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Demand Forecasting

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Information about Demand Forecasting
Education

Published on August 1, 2008

Author: laroiya

Source: authorstream.com

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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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