Forecasting and Decision making

Forecasting and Decision making Just like farming, business decisions too are characterized by risk and uncertainty. Hence, forecasting is generally used by businessmen to facilitate the business decision-making process. In this chapter, we will see how demand forecasting. However, demand forecasting alone cannot assure businessmen of the long-term sustainability and profitability of their business. Businessmen also need to keenly observe the entire business environment to foresee threats arising not only from competitors but also from changes in the economic conditions of the country. Economic forecasting helps businessmen to understand these changes and accordingly formulate business strategies.

ECONOMIC FORECASTING Economic forecasting can be termed as a process of predicting conditions in the economy as a whole or in part. Economic forecasting has many advantages. At the macro level, economic forecasting helps us in estimating the growth of an economy. Economic forecasts assist the Government in taking the steps required to achieve the objective of economic development. Economic forecasting is of vital importance even at the micro level. Firms formulate their strategies based on economic forecasts. For instance, if the forecasts indicate that the economy is growing at a fast pace, then it encourages the businessmen to invest more and improve their profits. Economic forecasting is also essential for individuals as it helps them in making prudent investment decisions

If the forecasts predict that the economy of a country is slowing down, then the Government makes changes in monetary and fiscal policies. A businessman forecasts the business environment in which he is operating and accordingly formulates strategies. For instance, a car dealer is required to estimate the demand for cars and accordingly maintain stocks. The Economy survey, which includes forecasts about the economy, also make some predictions about the economy, and on the basis of these, the Government makes changes in its economic policies to improve the country's economic development. These changes in economic policies are generally seen in the Union Budget of the Government.

In the absence of an economic forecast, it is not possible to make prudent business a investment decisions. The Economic Survey published by the Government also acts as a crucial source of economic statistics. These economic statistics act as a barometer of economic activity and help businessmen and individuals in decision making. Economic statistics that indicate the level of economic activity in a nation are also called 'economic indicators'.

DEMAND FORECASTING In the modern competitive environment, an organization must have some idea about the demand for its products. The high degree of business uncertainty makes it difficult for managers to predict future sales volumes of their products and decide how a company can use its scarce resources effectively. Demand forecasting helps managers to solve these problems to a large extent. Forecasting helps managers to predict the demand and to come up with a proper production mix. Demand forecasting for a particular product or a portfolio of products for a company in a given market is the micro aspect of the forecasting process. It can also be done for various products and services in an economy from the macro perspective. Macroeconomic forecasting includes predicting economic aggregates such as inflation, unemployment, GDP growth, short-term interest rate and trade flows.

Forecasting future demand requires relevant information gathered at the right time. There are several techniques used for demand forecasting. These can be divided into qualitative and quantitative techniques. Qualitative techniques include expert opinion, surveys and market experiments while quantitative techniques are time series analysis and barometric method. Expert Opinion :The expert opinion method, also known as expert consensus method, is being widely used for demand forecasting. This method utilizes the findings of market research and the opinions of management executives, consultants, and trade association officials, trade journal editors and sector analysts. When done by an expert, qualitative techniques provide reasonably good forecasts for a short term because of the expert's familiarity with the issues and the problems involved. There are various methods of confirming the opinion regarding future demand by experts. One of these methods is the Delphi method.

Delphi method: In the Delphi method, the opinion of number of experts is gathered individually. An analyst combines these forecasts using same weighting system and passes on the combined forecast to the forecasters. The forecasters make a new round of forecasts with this information. The process continues till an overall consensus is arrived at from all the panel members. The Delphi method is primarily used to forecast the demand for new products. Though it provides valuable insights, it is rather expensive as the experts may charge a high fee for their opinion.

