Forecasting in Supply Chain
Download as PPTX, PDF17 likes29,142 views
The document discusses demand forecasting and push/pull processes in supply chains. It notes that push processes anticipate customer demand while pull processes respond to it. Forecasts will always contain errors that should be measured. Long term forecasts are generally less accurate than short term ones. Aggregate forecasts tend to be more accurate than disaggregate ones due to error reduction. The bullwhip effect causes demand distortion as information moves up a supply chain.
Forecasting in Supply Chain
- 1. EP JOHN
- 2. ALL PUSH PROCESSES IN SUPPLY CHAIN ARE PERFORMED IN ANTICIPATION OF CUSTOMER DEMAND ALL PULL PROCESSES IN SUPPLY CHAIN ARE PERFORMED IN RESPONSE TO CUSTOMER DEMAND
- 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. AGGREGATE FORECASTS ARE USUALLY MORE ACCURATE 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 A COMPANY, GREATER IS THE DISTORTION OF INFORMATION IT RECEIVES. (BULLWHIP EFFECT)
- 5. PAST DEMAND LEAD TIME OF PRODUCT PLANNED ADVERTISING OR MARKETING EFFORTS STATE OF THE ECONOMY PLANNED PRICE DISCOUNTS ACTIONS THAT COMPETITORS HAVE TAKEN
- 6. QUATITATIVE TIME SERIES CASUAL SIMULATION
- 7. 1. UNDERSTAND THE OBJECTIVE OF FORECASTING 2. INTEGRATE DEMAND PLANNING AND FORECASTING THROUGH OUT THE SUPPLY CHAIN 3. UNDERSTAND AND IDENTIFY CUSTOMER SEGMENTS
- 8. 4. IDENTIFY THE MAJOR FACTORS THAT INFLUENCE THE DEMAND FORECAST 5.DETERMINE THE APPROPRIATE FORECASTING TECHNIQUE 6.ESTABLISH PERFORMANCE AND ERROR MEASURES FOR THE FORECAST
- 9. GOAL – SYSTEMATIC COMPONENET & RANDOM COMPONENT SYSTEMATIC COMPONENT – LEVEL, TREND AND SEASONAL FACTOR MULTIPLICATIVE LEVEL X TREND X SEASONAL FACTOR ADDITIVE LEVEL + TREND + SEASONAL FACTOR MIXED (LEVEL + TREND) X SEASONAL FACTOR
- 10. A GOOD FORECASTING METHOD SHOULD CAPTURE THE SYSTEMATIC COMPONENT OF DEMAND BUT NOT THE RANDOM COMPONENT. THE RANDOM COMPONENT MANIFESTS ITSELF IN THE FORM OF A FORECAST ERROR THAT CONTAIN VALUABLE INFORMATION AND MUST BE ANALYSED FOR THE TWO REASONS,
- 11. MANAGERS USE ERROR ANALYSIS TO DETERMINE WHETHER THE CURRENT FORECASTING METHOD IS PREDICTING THE SYSTEMATIC COMPONENT OF DEMAND ACCURATELY. ALL CONTIGENCY PLANS MUST ACCOUNT FOR FORECAST ERROR. Et = Ft - Dt
- 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 OF PROMOTIONS ON DEMAND AND CAN BE USED TO DETERMINE THE EXTENT AND TIMING OF PROMOTIONS
- 13. FIRMS WITH A FEW CUSTOMERS OFTEN EXPERIENCE VERY LUMPY DEMAND THAT IS HARDER TO FORECAST THAN DEMAND FROM MANY SMALL CUSTOMERS, THAT TENDS TO BE SMOOTHER. TWO STRATEGIES USED TO MITIGATE FORECAST RISK WITH RIGHT BALANCE ARE INCREASEING THE RESPONSIVENESS UTILISING OPPURTUNITIES FOR POOLING OF DEMAND.
- 14. COLLABORATE IN BUILDING FORECASTS SHARE ONLY THE DATA THAT TRULY PROVIDE VALUE BE SURE TO DISTINGUISH BETWEEN DEMAND AND SALES
- 15. UNDERSTAND THE ROLE OF FORECASTING FOR BOTH AN ENTERPRISE AND A SUPPLY CHAIN IDENTIFY THE COMPONENTS OF A DEMAND FORECAST FORECAST DEMAND IN A SUPPLY CHAIN GIVEN HISTORICAL DATA USING TIME- SERIES METHGODOLOGIES ANALYSE DEMAND FORECASTS TO ESTIMATE FORECAST ERROR