Forecasting in Supply Chain

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Forecasting in Supply Chain

  1. 1. EP JOHN
  2. 2. ALL PUSH PROCESSES IN SUPPLY CHAIN ARE PERFORMED IN ANTICIPATION OF CUSTOMER DEMANDALL PULL PROCESSES IN SUPPLY CHAIN ARE PERFORMED IN RESPONSE TO CUSTOMER DEMAND
  3. 3. FORECASTS ARE ALWAYS WRONG AND SHOULD THUS INCLUDE THE EXPECTED VALUE AND A MEASURE OF FORECAST ERROR LONG TERM FORECASTS ARE USUALLY LESS ACCURATE THAT SHORT TERM FORECAST i.e. LONG TERM FORECASTS HAVE A LARGER STANDARD DEVIATION OF ERROR RELATIVE TO THE MEAN THAN SHORT TERM FORECAST
  4. 4. AGGREGATE FORECASTS ARE USUALLY MOREACCURATE THAN DISAGGREGATE FORECASTS AS THEY TEND TO HAVE A SMALLER STANDARD DEVIATION OF ERROR RELATIVE TO THE MEAN THE FARTHER UP A SUPPLY CHAIN, OF ACOMPANY, GREATER IS THE DISTORTION OF INFORMATION IT RECEIVES. (BULLWHIP EFFECT)
  5. 5. PAST DEMAND LEAD TIME OF PRODUCT PLANNED ADVERTISINGOR MARKETING EFFORTS STATE OF THE ECONOMY PLANNED PRICE DISCOUNTS ACTIONS THAT COMPETITORS HAVETAKEN
  6. 6. QUATITATIVETIME SERIES CASUALSIMULATION
  7. 7. 1. UNDERSTAND THE OBJECTIVE OF FORECASTING2. INTEGRATE DEMAND PLANNING AND FORECASTING THROUGH OUT THE SUPPLY CHAIN3. UNDERSTAND AND IDENTIFY CUSTOMER SEGMENTS
  8. 8. 4. IDENTIFY THE MAJOR FACTORS THAT INFLUENCE THE DEMAND FORECAST5.DETERMINE THE APPROPRIATE FORECASTING TECHNIQUE6.ESTABLISH PERFORMANCE AND ERROR MEASURES FOR THE FORECAST
  9. 9.  GOAL – SYSTEMATIC COMPONENET &RANDOM COMPONENT SYSTEMATIC COMPONENT – LEVEL, TRENDAND SEASONAL FACTOR MULTIPLICATIVE LEVEL X TREND X SEASONAL FACTOR ADDITIVE LEVEL + TREND + SEASONAL FACTOR MIXED (LEVEL + TREND) X SEASONAL FACTOR
  10. 10.  A GOOD FORECASTING METHOD SHOULDCAPTURE THE SYSTEMATIC COMPONENT OFDEMAND BUT NOT THE RANDOM COMPONENT. THE RANDOM COMPONENT MANIFESTS ITSELFIN THE FORM OF A FORECAST ERROR THATCONTAIN VALUABLE INFORMATION AND MUSTBE ANALYSED FOR THE TWO REASONS,
  11. 11. MANAGERS USE ERROR ANALYSIS TODETERMINE WHETHER THE CURRENTFORECASTING METHOD IS PREDICTING THESYSTEMATIC COMPONENT OF DEMANDACCURATELY. ALL CONTIGENCY PLANS MUST ACCOUNTFOR FORECAST ERROR. Et = Ft - Dt
  12. 12.  DEMAND PLANNING MODULE(COMMERCIAL DEMAND PLANNING MODULES) ALSO USED FOR PRODUCTS AND CATEGORIES CUSTOMER SALES INFORMATION FACILITATE SHAPING OF DEMAND THESE TOOLS HELP ANALYSE THE IMPACT OFPROMOTIONS ON DEMAND AND CAN BE USED TO DETERMINE THE EXTENT AND TIMING OF PROMOTIONS
  13. 13.  FIRMS WITH A FEW CUSTOMERS OFTENEXPERIENCE VERY LUMPY DEMAND THAT ISHARDER TO FORECAST THAN DEMANDFROM MANY SMALL CUSTOMERS, THATTENDS TO BE SMOOTHER. TWO STRATEGIES USED TO MITIGATEFORECAST RISK WITH RIGHT BALANCE ARE  INCREASEING THE RESPONSIVENESS  UTILISING OPPURTUNITIES FOR POOLING OF DEMAND.
  14. 14. COLLABORATE IN BUILDINGFORECASTS SHARE ONLY THE DATA THAT TRULYPROVIDE VALUE BE SURE TO DISTINGUISH BETWEENDEMAND AND SALES
  15. 15.  UNDERSTAND THE ROLE OF FORECASTINGFOR BOTH AN ENTERPRISE AND A SUPPLYCHAIN IDENTIFY THE COMPONENTS OF ADEMAND FORECAST FORECAST DEMAND IN A SUPPLY CHAINGIVEN HISTORICAL DATA USING TIME-SERIES METHGODOLOGIES ANALYSE DEMAND FORECASTS TOESTIMATE FORECAST ERROR

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