Survey: Information can also be collected through surveys Survey: Information can also be collected through surveys. Surveys can be carried out through mail, e-mail, telephone or by directly speaking to respondents. Survey bye-mail an phone survey are conducted for prospective customers who are not using a particular product or service of a company. A firm can determine the demand for its products through a market survey. It may launch new products, if the survey indicates that there is a demand for that particular product in the market. For example, Coke in India expanded its product range beyond carbonated drinks, after the company conducted a nationwide survey. The survey revealed that about 80% of the youth preferred to drink tea or coffee rather than carbonated drinks at regular intervals. The remaining 20% preferred to have milk products, while only 2% preferred to drink carbonated drinks like Coke. The survey results helped Coke to expand its product range. Coke introduced coffee and tea in the

Market Experiment One major problem with the survey method is that people may not reveal their true likes and dislikes while giving responses. Responses to direct questions may not always be correct. Market experiments can help to overcome these problems as they generate data before introducing a product or implementing a policy. Market experiments are of two types: 1. Test Marketing , & 2. Controlled Experiments.

Test marketing : In this case, a test area is selected, which should be a representative of the whole market in which the new product is to be launched. A test area may include several cities and towns, or a particular region of a country or even a sample of consumers. By introducing the new product in the test area consumers' response about the product can be judged. More than one test area can be selected if the firm wants to assess the effects on demand due to various alternative marketing mix i.e. changes in price, advertising or packaging can be done in various market areas. Then the demand for the product can be compared at different levels of price and advertising expenditure. In this way, consumer's response to change in price or advertising can be judged.

Some of the drawbacks of test experiments are that they are very costly and much time consuming. If in a test market prices are raised, consumers may switch to the competitor's products. It may be difficult to regain lost customers even if the price is reduced to the previous level. Controlled experiments: Controlled experiments are conducted to test the demand for a new product launched or to test the demands for various brands of a product. In this method, a sample of consumers which are representative of the target market are selected. They are requested to visit the store of that firm where various varieties or brands of the product are kept for sale.

Their preferences are recorded Their preferences are recorded. They are then provided advertising materials for various brands. The selected consumers are given some fixed money and are allowed to make purchases of different variety of products or various brands of a product. The quantity of the product or particular brands of a product purchased by them is recorded. They are also requested to fill a questionnaire asking reasons for the choices they have made. The price of the product or its variety may be changed and the experiment is repeated. Controlled experiments provide more accurate results than consumer surveys. This is because in this case, the consumers are asked to make actual decisions regarding their purchases, while the consumer surveys show their intention to buy. Some of the drawbacks of controlled experiments are that they may be biased in the process of selection of a sample of consumers on which experiments is to be performed.

Quantitative techniques Time Series Analysis: The time series analysis is one of the most common quantitative method used to predict the future demand for a product. Here, the past sales and demand are taken into consideration. The time series analysis is divided into four categories - trends, seasonal variations, cyclical variations and random fluctuations. In trend analysis, past data is used to predict the future sales of a firm. A trend is a long term increase or decrease in the variable. Seasonal variations take into account the variations in demand during different seasons. For example, the sale of the cotton dresses increases in summer, while the sale of woolen clothes increases in winter.

Cyclical variations are the variations in demand due to fluctuations in the business cycle - boom, recession and depression. Random fluctuations may happen due to natural calamities like flood, earthquake, etc. which cannot be predicted accurately. There are two types of time-series analysis - moving average and exponential smoothing. The moving average is a series of arithmetic averages and can be divided into simple moving average and weighted moving average. For example, to predict sales for the next period using a simple moving average. On the other hand, exponential smoothing works on a premise that the most recent occurrences are more indicative of the future than the past ones.

Barometric Analysis: Barometric analysis or forecasting can be defined as "the prediction of turning points in one economic time series through the use of observations on another time series called the barometer or the indicator." In barometric analysis, the economic time series are divided into three groups - leading indicators, coincident indicators and lagging indicators. Leading indicators contain data that move ahead of the series in question. The growing number of senior citizens is a leading series for the demand for home for the aged. Leading indicators index includes such things as average weekly hours worked and claims for unemployment insurance, manufacturers' new orders, stock prices, orders for plant and equipment, index of consumer expectations etc.,

Coincident Indicators use data that move up and down corresponding to some other series - for example, the relationship between national income and employment (in the short term). Components of an Index of Coincident indicators are employees on non agricultural payrolls, industrial production, personal income minus transfer payments, manufacturing and trade sales. Lagging indicators move behind the series in question - for example, manufacturer's inventory is a lagging series for sales. The lagging indicator composite includes changes in labor costs per unit, ratio of inventory to sales, and figures on instalment credit and loans, among other items.

