sales forecast
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Sales Forecast
Definition Estimation of sales, in a future period under an assumed set
of economic and other factors
Sales forecast help an organization to determine accurately the market demand for products, customer tastes & usage patterns
It predicts, how much of a company’s particular product can be sold during a future period under a given market program & assumed set of factors
Sales forecasting, according to Cundiff and Still, is “an estimate of sales during a specified future period which is tied to a proposed marketing plan and which assumes a particular set of uncontrollable and competitive forces.”
Cont….
1. Defining the objectives to be achieved.
2. Dividing various products into homogeneous groups.
3. Analysing the importance of various factors to be studied for sales
forecasting.
4. Selecting the method.
5. Collecting and analysing the related information.
6. Drawing conclusions from the analysis made.
7. Implementing the decisions taken.
8. Reviewing and revising the sales forecasting from time to time.
Steps in Sales Forecasting
Sales Forecasting Methods Qualitative Methods
User Expectations Jury of Executive opinion Method Sales force Composite Delphi technique Market test
Quantitative Methods Time series analysis Moving average Exponential Smoothing Regression and correlation analysis
Qualitative Methods…..
Users expectation Normally carried for industrial products, having less
number of customers & product is well defined.
Here customer requirements are found out by directly meeting the customers
Through simples questionnaires
Advantages: Direct contact with costomers
Disadvantage: Under/overestimate the requirement without considering
the changes in business environment
Sales Force CompositeThis method is also called BOTTOM-UP approach or GRASS ROOTS
approach Derived by taking an estimate of expected sales in the forecast
period from each salesperson
Forecast here is based upon experience and expectations of the sales person
Advantages: Done by salespeople who are closest to market Detailed estimates(customer,product,territory)
Disadvantage: salesperson might sometimes over or under estimate The salesperson might not consider the overall environment while
forecasting
Jury of Executive opinion Method
Oldest,simplest & most widely used method. This method includes getting the views of
TOP EXECUTIVES regarding Sales. Sales forcasts are either taken by average of
all individual opinions or through discussions Executive opinions are based either on some forcasting
method or based on experience,judment & intuition.
A study of 150 companies found that 86% cos use this method.
Advantages: Quick and easy Less expensive Popular among small & mediun type cos.
Disadvantages: Unscientific Subjective Difficult to break down the sales into sub units
(region,branches) inaccuracies may be there as these people are not in direct
contact with the market
Delphi TechniqueThis method is developed by Rand Corporation during late 1940.
Experts(within & ouside the organisation) are asked to forecast the sales of an organization
Experts are usually from universities, govt. institutions, industry etc Opinion of all experts are combined and an average figure is taken out Experts are kept informed about the general opinion of the group, so that
they an modify their decision This continues till consensus is reached
Advatages: Useful for new products
Disadvantage: Difficulty in getting a panel of experts Longer time for getting consensus Break down into product territories is not piossible
Market Test used for forcasting sales for new product,where no historical data is
available.
Here, the product is tested in a limited area to find out about consumer acceptance of the product
Based on sales in that particular market, future sales are forecasted
Generally those cities are chosen which represent the country as a whole
Customer’s reaction in that particular market is taken as a base for forecasts of overall sales of the product in the country as a whole
3 major methods used are: Full blown Test Markets Controlled Test Marketing Slimulated Test Marketing
Full Blown Test Markets Co. chooses 2 to 6 representative cities,does full promotional
campaign,similar to what would be done at National level. Duration varies from few months to 1 yr,depending upon
repurchase period of new product buyers surveys are carried out to know about consumer
attitude,usage and satisfaction towards the product. If results show high trails & repurchase rate product is
launched nationally If results show high trail & low repurchase rate product is
redesigned or dropped If results show low trail & high repurchase rate product is
acceptable If results show low trail & low repurchase rate product is left
out permanetaly
Controlled Test Marketing: Co.hires a research firm & gets the panel of stores at specified
geographical location Research firm delivers the new product to the panel
stores,arranges for the promotion at stores & measures the sales also.
Research form also interviews the sample consumers to know the perception about the new product.
Stimulated Test Marketing: In ths 30-40 shoppers are selected,based upon their brand
Familiarity,preferance in a paticular product category eg Babycare
They are shown print advertisements & commercials of well know brands and also of new product.
The shoppers are given small amt of money & asked to buy any item in the store.
Researches co.notes how many buy the new product & how many competing product
Later consumers are intervied to find reasons for buying or not buying,after usage of product their satisfaction Level &repurchase intention
New product is not exposed to competitors
Advantages: Forcasting sales for new products Helps co. to decide whether to launch the product
nationally
Disadvantage: If the repurchase period is long,it is difficult for the co.to
wait for results
For industrial products the test marketing is done by:
Alpha testing(within the organisation) Beta testing(outside the organisation)
Example:infosys did beta testing for its banking software,to check if it’s fit for multiple billion dollar US market
Another method cos can use is Industry Trade Shows
Quantitative Methods….
