Sales forecasting techniques

Presentation on Qualitative and Quantitative Techniques of Sales Forecasting

1. Presented By Lok Bdr. Khatri Roll no.- 7 LBCHS B.PHARMACY Batch- 2016 Sales Forecasting Techniques

2. Sales Forecasting Estimates of future sales of a company’s product for a specific period. A sales forecast is a projection of the expected customer demand for products or service at a specific company, for a specific time horizon and with certain underlying assumptions. Essential tool used for business planning, marketing and general management decision making.

3. Importance of Sales Forecasting Enable a business or organization to work systematically. Enables the production manager to set target for his workers. Helps to determine the production capacity that is actually required. Helps to cut down wasteful expenditure.

4. Sales Forecasting Methods I. Qualitative Method - subjective in nature since they rely on human judgment and opinion II. Quantitative Method - utilizes significant amount of data, equations, statistical models

5. I. Qualitative Methods Jury of Executive opinion or Expert’s Opinion Delphi Technique Sales force Composite Survey of Buyers Intention

6. II. Quantitative Methods Moving Averages Method Exponential Smoothing Decomposition Naïve/Ratio Method Regression Analysis

7. QUALITATIVE METHODS

8. 1.Jury of Executive Opinion Probably the oldest approach to forecasting. Most widely used and relatively quick Group estimates demand by working together. The group has executives from different departments like marketing, sales, marketing research, finance, production, operations,etc who are experts in that area. Each member is asked to provide an estimate of future sales with written justification. The opinion are then analyzed.

9. 2.Delphi Method Delphi method also gathers, evaluates and summarizes expert opinions as the basis for a forecast. The procedure includes selection of panel of experts from within or outside the organization with a Delphi coordinator. The coordinator asks each expert separately to make a forecast on some matter. Group of experts used but they are kept apart from each other so that their opinions are established independently. They prepare individual forecasts, the coordinator then summarizes the forecasts into a report and send to each panel members. The experts are then asked to make another prediction separately on the same matter, with the knowledge of the forecasts of the other experts on the panel. This process continues until a consensus forecast of the future emerges.

10. 3.Sales Force Composite Method Also known as “Grassroots Approach” Individual salesperson forecast sales for their territories. Individual forecasts are combined and modified by the sales manager to form the company sales forecast. It is considered very valuable management tool and is commonly used in business and industry throughout the world. A major disadvantage is that sales people might be a poor judge of future sales level or market conditions. They can have bias opinions as well.

11. 4.Survey of Buyer’s Intentions Forecast survey of a limited and well-defined group of buyers. Applicable to situations in which potential purchaser are well defined and limited in number, such as industrial markets. Process includes asking customers about their intentions to buy the company’s product and services. The information collected from buyers help the company to make effective decisions not only in sales and marketing areas but also on production, research and development.

12. QUANTITATIVE METHODS

13. Moving average method In this method of forecasting, the moving averages of the company sales of the previous periods are calculated for forecasting the sales of the future periods. The formula used is: Sales for next year = Actual sales for past 3 or 6 years Number of years (3 or 6) When a forecast is developed for the next period, the sales in the oldest period is dropped from the average and is replaced by sales in the newest period.

14. Exponential Smoothing Used for short run forecasts Instead of weighing all observations equally in generating the forecast, exponential smoothing weighs the most recent observations Next year’s sale= α (this year’s sale) + ( 1- α )( this year’s forecast) α is smoothing constant taken in scale 0-1

15. Exponential Smoothing F t = α D t-1 + (1 – α ) F t-1 where, α = Smoothing coefficient typically α = 0.2 or 0.3 work well D t-1 = Actual demand for recent period F t-1 = Demand Forecast for recent period F t = Forecast of next period demand

16. Example: One of the two wheeler manufacturing company experienced irregular but usually increasing demand for three products. The demand was found to be 420 bikes for June and 440 bikes for July They use a forecasting method which takes average of past year to forecast future demand. Using the simple average method demand forecast for June is found as 320 bikes ( Use a smoothing coefficient 0.7 to weight the recent demand most heavily) and find the demand forecast for August. Solution: F t = α D t-1 + (1 – α ) F t-1 For July: = 0.7(420) + (1-0.7)320 = 294 + 96 = 390 units For August: = 0.7(440) + (1-0.7) 390 = 308 + 117 = 425 units

17. Naïve or Ratio Method It is a forecasting method which is based on the assumption that what happened in the immediate past will continue to happen in the immediate future. The simple formula used as follows: Sales Forecast for the Next year = Actual Sales of this year X Actual Sales of this year/ Actual Sales of Last year Example: Actual sales of this year (2020) is Rs 956 million and the actual sales of last year (2019) was Rs 948 million. The next year (2021) sales forecast would be = 956 * 956/948 = Rs 964 million

18. Decomposition method This is one of the methods of sales forecasting in which the company’s period of sales data are broken down ( or decomposed) into major components, such as trends, cycle, seasonal and erratic events. These components are then recombined to forecast the sales for the future period.

19. Regression Analysis It is a statistical method of sales forecasting that derives an equation based on relationship between the company sales(dependent variable, x) and independent variables or factors ( y1, y2 ) which influence the sales. Simple regression analysis : Forecasting technique using only one independent variable. Multiple regression analysis : forecasting technique using two or more independent variables. Technically complex

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