AN AUTOMATED SALES FORECASTING SYSTEM

AN AUTOMATED SALES FORECASTING SYSTEM

Sales Forecasting Example 80000 60000 40000 20000 0 Jun-91 Jun-92 Jun-93 Jun-94 Jun-95 Jun-96 Date

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Italian German From Bavaria

Sales Forecasting Example 80000 60000 40000 20000 0 Jun-91 Jun-92 Jun-93 Jun-94 Jun-95 Jun-96 Date

Sales Forecasting Example 80000 60000 40000 20000 0 Jun-91 Jun-92 Jun-93 Jun-94 Jun-95 Jun-96 Date

REQUIREMENTS Regular weekly and monthly forecasts

REQUIREMENTS Regular weekly and monthly forecasts Input directly into production scheduling

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

THERE IS NO FOOLPROOF WAY OF AUTOMATICALLY PRODUCING PERFECT FORECASTS

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

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

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

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

WHY GO TO ALL THIS EFFORT?

WHY GO TO ALL THIS EFFORT? Reduced Inventory Levels

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

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

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

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

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

METHODOLOGY

METHODOLOGY Bottom up

Sales Customer Example 250 200 150 100 50 0 Jan-92 Jan-93 Jan-94 Jan-95 Jan-96 Date

METHODOLOGY Bottom up Top down

Sales Forecasting Example 80000 60000 40000 20000 0 Jun-91 Jun-92 Jun-93 Jun-94 Jun-95 Jun-96 Date

ISSUES AND PROBLEMS

ISSUES AND PROBLEMS New products or products with minimal sales history

Sales Product Example 1000 900 800 700 600 500 400 300 200 100 0 Jan-92 Jan-93 Jan-94 Jan-95 Jan-96 Date

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

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

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

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

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

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

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)

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)

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

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

FORECASTS TO BE ADJUSTED Reasons:

FORECASTS TO BE ADJUSTED Reasons: Significant future events

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

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

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

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

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

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

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

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

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)

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

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

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

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

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

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

STRENGTHS CONCLUSION

CONCLUSION STRENGTHS Saves time

CONCLUSION STRENGTHS Saves time Generally produces good forecasts

CONCLUSION STRENGTHS Saves time Generally produces good forecasts Unbiased & Apolitical

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

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

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

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

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