Time Series Analysis/Decompostion method
Here future trends are estimated based on organization's past performance
Method normally used for long term forecasts i.e. 10yrs & above Sales are broken down into 4 major components
Trends Cyclic variations Seasonal Erratic events
Sales = T X C X S X I where T=Long term variations, C=Cyclical variations, S=Seasonal changes, I=Irregular/unexpected changes in environment
Companies like Coca Cola use this method.
Assuming that previous yrs sales have been broken down as follows: Growth of 3% due to tech.,population(trend) Increased terroriost activities sales are expected to reduce sales by 5%(erratic event) 10% reduction in sales due to recession in demand(cyclic) 15% increase due to festive season in last quater Sales for 2009 were 956 million
Forecast for 2010 sales are: Trend component shows sales will be985(956*1.03) Sales reduced due to erratic component,will be 936(985*.95) Sales reduced due to cyclic component will be842(936*.90) Quaterly sales will be 210(842/4) Increase in sales in last quarter 242(210*1.15) Sales in rest of 3 quarters 200 million (842
Advantages: Conceptually sound
Disadvantage: Difficult to break the data into various components
Moving Average
Sales are forecasted based on sales of previous year. Here average of sales for several periods is used for projecting
future sales. when a forecast is developed for next period,the sales in the oldest
period is dropped from the average and is replaced by sales in the newest period,hence the name is moving avg
Formula: Sales forcast for nxt yr =actual sales for past 3 or 6 yrs/no of yrs(3 or 6)
If co operates in stable environment 2 or 3 yr avg is most useful If a firm. In a industry operates in cyclic varitions,the moving avg
should use data equal to length of cycle
Moving Averages forecast
Year Actual sales 3 yr moving avg 6 yr moving
1997 840
1998 880
1999 864
2000 832 861
2001 862 858
2002 948 852
2003
2004
956 880
922
871
890
Advantages: Relatively simple Easy to calculate Widely used for short term/medium term sales forcasts
Disadvantages: Cannot perdict long term sales forecasts accurately Historical data is required Unable to predict the upturn or down turn in market
Exponential Smoothing It is refinement of moving average method. Under this method greater weightage is attached to sales in recent
periods compared to sales of earlier periods Best suited for short term forecasting when market is relatively
stable. Usually of great help in updating quarterly forecasts. Sales forcast for next year =(L)actual sales this yr +
(1-L)this yrs sales forecast
where L is smoothing or probability weighting factor
Sales of 2004 will be 0.2*956+80.8*880=895
Advantages: Simple to operate Useful when data has a trend or seasonal pattern
Disadvantage: Smoothing constant is arbitary Long term & new product forcasting is not possible
Ratio/Naïve method Based upon the assumption that what happened in immediate past will
happen in immediate future
Sales forcast fo next year=actual sales for this year*(actual sales of this yr/actual sales of lat yr)
Sales for 2004 will be 956*(956/948)=964 million
Advantages: SIMPLE TO CALCULATE Requires less data Good for short term forecasts
Disadvantage: Accuracy will be less if past sales have fluctuated considerably
Regression & Correlation Analysis
These are used for forecasting sales of a firm. Regression analysis is used to identify the factors that influence
sales. If there is single independent variable, its called Simple regression
analysis and in case of two or more variables its called multiple regression analysis.
Simple regression analysis is measured by Least Square Method Y=a+bX where Y = dependent variable(sales) Where a =the Yintercept value(the value of Y when X is 0) Where b = avg increment of sales change Where X = independent variable
Correlation analysis is used to measure the degree of relationship between sales(Y) due to change in X
Multiple regression Model
When there are several independent variables.
YF=a+b1*x1+b2*x2….
where x1…xn are independent variables
Selecting a forcasting method
Accuracy For short term forecasts exponential method is
accurate.for long term regression analysis is useful
Costs Type of data available Requirement of software Experience of co.
How to increase forcasting accuracy
Use multiple forecasting Methods Identify suitable method
Regression analysis
Obtain a range of forecasts Minimum estimate Maximum Intermediate
Use software tools
Difficulties associated with Forecasting
Lack of qualified &trained personnel Changing consumer attitudes Fashion & fads Lack of adequate sales history
Factors affecting or Influencing sales forecasting
1. Business Environment
2. Conditions within the industry
3. Internal Conditions of the business Enterprise
4. Socio Economic Conditions
5. Factors Affecting Export Trade
Basic terms
Market Potential/Industry sales forecast It is the maximum expected sales of a given product
or service for the entire industry in a given mkt for a specific period of time
Eg:the mkt potential for Mobile phones in India for the Yr 2010-11 is estimated to be 4 million number
4 major things to be included: Item marketed eg product service Sales estimate in units/value Description of mkt by geographical area or type of
customers A specific time period eg a paticular yr
Market forecast/Mkt size: It is the expected industry sales for a given product or
service at one specific level of industry in a given mkt for a specific period of time.
Eg : mkt forecast for Mobile phones in organised sector in india for yr 2010-11 is 700 crore
Sales potential It is the estimated sales of a given product or service
fo a company in a given mkt for a specific period of time
Eg: Sales