Preferred when there is limited/no historical dataSales force planning: gathering the opinions of salespeople and managers for a particular product or family of products.Frequent contact with customers often provides insight into what customers may be considering for the future and also into customer perceptions of the company and itsproducts.e.g. surveys, analog FC (‘similar’ goods)2. Time-series analysis: a technique that utilizes past demanddata to predict future demand by examining cyclical, trend and seasonal influences.Historical dataand the assumption that past patterns will continue in the future.Goal: identify underlying patterns of demand and develop a model to predict these patterns in the futuree.g. average changes (FY -1)3. Causal relationships: a technique that identifies a connectionbetween two factors, one that precedesand causes changes in the second or effect factor.(one or more factors are related to demand and that relationship between cause and effect can be used to estimate demand)e.g. X affects YExamples of FC methodsMarket research is a systematic approach to measuring customer interest in a service or product through data-gathering surveys.Market research is widely used for new products, for which we have existing similar products. Note: it has a high degree of uncertainty and must be interpreted with caution.E.g. focus groupsNaïve forecast:A method of forecasting that uses the demand for the current period as the forecastfor the next period
Very simple and low cost to use.Works best when demand, trend and seasonal patterns are stableand there is relatively little random variation.Casual Methods: available historical datasuggest a relationshipbetween the forecasted item and some factorIncreased government grants for solar panel and greater demand for installers.Cyclone season and price of bananasIncreased rain fall and demand for umbrellas.Sunshine and sales of ice-creamCausal methods employ mathematical techniques to relate one or more independent variables to the variable being forecast.Moving Average: A technique for estimating the average of a demand series and filtering out the effects of random variationDeveloping a moving average involves computing the average of nprevious periods of demand and then using this as the estimate for the next period of demand.The average is updated after every period to include the most recent demand data.Demand Forecasting Issuesforecasting techniques depend on factors, such as:osituation at hand (judgmental forecasting is appropriate)oforecasting costs in terms of time and money (are associated with each particular forecasting technique)oaccuracy of various forecasting techniques.Forecasting accuracy= relationship between actual and forecasted demandoaccuracy can be affected by various considerations.