Forecasting of demand is the art of predicting demand
for a product or a service at some future date on the
basis of certa...
Types of forecasts
 There are long-term forecasts as well as short-term
forecasts.
 Operations managers need long-range ...
 Since forecasting forms an integral part of
planning and decision-making , production
managers must be clear about the h...
Importance of Demand forecasting
 Determination of sales territory.
 To decide to enter a new market or not.
 To determ...
 To assess the effect of a proposed marketing
programme.
 Helpful in the product mix decisions.
 To decide the promotio...
Criteria of good forecasting
Method
 Simplicity and ease of comprehension.
 Economy
 Availability
 Durability

 Accur...
Methods of demand forecasting
 I. Opinion polling.
 II. Statistical method.
 Opinion polling method:
 1. Consumer surv...
 Consumer survey method:
 Complete enumeration.
 Sample survey test.
 End use method.
Statistical method
 Time series analysis.
 Barometric method.
 Regression analysis.
 Simultaneous equation method.
 Time series analysis:
 Chronologically arranged continuous past data.

 Trend analysis method.
 Least square method.
...
 Dt-1= Actual demand for periodt-1.
 Eg: F July= α DJune + (1- α)F June
 Strategies for developing aggregate plans:
 T...
 Trend projection method:
 These are generally based on analysis of past sales

pattern.
 Least squares method: certain...
MOVING AVERAGE METHOD:
 This method is based on the assumption that the
future is the average of past achievements.
 Hen...
 Customer needs demand forecasts competition.
 Financial conditions of the firm.
 Labour training capacity.
 New produ...
Barometric techniques:
 Under the barometric technique one set of data is used

to predict another set.
 In other words,...
Simultaneous equation method
 In this method, all variables are simultaneously

considered with the conviction that every...
Correlation and regression
methods:
 Correlation and regression methods are statistical

techniques.
 Correlation descri...
regression analysis
 An equation is estimated which best fits in the sets of

observations of dependent variables and ind...
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Demand forcasting

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Demand forcasting

  1. 1. Forecasting of demand is the art of predicting demand for a product or a service at some future date on the basis of certain present and past behavior patterns of some related events. Forecasting is used in process design, capacity and facilities planning, aggregate planning scheduling inventory management etc
  2. 2. Types of forecasts  There are long-term forecasts as well as short-term forecasts.  Operations managers need long-range forecasts to make strategic decisions about products, processes and facilities. Long tem forecasts are used to make location, layout,and capacity decisions.  They also need short-term forecasts to assist them in making decisions about production issues that span only the next few weeks.
  3. 3.  Since forecasting forms an integral part of planning and decision-making , production managers must be clear about the horizon of forecasts-month or year, for example, additionally they must also be clear about the method of forecasting and unit of forecasting
  4. 4. Importance of Demand forecasting  Determination of sales territory.  To decide to enter a new market or not.  To determine how much production capacity to be builds up.  Helpful in deciding the number of salesman required to achieve the sales objective.  To prepare standard against to which measure performance.
  5. 5.  To assess the effect of a proposed marketing programme.  Helpful in the product mix decisions.  To decide the promotional mix.  To assess the effect of a proposed marketing programme.  In deciding the channels of distribution and physical distribution decision.
  6. 6. Criteria of good forecasting Method  Simplicity and ease of comprehension.  Economy  Availability  Durability  Accuracy
  7. 7. Methods of demand forecasting  I. Opinion polling.  II. Statistical method.  Opinion polling method:  1. Consumer survey method.  2. Sales force opinion method.  3. Delphi method.
  8. 8.  Consumer survey method:  Complete enumeration.  Sample survey test.  End use method.
  9. 9. Statistical method  Time series analysis.  Barometric method.  Regression analysis.  Simultaneous equation method.
  10. 10.  Time series analysis:  Chronologically arranged continuous past data.  Trend analysis method.  Least square method.  Moving average method  Exponential smoothing.:α Dt-1+(1- α)Ft-1  α = Exponential smoothing constant (0 to1).  Ft= forecasting period.
  11. 11.  Dt-1= Actual demand for periodt-1.  Eg: F July= α DJune + (1- α)F June  Strategies for developing aggregate plans:  The aggregate plan is developed after careful consideration of the different Variables which influence the production plan.  Similarly the aggregate plan also influenced by no. of factors.
  12. 12.  Trend projection method:  These are generally based on analysis of past sales pattern.  Least squares method: certain statistical formulae are here to find the trend line which best fits the available data.  The trend line is the basis to extrapolarate the line for future demand for the given product or service on graph.
  13. 13. MOVING AVERAGE METHOD:  This method is based on the assumption that the future is the average of past achievements.  Hence based on past achievement, future is predicted.  When the demand is stable this method can provide good forecasts.  The main issue in moving averages is determining the ideal number of periods to include the average.
  14. 14.  Customer needs demand forecasts competition.  Financial conditions of the firm.  Labour training capacity.  New products product design changes Machines.  Suppliers capability storage capacity material availabity.  Machine capacity, workforce capabilities.
  15. 15. Barometric techniques:  Under the barometric technique one set of data is used to predict another set.  In other words, to forecast demand for a particular product or service, use some other relevant indicator of future demand.  Ex: the demand for cable TV may be linked to the number of new houses occupied in a given area.
  16. 16. Simultaneous equation method  In this method, all variables are simultaneously considered with the conviction that every variable influences the other variables in an economic environment.  It is a system of ‘n’ unknowns. It can be solved, the moment the model is specified because it covers all the unknown variable. It is also called complete systems approach to demand forecasting.
  17. 17. Correlation and regression methods:  Correlation and regression methods are statistical techniques.  Correlation describes the degree of association between two variables such as sales and advertisement expenditure. When two variables are tend to change together, then they are said be correlated.  The extent to which they are correlated is measured by correlation coeffient.  Of these two variables, one is a dependent variable and the other is independent variable.
  18. 18. regression analysis  An equation is estimated which best fits in the sets of observations of dependent variables and independent variables .  The best estimate which best fits in the sets of observation of dependent variables and independent variables.  the best estimate of the underlying relationship between these variables is thus generated.  The dependent variables is then forecast based on this estimated equation for a given value of the independent variable.

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