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Demandforecasting

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demand forecasting & techniques

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Demandforecasting

  1. 1. Presenting by - P.JOEL PRAKASH
  2. 2. What is demand Forecasting ?  “PREDICTIONS ARE USUALLY DIFFICULT, ESPECIALLY ABOUT THE FUTURE”  Prediction or estimation of a future situation, under given conditions.  Classified into categories: (i) Passive forecasts (ii)Active forecasts  Important aid in effective and efficient planning  It is backbone of any business
  3. 3. Importance of demand forecasting  Crucial to manufacturer ,wholesaler, retailer  Business decisions  Planning for future finished goods  accurate demand forecasts lead to efficient operations and high levels of customer service  Improve quality & effectiveness of product
  4. 4. Factors determining demand forecasting  Time factor  Level of forecasting  General or Specific forecasting  Problems & methods of forecasting  Classification of goods  Knowledge of different market conditions
  5. 5. Levels of Demand Forecasting 1) Micro Level- Demand forecasting by individuals business firm for forecasting the demand for its product. 2) Industrial Level- Demand estimate for the product of the industry 3) Macro Level- Aggregate demand forecasting for industrial output at the national level- it is based on the national income/ aggregate expenditure of the company.
  6. 6. Types of Forecasts by Time Horizon Short–range Forecast • Usually < 3 months Medium-range Forecast • 3 months to 2 year Long-range Forecast • 2 years Quantitative methods Qualitative methods
  7. 7. Approach of forecasting Qualitative Quantitative FORECASTING
  8. 8. Qualitative Forecasting approach  Obtaining information on likes and dislikes of the consumers  It is short term forecasting  Demand forecasts for new products
  9. 9. Qualitative Forecasting approach I. Consensus approach  Expert Opinion method Forecasting the demand on base of opinion of several experts who are more relevant to that area of interest  Delphi method It is a systematic, interactive forecasting method which relies on a panel of experts
  10. 10. Complete Enumeration survey method Complete survey on all the consumers for commodity Ex: 1.Indians addicted to smartphones, says survey 2. About 70 percent students today own smart phones in cities, according to a survey by software services firm TCS By these survey many young entrepreneurs came forward and setting up there own business Survey approach
  11. 11. Sample Survey Method: Only few consumers are selected and there views are collected Ex: samples of Maggie from different shops of city are collected for testing
  12. 12. End-User Survey Method: Focus on forecasting the demand on intermediary goods Ex: Cement use for construction of houses, buildings, hotels, etc
  13. 13. Sales Force Opinion Survey Method Employees of Company who are the part of sales & marketing teams are asked to predict the demand
  14. 14. Quantitative Forecasting  Forecast of future demand is based on past data & extrapolating it to make the forecast of future levels.  It is long-term forecasting  Demand forecast for existing products can be made by these method accurately
  15. 15. Levels of Approach in Quantitative forecasting  Trend Projection approach  Secular-Trend method: Change occurring consistent over period of time Ex: Sales of PC’S increases over a year  Seasonal-Trend Method: Seasonal variation of the data within a year Ex: raincoats are dependent of weather  Cyclical-Trend Method: Demand for the product that may have a tendency to recur in a few years. Ex: Changes in BSE
  16. 16. Barometric approach This type of approach is constructs an index of relevant economic indicators and forecast future trends on the basis of these indicators. These indicators are leading indicators tells us where we are heading coincident indicators tells us where we are lagging indicators tells us where we lagging behind Commonly Used indicators:- (1) Gross National Income. (2) Employment (3) Agriculture Income (4) Bank Deposits etc. (5) Industrial Production (6) Construction contracts awarded for building materials. (7) Personal Income. Andrew Carnegie the famous industrialist used to estimate the future of steel by counting the no of chimneys emitting smoke in Pittsburg Ex:In 2001, Gujarat earthquake all constructions are collapsed while rebuilding the cement became the leading indicators
  17. 17. Economic approach It is on basics of systematic analysis of economic relationships by combing economic theory with mathematical & statistical tools Regression method: To develop the functional relationship & analyze the values of dependent variables with those of one or more in dependents variables Plain biscuits Savory Biscuits Filled Biscuits Sales of biscuit by category
  18. 18. Simultaneous Method: Incorporates mutual dependences among variables. Ex: demand forecasts on electricity based on many factors
  19. 19. Forecasting Limitations  Change in fashion  Consumer’s Psychology  Uneconomical  Lack of Experts  Lack of past data

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