King Abdulaziz University Faculty of Engineering Industrial Engineering Dept. - PowerPoint PPT Presentation

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King Abdulaziz University Faculty of Engineering Industrial Engineering Dept.

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All functional lines: (finance, marketing, personnel, production areas) Some ... Model implementation (the actual Forecast). 5. Forecast evaluation. – PowerPoint PPT presentation

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Title: King Abdulaziz University Faculty of Engineering Industrial Engineering Dept.


1
King Abdulaziz UniversityFaculty of
EngineeringIndustrial Engineering Dept.
  • IE 436
  • Dynamic Forecasting

2
CHAPTER 1 Introduction to Forecasting
The History of Forecasting
  • Some Techniques In the nineteenth century.
  • Some Others only recently.
  • Forecasting Process Continue to grow.
  • Consumers of forecasts (Managers)
  • More attention to Forecasting.

3
Is Forecasting Necessary?
  • All organizations operate in uncertainty.
  • Decisions affecting the future must be made.
  • Judgments are not so accurate.
  • World has always been changing.
  • Competition has become more keen.

4
Who needs forecasts ?
  • All types of organizations
  • (large-small, private-public).
  • All functional lines
  • (finance, marketing, personnel, production
    areas)

5
Some Questions that need forecasting
  • Increase advertising by 10 sales?
  • Over the next 2 years revenues?
  • How many units might we sell?
  • To explain sales variability
  • factors to consider?
  • Loan balance over the next 10 years?

6
Types of Forecasts
  • Time horizon (long, intermediate, short).
  • Level of details (micro-macro).
  • Methods used (Quantitative-qualitative).
  • Note judgment must be used along with
    quantitative forecasting procedures.

7
Range of Forecasting
Range Period Variables to be forecasted
Short Term 1 day to 1 year, )1 season) Demand forecasting, staffing levels, purchasing, inventory levels
Medium Term 1 season to 2 years Aggregate planning, capacity planning, sales forecasts
Long Term 5 and more years into the future RD, plant location, product planning
8
Forecasting Steps
  • 1. Problem Formulation and
  • Data collection.
  • 2. Data manipulation and cleaning.
  • 3. Model building and evaluation.
  • 4. Model implementation
  • (the actual Forecast).
  • 5. Forecast evaluation.

9
Forecasting Steps
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