AN AUTOMATED SALES FORECASTING SYSTEM

Transcription

1 AN AUTOMATED SALES FORECASTING SYSTEM

2 Sales Forecasting Example Jun-91 Jun-92 Jun-93 Jun-94 Jun-95 Jun-96 Date

3 Italian

4 Italian German

5 Italian German From Bavaria

6 Sales Forecasting Example Jun-91 Jun-92 Jun-93 Jun-94 Jun-95 Jun-96 Date

7 Sales Forecasting Example Jun-91 Jun-92 Jun-93 Jun-94 Jun-95 Jun-96 Date

8 REQUIREMENTS Regular weekly and monthly forecasts

9 REQUIREMENTS Regular weekly and monthly forecasts Input directly into production scheduling

10 REQUIREMENTS Regular weekly and monthly forecasts Input directly into production scheduling Automated

11 THERE IS NO FOOLPROOF WAY OF AUTOMATICALLY PRODUCING PERFECT FORECASTS

12 THE SAS SOLUTION SAS/ACCESS SAS/ETS PROC ARIMA PROC FORECAST PROC AUTOREG PROC EXPAND SAS/BASE SAS/AF SAS/EIS SAS/GRAPH

13 THE SAS SOLUTION SAS/ACCESS SAS/ETS PROC ARIMA PROC FORECAST PROC AUTOREG PROC EXPAND SAS/BASE SAS/AF SAS/EIS SAS/GRAPH CLIENT/SERVER ARCHITECTURE

14 SYSTEM STRUCTURE Batch job running under UNIX Reads sales Calculates and stores forecasts Produces some reports

15 SYSTEM STRUCTURE Batch job running under UNIX Reads sales Calculates and stores forecasts Produces some reports Online system running under Windows Viewing & editing forecasts Setting of parameters and options Flexible report generation Exporting the forecasts to other systems

16 WHY GO TO ALL THIS EFFORT?

17 WHY GO TO ALL THIS EFFORT? Reduced Inventory Levels

18 WHY GO TO ALL THIS EFFORT? Reduced Inventory Levels Reduced Out-of-Stock

19 WHY GO TO ALL THIS EFFORT? Reduced Inventory Levels Reduced Out-of-Stock Reduced Old/Obsolete Stock

20 WHY GO TO ALL THIS EFFORT? Reduced Inventory Levels Reduced Out-of-Stock Reduced Old/Obsolete Stock Reduced Distribution Costs

21 WHY GO TO ALL THIS EFFORT? Reduced Inventory Levels Reduced Out-of-Stock Reduced Old/Obsolete Stock Reduced Distribution Costs Improved Cash Flow Planning

22 WHY GO TO ALL THIS EFFORT? Reduced Inventory Levels Reduced Out-of-Stock Reduced Old/Obsolete Stock Reduced Distribution Costs Improved Cash Flow Planning Highlighting of Problem Sales Areas

23 METHODOLOGY

24 METHODOLOGY Bottom up

25 Sales Customer Example Jan-92 Jan-93 Jan-94 Jan-95 Jan-96 Date

26 METHODOLOGY Bottom up Top down

27 Sales Forecasting Example Jun-91 Jun-92 Jun-93 Jun-94 Jun-95 Jun-96 Date

28 ISSUES AND PROBLEMS

29 ISSUES AND PROBLEMS New products or products with minimal sales history

30 Sales Product Example Jan-92 Jan-93 Jan-94 Jan-95 Jan-96 Date

31 ISSUES AND PROBLEMS New products or products with minimal sales history Read Budgets

32 ISSUES AND PROBLEMS New products or products with minimal sales history Read Budgets Mathematically Derive

33 ISSUES AND PROBLEMS New products or products with minimal sales history Read Budgets Mathematically Derive» Date of first sale

34 ISSUES AND PROBLEMS New products or products with minimal sales history Read Budgets Mathematically Derive» Date of first sale» Expected sales for the first 12 months

35 ISSUES AND PROBLEMS New products or products with minimal sales history Read Budgets Mathematically Derive» Date of first sale» Expected sales for the first 12 months» Trend

36 ISSUES AND PROBLEMS New products or products with minimal sales history Read Budgets Mathematically Derive» Date of first sale» Expected sales for the first 12 months» Trend» Similar product

37 ISSUES AND PROBLEMS New products or products with minimal sales history Read Budgets Mathematically Derive» Date of first sale» Expected sales for the first 12 months» Trend» Similar product» Seasonal breakdown (known)

38 ISSUES AND PROBLEMS New products or products with minimal sales history Read Budgets Mathematically Derive» Date of first sale» Expected sales for the first 12 months» Trend» Similar product» Seasonal breakdown (known) Deseasonalise the data and use simple models (eg Exponential Smoothing)

