Demand Forecasting

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introduction to the methods of estimating demand

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Presentation Transcript

DEMAND FORECASTING : 

DEMAND FORECASTING DR.SK LAROIYA

Slide 2: 

ESTIMATION OF DEMAND FOR A PRODUCT IN A FORECAST YEAR/ PERIOD IS TERMED EX-ANTE FORECASTS EX-POST FORECASTS

FORECAST FRAMEWORK : 

FORECAST FRAMEWORK HOW FAR AHEAD? SHORT TERM OR LONG TERM FORECAST? AT FIRM’S LEVEL AT INDUSTRY’S LEVEL FOR MARKET SEGMENT FOR TOTAL MARKET

Slide 4: 

ACTIVE FORECAST PASSIVE FORECAST FOR A NEW PRODUCT FOR A N ESTABLISHED PRODUCT

WHY DEMAND FORECAST : 

WHY DEMAND FORECAST GENERAL PURPOSE: MARKET IS DYNAMIC , COMPETITIVE AND VOLATILE BETTER PLANNING AND ALLOCATION OF RESOURCES

Slide 6: 

SPECIFIC PURPOSES: APPROPRIATE PRODUCTION SCHEDULING INVENTORY CONTROL DETERMINING APPROPRIATE PRICING POLICIES SETTING SALES TARGETS AND ESTABLISHING CONTROLS AND INCENTIVES

Slide 7: 

PLANNING NEW UNIT OR EXPANDING THE EXISTING ONE PLANNING LONG TERM FINANCIAL REQUIREMENTS PLANNING HRD STRATEGIES

METHODS OF DEMAND FORECASTING : 

METHODS OF DEMAND FORECASTING SURVEY OF BUYERS’ INTENTIONS CONSUMER GOODS PRODUCER GOODS ( END USE METHOD) MIX GOODS

Slide 9: 

EXPERTS’ OPINION METHOD SIMPLE OR WEIGHTED AVERAGE OF NUMBERS GIVEN BY VARIOUS EXPERTS TO ARRIVE AT NEEDED FORECAST DELPHI METHOD

Slide 10: 

MARKET EXPERIMENT METHOD ACTUAL EXPERIMENT MARKET SIMULATION METHOD ( LAB. EXPERIMENT TECHNIQUE)

Slide 11: 

TREND PROJECTION METHOD:

Slide 12: 

SMOOTHING METHOD: IF THE VARIABLE UNDER FORECAST DOES NOT FOLLOW ANY SPECIFIC TREND – UPWARD OR DOWNWARD- TREND PROJECTION METHOD IS INAPPROPRIATE

Slide 13: 

IN SUCH A SITUATION SMOOTHING METHOD IS MORE USEFUL SIMPLE SMOOTHING WEIGHTED SMOOTHING EXPONENTIAL SMOOTHING

Slide 14: 

SIMPLE SMOOTHING: SIMPLE AVERAGE OF SPECIFIC OBSERVATION (CALLED ORDER)

Slide 15: 

WEIGHTED SMOOTHING: WEIGHTED AVERAGE: AS RECENT OBSERVATIONS ARE MORE RELEVANT THAN THE OLDER ONES FOR ESTIMATING FUTURE DEMAND, WEIGHTED SMOOTHING IS PREFERRED TO SIMPLE SMOOTHING

Slide 16: 

WEIGHTS ARE ASSIGNED IN A DESCENDING ORDER AS ONE GOES FROM CURRENT OBSERVATION TO PAST ONES

Slide 17: 

EXPONENTIAL SMOOTHING: SINCE IT IS HARD TO DECIDE A PRIORI WEIGHTS, THEY ARE OFTEN ASSUMED TO FOLLOW GEOMETRICAL PROGRESSION a, a(1-a), a(1-a)² ……. WHERE ‘a’ IS WEIGHT ATTACHED TO MOST CURRENT OBSERVATION

Slide 18: 

AND a(1-a), TO ONE PERIOD BACK OBSERVATION AND, a(1-a)² TO TWO PERIOD BACK OBSERVATION AND SO ON THE SUM OF ALL THESE WEIGHTS IS EQUAL TO 1 AND VALUE OF ‘a’ LIES BETWEEN 0 AND 1

Slide 19: 

WHEN WEIGHTS ARE DESIGNED IN THIS WAY, WEIGHTED SMOOTHING METHOD BECOMES EXPONENTIAL SMOOTHING METHOD

Slide 20: 

REGRESSION METHOD: -BIVARIATE -MULTIVARIATE

Slide 21: 

IT INVOLVES FOUR STEPS: IDENTIFICATION OF VARIABLES WHICH INFLUENCE DEMAND FOR THE PRODUCT WHOSE FUNCTION IS UNDER ESTIMATION COLLECTION OF HISTORICAL DATA ON ALL RELEVANT VARIABLES CHOOSING AN APPROPRIATE FORM OF A FUNCTION ESTIMATION OF FUNCTION

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