11_-_Methods_of_Forecasting[1]

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Methods of Forecasting:

1 Methods of Forecasting

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2 Forecasting can be classified into two basic types: Qualitative and Quantitative Qualitative techniques are subjective or judgmental and based on estimate and are based on estimate and opinion. Qualitative / Non-statistical techniques Quantitative / statistical techniques Qualitative / Non- Statistical Methods of Forecasting Grass roots It derives a forecast by compiling inputs from those at the end of the hierarchy who deal with what is begin forecast. For example-an overall sales forecast may be derived by combining inputs from each salesperson, who is closest to his or her own territory Methods of Forecasting

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3 Jury Method / executive opinion Method The jury Method is the commonly applied method of Sales Forecasting (also known Executive Opinion Method), Judgment is the crucial factor in this method. This is true of both – ‘TOP JURY METHOD’ and ‘PERCOLATED JURY METHOD’. In the Top Jury Method, the participants are limited to senior level persons only whereas in the Percolated Jury Method – a large number of Marketing/Sales Executives participate. By a rough averaging of these opinions the final forecast is arrived at. Evidently, the more the participants have a versatile experience and sound knowledge of the business, the more accurate shall be the forecasting. They must be well informed about the overall Economic Environment and the condition prevailing in the country. They should also have the knowledge about the strengths and weakness of their firm.

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4 Merits This is based on judgment and is easy to operate. Gives due weightage to experience judgment of the people who know the market. This method is more suitable for the firms who have to adopt Statistical Techniques in their firms (where past sales and market statistics are not available). Demerit Forecasting is based on “Opinions” and not on “Facts”.

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5 Survey of Expert Opinion Method This method is based on ‘Opinion’ but differs from the Jury Method in the sense that here the experts in the concerned field inside or outside the organisation are approached for their estimates. This method is more useful in developing the total industry forecast that company level Sales Forecast. Sales Force composite Method As per the Sales Force composite Method, the Sales Forecasting is done by the Sales Force. It is also a judgement based method. Each salesman develops the forecast for his respective territory; the territory based forecast are consolidated at branch/area/region level; and the aggregate of all these forecasting is taken as the Corporate Forecast.

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6 Merits & Demerits of sales composite method are- Merits As the method is a grass root method, it is a micro level and hence more close to the values likely to be. As customers in proximity to salesmen, hence their opinions are also figuring here and hence more reliable in prediction. As the salesmen themselves do it hence they have to commit for the same and easy for implementation for fixing of Sales Quota. The technique takes care of Production and hence easy to do for branch/area wise and month wise and customer wise (Dealer/Distributor) Hence gives a very meaningful Corporate Forecasting and be responsible for better budgets etc. Demerits All salesmen may not be matured and experienced enough and do not possess the knowledge of statistical techniques. As they shall have their sales quota fixed on this, may try to play it safe. Some salesmen are more optimistic and some are more pessimistic. Knowledge of Market conditions and prevailing conditions in the country are also essential for Forecasting

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7 Comparison with jury method: It is similar but differs as in Jury Method only a few Executives participate whereas here all salesmen participate. It is a grass roots method as the forecast is obtained from consumers by sales force / dealers or retailers who are closest to the market. User Expectation Method More suited for industrial products. The method is called User Expectation Method / End Use Method / Survey of Buyers’ intention Method.

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8 Market research Method This method sets out to collect data in a variety of ways (like surveys, interviews) to test hypothesis about the market. This is typically used to forecast long range and new product sales. Market research is used mostly for product research in the sense of looking for new product ideas, likes and dislikes about existing products. The data collection methods are primarily surveys and interviews.

Delphi Method:

9 Delphi Method A qualitative forecasting technique in which a panel of experts working separately and not meeting, arrive at a consensus through the summarizing of ideas by a skilled coordinator. Thus group of experts responds to questionnaire. A moderator compiles results and formulates a new questionnaire which is submitted to the group. Thus there is a learning process for the group as it receives new information and there is no influence of group pressure or dominating individual. The Delhi Method is a fairly new technique where a set of procedures is laid for obtaining and referring the opinions of a group of people. When the experts are asked to about their opinions, usually there is a divergence. To the decision maker, it posses the problem of evaluation of the divergent points view. Also a group of interaction has its drawbacks such at the influence exercised by ;dominant individuals and so on). In Delphi Techniques such drawbacks are kept at a minimum.

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10 Delphi Technique “The Delphi Technique is an iterative process to obtain the most expert opinion of a group of experts. It is essentially a series of intensive interrogation of an individual considered as expert in the relevant area of inquiry, through a number of sounds of “inquiry, response and feedback”. At the end of each round, the responses are sent to the respondents for further inquiry. This is repeated until the convergence of opinion takes place. However at each round the individual responses are kept confidential. In the entire process of study, there is no face to face communication. The anonymity and secrecy of the individuals’ behavior is maintained right through.

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11 Advantages The influence of dominant members and group pressure in expressing opinion is prevented. The respondents are not effected the ‘bandwagon effect’ of a majority opinion. The respondents are free to retreat from an expressed opinion. This technique has been widely and successfully used to forecast the distant future. The basis for the forecast is the respondents’ experience and sense of awareness as an expert. This technique can be used for forecasting both qualitative and quantitative factors. This technique can be used to process both opinion, judgement and exact numeric factors.

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12 The Quantitative Forecasting Method A few major Quantitative Forecasting Methods are: Time Series Time series analysis, is based on the idea that data relating to past demand can be used to predict future demand. Past data may include several components, such as trend, seasonal, or cyclical influences. For example sales figure collected for each of the past six weeks can be used to forecast sales for the seventh week.

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13 Simple Moving Average Method A simple moving average (MA) combines the demand data from several of the most recent periods, their average being the forecast for the next period. This technique retires the old data and inducts fresh data into its calculation at every forecasting period to keep calculated current. MA = Sum of demands for periods Chosen number of periods

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14 Weighted Moving Average Method An averaging method that allows for varying weighting of old demands. This model allows uneven weighting of demand. Thus specific points may be weighed more or less than the others, as seen fit by experience. WMA = Each period’s demand times a weight, summed over all period’s in the moving average An advantage of this model is that it allows to compensate for some trend or seasonality fitting the coefficients C.

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15 Exponential Smoothing An averaging method that exponentially decreases the weighting of old demands. These are well known and often used in operations management because they are readily available in standard computer software packages and they require relatively little data storage and computation which is an important consideration during forecasting. Thus recent data points are weighted more with weighting declining exponentially as data become older. It is the most used of all forecasting techniques. Advantages of this technique are Exponential models are surprisingly accurate. Formulation an exponential model is relatively easy. Little computation is required to use the models.

Trend Projection:

16 Trend Projection It fits a mathematical trend line to the data points and projects it into the future. Regression Analysis It fits a straight line to past data generally relating the data value to time. And most common fitting technique is least squares which is discussed below. Method of Least Squares This is the most popular method of fitting a trend line to the sales data. This method is a mathematical device which places a line through a series of plotted points in such as way that the sum of the squares of the deviations of the actual points above and below the trend line is at the minimum. The method, therefore, is called the Method of Least Squares and gives the line of the best fit. Advantages : The method is free from personal prejudice and bias. Different persons working with this method will get the same result. Trend values can be obtained for all the years. The method gives the very satisfactory results as the sum of the squares of deviations is the least.

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