time_horizon

8/7/2019 Time_horizon

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Islamic University, Gaza - Palestine

Department of Industrial Engineering

Introduction to Principles of ProductionManagement

WS 2009/2010

Presented by

Dr. Eng. Abed Schokry


What is Forecasting

Process of predicting a future event Underlying basis of allbusiness decisions:

• Production• Inventory

• Personnel• Facilities


Introduction to Forecasting

• What is forecasting?

– Not just a guess

– Definite methods of predicting future events

• Why are we interested?

– Forecasts provide helpful information to make betterdecisions

– Rewards of good forecasting or penalties for bad forecasting

can be high – Forecasting is easier and cheaper now


Types of Forecasts by Time Horizon

ShortShort--range forecastrange forecast

•• Up toUp to 11 year; usually less thanyear; usually less than 33 monthsmonths•• Job scheduling, worker assignmentsJob scheduling, worker assignments

MediumMedium--range forecastrange forecast

•• 33 months tomonths to 33 yearsyears•• Sales & production planning, budgetingSales & production planning, budgeting

LongLong--range forecastrange forecast

•• 33++ yearsyears

•• New product planning, facility locationNew product planning, facility location




Short-term vs. Longer-term Forecasting

Medium/long range forecasts deal with more comprehensive issuesMedium/long range forecasts deal with more comprehensive issues

and support management decisions regarding planning andand support management decisions regarding planning andproducts, plants and processes.products, plants and processes.

ShortShort--term forecasting usually employs different methodologies thanterm forecasting usually employs different methodologies thanlongerlonger--term forecastingterm forecasting

ShortShort--term forecasts tend to be more accurate than longerterm forecasts tend to be more accurate than longer--termtermforecastsforecasts


Seven Steps in Forecasting

Determine the use of the forecastDetermine the use of the forecast

Select the items to be forecastedSelect the items to be forecasted

Determine the time horizon of the forecastDetermine the time horizon of the forecast

Select the forecasting model(s)Select the forecasting model(s)

Gather the dataGather the data

Make the forecastMake the forecast

Validate and implement resultsValidate and implement results


Forecasting Approaches

Qualitative MethodsQualitative Methods

(subjective) = people expertise)

Quantitative MethodsQuantitative Methods((objective) = math models

••Used when situation isUsed when situation is

vague & little data existvague & little data exist

••New productsNew products

••New technologyNew technology

•• Involves intuition, experienceInvolves intuition, experience

e.g., forecasting sales one.g., forecasting sales on

InternetInternet

••Used when situation is ‘stable’Used when situation is ‘stable’& historical data exist& historical data exist

••Existing productsExisting products

••Current technologyCurrent technology

•• Involves mathematicalInvolves mathematicaltechniquestechniques ¨̈e.g., forecastinge.g., forecasting

sales of color televisionssales of color televisions


Forecasting Process

6. Check forecastaccuracy with oneor more measures

4. Select a forecastmodel that seemsappropriate for data

5. Develop/computeforecast for periodof historical data

8a. Forecast overplanning horizon

9. Adjust forecastbased on additionalqualitative informationand insight

10. Monitor resultsand measureforecast accuracy

8b. Select newforecast model oradjust parametersof existing model

7.Is accuracyof forecast

acceptable?

1. Identify thepurpose of forecast

3. Plot data andidentify patterns

2. Collect historicaldata

No

Yes




Overview of Qualitative Methods

Jury of executive opinionJury of executive opinion

Pool opinions of highPool opinions of high--level executives, sometimes augment bylevel executives, sometimes augment bystatistical modelsstatistical models

Delphi methodDelphi method

Panel of experts, queried iterativelyPanel of experts, queried iteratively

Sales force compositeSales force composite

Estimates from individual salespersons are reviewed forEstimates from individual salespersons are reviewed forreasonableness, then aggregatedreasonableness, then aggregated

Consumer Market SurveyConsumer Market Survey

Ask the customerAsk the customer


Overview of Qualitative Methods

•• Jury of executive opinion

Pool opinions of high-level executives, sometimes augment bystatistical models

• Delphi method

Panel of experts, queried iteratively

• Sales force composite

Estimates from individual salespersons arereviewed for reasonableness, then aggregated

• Consumer Market Survey

Ask the customer


Jury of Executive Opinion

•• Involves small group of high-level managers• Group estimates demand by working toge ther

• Combines managerial experience with statistical models

• Relatively quick

• ‘ Group-think’ is disadvantage


Sales Force Composite

•• Each salesperson projects his or her salesEach salesperson projects his or her sales

•• Combined at district & national levelsCombined at district & national levels

•• Sales reps know customers’ wantsSales reps know customers’ wants

•• Tends to be overly optimisticTends to be overly optimistic




Delphi Method

• I terative group process

• 3 types of peop le:

• Dec ision makers

• Staff• Respondents

A panel of experts are individually questioned about their

perceptions of future events.

• Reduces ‘group-think’


Consumer Market Survey

• Ask customers about purchasing plans

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

• Sometimes difficult to answer


Quantitative Forecasting Methods (Non-Naive)


What is a Time Series?

Is a set of observations measured at successive points in time oversuccessive periods of time.

A time series is a time-ordered list of historical data .

Assumption : the history is a reasonable predictor of the future.

Obtained by observing response variable at regular time periods

Assumes that factors influencing past and present will continue influencein future

Example:

Year: 1998 1999 2000 2001 2002Sales: 78.7 63.5 89.7 93.2 92.1




Time Series Components


Trend Component

•Persistent, overall upward or downward pattern

•Due to population, technology etc.

•Several years duration


Seasonal Component

• Regular pattern of up & down fluctuations• Due to weather, customs etc.

• Occurs within 1 year

Examples of seasonal model:

• heating fuel• skiing equipment• ice cream


Common Seasonal Patterns




Cyclical Component

• Repeating up & down movements

• Due to interactions of factors influencing economy• Usually 2-10 years duration


Random Component

• Erratic, unsystematic, ‘residual’ fluctuations

• Due to random variation or unforeseen events

o Union strikeo Tornado

• Short duration & non-repeating


Costs and Benefits of Forecasting

Benefits:

– Aids decision making

– Informs planning and resource allocation decisions

– If data is of high quality, can be accurate


Benefits and Costs of Forecasting

Costs:

– Data not always reliable or accurate

– Data may be out of date

– The past is not always a guide to the future

– Qualitative data may be influenced by peer pressure

– Difficulty of coping with changes to external factors out of the

business’s control – e.g. economic policy, politicaldevelopments, natural disasters – Tsunami, earthquakes, etc.




End of Chapter 3

time_horizon

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