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Gathering information is a costly procedure and so some attempt at evaluating the worth of the information needs to be carried out before deciding on the level of research expenditure. Common sense indicates that there is no point in spending more money on marketing research than the costs of making a wrong decision and so an attempt must be made to estimate the costs of the decision.

Sometimes this is easy. If a new product is to be launched then the costs of this include all the development costs associated with the product plus the marketing costs associated with its launch. This generally indicates a large cost and is therefore a rationale for considering an expensive research programme. It is more difficult when a decision concerns whether to use one message or another in an advertising campaign. In this case the costs of a wrong decision are extremely hard to quantify, as are the costs of making a right decision.

One approach for deciding how much research information is worth is simply to take a subjective view which attempts to relate the overall amount involved in the project costs to the amount to be set aside for research.

Marketing research expenditure can be looked upon rather like insurance, in that its aim is to reduce risk. Its value is therefore related to the level of risk likely to be incurred: the higher the level of risk then the higher the level of research expenditure appropriate to guard against that risk. In assessing the value of research information most people operate at this subjective and intuitive level. However, some more formal devices offer a framework for putting a monetary value on information costs.

One technique uses theoretical calculations of expected profit from the project with and without availability of prior research information. The basic assumption of the technique is that research information increases the certainty of a particular outcome being achieved and the outcome can be evaluated in terms of expected profit. Expected profit without the benefits of research information is likely to be less than the expected profit after buying research information. The difference in the two calculations puts a monetary value on the reduction of uncertainty produced by the research findings. The implication is that research is worth the difference in monetary values and therefore a research project costing up to that amount would represent a worthwhile investment for the organization.

This technique requires the decision maker to quantify subjective assessments of possible outcome, i.e. to quantify factors that might otherwise be called 'hunches' or 'intuition', or simply 'experience'. This is an advantage because it allows other members of the organization to evaluate and perhaps challenge what might otherwise remain as implicit decision-making processes. The disadvantage of this technique is that it gives a superficial air of elegance and sophistication to what is, in effect, guesswork. However, it does form a useful framework for those who would simply like to work out the numbers as just one way of estimating how much to spend on research. A simplified version of the calculation is shown below.

A manufacturer wishes to decide whether to improve the quality of its product. The improved product will cost more, but it is likely that sales and profitability will increase. If sales increase by 25 per cent, then the product's contribution to profit will increase by £100,000. The manufacturer therefore needs to assess the chances of achieving that 25 per cent sales increase. In a meeting, the experienced senior management team is asked to assess subjectively the probability of achieving the sales increase, i.e. to make a joint 'guesstimate'. The outcome of the meeting is that the management team assesses the probability of achieving the sales increase at 0.4. Expected profit can therefore be calculated at: £100,000 (profit estimate) x 0.4 (chance of making it) = £40,000. However, the company has used research in the past to assist in making sales forecasts, and in its experience has found that, if a particular value is forecast by research then there is a 75 per cent probability of the value being achieved. In this case, then, if the research forecasts a sales increase of 25 per cent, then the probability of its being achieved would be 0.75. Expected profit following the research can therefore be calculated at: £100,000 (profit estimate) x 0.75 (chance of making it, following research) = £75,000.

This calculation indicates that expected profit after research is £35,000 greater than expected profit before research and assumes (oversimplistically) that the sales increase would be maintained for only one year. A research programme costing less than £35,000 would therefore be a worthwhile undertaking, i.e. what this reduction in uncertainty is 'worth'. The two factors in the equation are the value of the decision outcome (in this case profit) and the degree of certainty with which that outcome can be anticipated without conducting research. The higher the outcome value and the higher the level of uncertainty within the organization about achieving it, then the greater the need for, and worth of, research.

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