 10 15 20

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Erratic, unsystematic, ‘residual’ fluctuations

Due to random variation or unforeseen events

Short duration and nonrepeating

RandomRandom Component Component

M T W T F

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AssociativeAssociative Forecasting Forecasting

Used when changes in one or more independent variables can be used to predict the changes in the dependent

variableMost common technique is linear regression analysis

We apply this technique just as We apply this technique just as we did in the time series we did in the time series

exampleexample

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AssociativeAssociative Forecasting ForecastingForecasting an outcome based on predictor variables using the least squares technique

y = a + bx^

where y= computed value of the variable to be predicted (dependent variable)a= y-axis interceptb= slope of the regression linex= the independent variable though to predict the value of the dependent variable

^

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Forecasting at Disney WorldForecasting at Disney World Global portfolio includes parks

in Hong Kong, Paris, Tokyo, Orlando, and Anaheim

Revenues are derived from people – how many visitors and how they spend their money

Daily management report contains only the forecast and actual attendance at each park

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Forecasting at Disney WorldForecasting at Disney World

Disney generates daily, weekly, monthly, annual, and 5-year forecasts

Forecast used by labor management, maintenance, operations, finance, and park scheduling

Forecast used to adjust opening times, rides, shows, staffing levels, and guests admitted

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Forecasting at Disney WorldForecasting at Disney World 20% of customers come from

outside the USA Economic model includes gross

domestic product, cross-exchange rates, arrivals into the USA

A staff of 35 analysts and 70 field people survey 1 million park guests, employees, and travel professionals each year

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Forecasting at Disney WorldForecasting at Disney World Inputs to the forecasting model

include airline specials, Federal Reserve policies, Wall Street trends, vacation/holiday schedules for 3,000 school districts around the world

Average forecast error for the 5-year forecast is 5%

Average forecast error for annual forecasts is between 0% and 3%

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THANK YOU

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