RISK AND DECISION-MAKING Risk and Uncertainty : A condition of 'certainty' is said to exist if a businessman is sure about the outcome of a certain business decision. On the other hand, when the outcome of a decision is not known, then such a decision is said to be taken under conditions of risk and uncertainty. Risk is a condition where the firm is aware of all the possible outcomes of a decision. Also, the firm is capable of associating each possible outcome with a probability. Uncertainty is a condition, when the businessman is not able to associate probability to the possible outcomes. Every economic decision involves an element of risk and uncertainty. In fact, risk and uncertainty are an integral part of decision making. Although, one cannot completely eliminate the risk and uncertainty factor in decision making, it can be minimized through proper forecasting and future planning.

Risk: A major distinction between risk and uncertainty is that risk is calculable, whereas, uncertainty is non-calculable. Risk can be defined as a situation where there can be more than one possible outcome to a decision. Further, these outcomes can also be measured. Risk is the distinction between the expected and the actual outcome. The actual outcome is the reward or return for taking decision. For example, the shareholder gets dividend (return) for investing his money in the shares of a company (investment decision). He anticipates that in a particular year the share prices may go up and that he may get more returns. However, the actual returns may be more than his expectations or they may be less than his expectations. Thus, there is an element of risk.

Uncertainty: Uncertainty cannot be measured Uncertainty: Uncertainty cannot be measured. For example, the meteorological department cannot exactly determine the chances of monsoon failure in a particular year. As a result, farmer may be unable to produce much on account of monsoon failure. Further, the farmer may also incur losses in case the produce does not reach the market on time on account of truck strikes or storage damages. In such cases, the risk of loss cannot be calculated. Therefore, uncertainty exists when the risk involved in decision-making is not calculable.

Risk and Decision-making Decision making under risky conditions involves computation of expected values for each strategy. The strategy which has the highest expected value is chosen by the decision maker. When two or more strategies display same expected values, then the decision is made based on the degree of risk involved in both the strategies. Degree of risk indicates the extent to which the pay-off of a strategy deviated from the expected value. The degree of risk can be calculated with the help of the spread or variation in the probability distribution Thus, a precise measurement of risk is provided by standard deviation'.

Uncertainty and Decision-making Uncertainty can be reduced by using non-quantitative methods like hedging', acquiring monopoly status, product diversification, monitoring the marketing environment, etc. A condition of uncertainty may be converted into a condition of risk, if the decision maker is capable of identifying the possible outcomes and also estimate and assign probabilities to each strategy. He may also assign equal probabilities to each strategy instead of guessing the probabilities to be assigned to each strategy. There are several quantitative criteria that help decision makers to reduce the risk involved in decision-making under conditions of uncertainty.

Maximax criterion: In the maximax criterion, the decision maker has an absolutely optimistic view about the outcomes or pay-offs. He is concerned about only the most promising outcome or outcomes (among all the possible strategies or pay-off matrix) and ignores the other possibilities. The decision maker selects that strategy which according to him is 'best among the best'. However, the maximax criterion may sometimes suggest the same strategy as the one suggested by maximin criterion.

Maximin criterion: The maximin criterion takes a conservative approach to decision making. In this criterion, the decision maker is pessimistic about the outcomes and anticipates that the worst will happen. He considers the worst possible outcomes from the pay-off matrix. The decision maker then chooses that outcome which maximizes the minimum payoffs. An important assumption made under this criterion is that the decision maker does not have any access to meaningful information that can help him assign probabilities to the possible outcomes.

Minimax criterion: This criterion concentrates on the opportunity loss of a particular strategy. Opportunity loss is referred to as 'regret' in this criterion. According to the minimax criterion, the decision maker minimizes the maximum regret that could have been incurred. The decision maker considers the regrets in the pay-off matrix. The regret or opportunity loss of a strategy is given by the difference between a particular outcome or pay-off and the highest possible pay-off for the resulting state of nature.