39 ISSUES AND PROBLEMS New products or products with minimal sales history Product succession

40 ISSUES AND PROBLEMS New products or products with minimal sales history Product succession Some forecasts need to be adjusted

41 FORECASTS TO BE ADJUSTED Reasons:

42 FORECASTS TO BE ADJUSTED Reasons: Significant future events

43 FORECASTS TO BE ADJUSTED Reasons: Significant future events Forecasts are not politically acceptable

44 FORECASTS TO BE ADJUSTED Reasons: Significant future events Forecasts are not politically acceptable System overreacts to short term trends

45 FORECASTS TO BE ADJUSTED Reasons: Significant future events Forecasts are not politically acceptable System overreacts to short term trends Solutions: Online editing of forecasts

46 FORECASTS TO BE ADJUSTED Reasons: Significant future events Forecasts are not politically acceptable System overreacts to short term trends Solutions Online editing of forecasts Quickly find potential problems

47 FORECASTS TO BE ADJUSTED Reasons: Significant future events Forecasts are not politically acceptable System overreacts to short term trends Solutions Online editing of forecasts Quickly find potential problems» Displaying forecasts

48 FORECASTS TO BE ADJUSTED Reasons: Significant future events Forecasts are not politically acceptable System overreacts to short term trends Solutions Online editing of forecasts Quickly find potential problems» Displaying forecasts» Analysis of how successful previous forecasts have been

49 FORECASTS TO BE ADJUSTED Reasons: Significant future events Forecasts are not politically acceptable System overreacts to short term trends Solutions Online editing of forecasts Quickly find potential problems» Displaying forecasts» Analysis of how successful previous forecasts have been Specify model(s) for future forecasts

50 ISSUES AND PROBLEMS New products or products with minimal sales history Product succession Some forecasts needed to be adjusted The selection criteria of the best model

51 ISSUES AND PROBLEMS New products or products with minimal sales history Product succession Some forecasts needed to be adjusted The selection criteria of the best model Mean Absolute Percentage Error (MAPE) Root Mean Squared Error (RMSE) Akaike Information Criterion (AIC)

52 ISSUES AND PROBLEMS New products or products with minimal sales history Product succession Some forecasts needed to be adjusted The selection criteria of the best model Freak Sales

53 ISSUES AND PROBLEMS New products or products with minimal sales history Product succession Some forecasts needed to be adjusted The selection criteria of the best model Freak Sales Tuning the system

54 ISSUES AND PROBLEMS New products or products with minimal sales history Product succession Some forecasts needed to be adjusted The selection criteria of the best model Freak Sales Tuning the system The number of products to forecast

55 ISSUES AND PROBLEMS New products or products with minimal sales history Product succession Some forecasts needed to be adjusted The selection criteria of the best model Freak Sales Tuning the system The number of products to forecast The number of models (and their variations) to try

56 ISSUES AND PROBLEMS New products or products with minimal sales history Product succession Some forecasts needed to be adjusted The selection criteria of the best model Freak Sales Tuning the system The number of products to forecast The number of models (and their variations) to try The number of periods of sales history to use as input

57 ISSUES AND PROBLEMS New products or products with minimal sales history Product succession Some forecasts needed to be adjusted The selection criteria of the best model Freak Sales Tuning the system The number of products to forecast The number of models (and their variations) to try The number of periods of sales history to use as input The speed and availability of the machine

58 STRENGTHS CONCLUSION

59 CONCLUSION STRENGTHS Saves time

60 CONCLUSION STRENGTHS Saves time Generally produces good forecasts

61 CONCLUSION STRENGTHS Saves time Generally produces good forecasts Unbiased & Apolitical

62 CONCLUSION STRENGTHS Saves time Generally produces good forecasts Unbiased & Apolitical Input into budgeting

63 CONCLUSION STRENGTHS Saves time Generally produces good forecasts Unbiased & Apolitical Input into budgeting Forecasts can be exported directly to other systems

64 CONCLUSION STRENGTHS Saves time Generally produces good forecasts Unbiased & Apolitical Input into budgeting Forecasts can be exported directly to other systems WEAKNESSES

65 CONCLUSION STRENGTHS Saves time Generally produces good forecasts Unbiased & Apolitical Input into budgeting Forecasts can be exported directly to other systems WEAKNESSES Doesnt produce perfect forecasts every time

66 CONCLUSION STRENGTHS Saves time Generally produces good forecasts Unbiased & Apolitical Input into budgeting Forecasts can be exported directly to other systems WEAKNESSES Doesnt produce perfect forecasts every time Doesnt know the future

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