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
Importance of demand forecasting Crucial to supplier, manufacturer or 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
Levels of Demand Forecasting1) 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 industry3) Macro Level- Aggregate demand forecasting for industrial output at the national level- it is based on the national income/ aggregate expenditure of the company.
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 Other factors
Approach of forecasting Qualitative FORECASTING Quantitative
Qualitative Forecasting approach I. Judgmental approach Surveys Consensus methods Delphi method II. Experimental approach Test marketing Customer buying database Customer panels
Advantages & Disadvantages ofQualitative ForecastingAdvantages :-o Ability to predict changeso Flexibilityo AmbiguityDisadvantages :-o Accurate forecast is not possibleo Judgmental approacho False/ inadequate information
Quantitative Forecasting Approach Relationship approach Econometric models Life cycle models Input-output models Time series approach Static models Adaptive models
Forecasting Examples Examples from Projects: Demand for tellers in a bank; Traffic flow at a major junction Pre-poll opinion survey amongst voters Demand for automobiles or consumer durables Segmented demand for varying food types in a restaurant Area demand for frozen foods within a locality Example from Retail Industry: American Hospital Supply Corp. 70,000 items; 25 stocking locations; Store 3 years of data (63 million data points); Update forecasts monthly; 21 million forecast updates per year.