Forecasting Mse401 1

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    3-1

    Technology Forecasting LearningTechnology Forecasting Learning

    ObjectivesObjectives

    List the elements of a good forecast. Outline the steps in the forecasting

    process.

    Describe at least three qualitativeforecasting techniques and the advantages

    and disadvantages of each.

    Compare and contrast qualitative andquantitative approaches to forecasting.

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    FORECAST: A statement about the future value of a

    variable of interest such as demand.

    Forecasting is used to make informeddecisions.

    Long-range

    Short-range

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    ForecastsForecasts

    Forecasts affect decisions and activitiesthroughout an organization

    Accounting, finance

    Human resources Marketing

    MIS

    Operations Product / service design

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    Accounting Cost/profit estimates

    Finance Cash flow and funding

    Human Resources Hiring/recruiting/training

    Marketing Pricing, promotion, strategy

    MIS IT/IS systems, services

    Operations Schedules, MRP, workloads

    Product/service design New products and services

    Uses of ForecastsUses of Forecasts

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    Assumes causal systempast ==> future

    Forecasts rarely perfect because of randomness

    Forecasts more accurate forgroups vs. individuals

    Forecast accuracy decreasesas time horizon increases I see that you will

    get an A this semester.

    Features of ForecastsFeatures of Forecasts

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    Elements of a Good ForecastElements of a Good Forecast

    Timely

    AccurateReliable

    Meaningfu

    l

    Written

    Easy

    tous

    e

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    Steps in the Forecasting ProcessSteps in the Forecasting Process

    Step 1 Determine purpose of forecast

    Step 2 Establish a time horizon

    Step 3 Select a forecasting techniqueStep 4 Obtain, clean and analyze data

    Step 5 Make the forecast

    Step 6 Monitor the forecast

    The forecast

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    Types of ForecastsTypes of Forecasts

    Judgmental- uses subjective inputs

    Time series - uses historical dataassuming the future will be like the past

    Associative models - uses explanatoryvariables to predict the future

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    Judgmental ForecastsJudgmental Forecasts

    Executive opinions Sales force opinions

    Consumer surveys

    Outside opinion

    Delphi method

    Opinions of managers and staff Achieves a consensus forecast

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    Time Series ForecastsTime Series Forecasts

    Trend- long-term movement in data Seasonality- short-term regular

    variations in data

    Cycle wavelike variations of more thanone years duration

    Irregular variations - caused by unusual

    circumstances Random variations - caused by chance

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    Naive ForecastsNaive Forecasts

    Uh, give me a minute....We sold 250 wheels last

    week.... Now, next week

    we should sell....

    The forecast for any period equalsthe previous periods actual value.

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    Simple to use Virtually no cost

    Quick and easy to prepare

    Data analysis is nonexistent Easily understandable

    Cannot provide high accuracy

    Can be a standard for accuracy

    Nave ForecastsNave Forecasts

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    Techniques for AveragingTechniques for Averaging

    Moving average

    Weighted moving average

    Exponential smoothing

    Ch i F tiCh i F ti

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    Choosing a ForecastingChoosing a Forecasting

    TechniqueTechnique

    No single technique works in everysituation

    Two most important factors

    Cost Accuracy

    Other factors include the availability of:

    Historical data Computers

    Time needed to gather and analyze the data

    Forecast horizon

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    Operations StrategyOperations Strategy

    Forecasts are the basis for many decisions

    Work to improve short-term forecasts

    Accurate short-term forecasts improve

    Profits

    Lower inventory levels

    Reduce inventory shortages

    Improve customer service levels Enhance forecasting credibility


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