The starting point for creating a research design should be an understanding of which decisions need to be made. Examples of the type of decisions that research is used to address are:
- Should a pack of chewing gum change from 10 to 12 pieces?
- Should a vegetable juice replace its glass bottles with plastic bottles?
- Should an airline replace its economy seats with stand-up beds?
- Who is the best Republican candidate for President?
- How many phone plans should a company offer?
- Which of 10 new product ideas should be further investigated?
- Should a company replace its American call centers with call centers in India?
- What is the best way to reduce consumption of alcohol?
It is rare that research can actually provide a definitive answer to such questions. Rather, it provides data for a business case. For example, research can provide an estimate of the impact of sales that occurs when a pack of gum is increased by two pieces, and this is combined with the company’s cost data to work to create a business case for the change in pack size.
A key thing to keep in mind when working out which business decisions need to be addressed by research is that the more precisely a firm can identify the key decisions, the more precise the resulting estimates. A firm that is able to specify that it wants to understand the impact on sales of changing its pack of gum from 10 to 12 pieces has a good chance of conducting research that is sufficiently accurate to help make this decision. However, if the same firm says that it wants to “understand the consumer value equation for gum, in terms of how consumers trade off price, pack size, multipacks, flavours and health benefits” it will end up with a much less precise estimate of the impact of a change in the number of pieces and thus risks making worse business decisions.[note 1]
Once the relevant business decisions have been identified and a list of things to be estimated has been created, the next step is to create any appropriate models, as these will lead to the identification of further estimates that are required. For example, the figure below shows a model and information needs for a banking study aimed at increasing acquisition and retention. Where the model has not been proposed by the client – and it is rare they are proposed – the researcher then needs to create or find useful models. Usually, one or more of three different types of models are required: models of behavior change, measurement models and decompositions. We now discuss each in turn.
- There are lots of different reasons why this is the case. There are statistical reasons relating to degrees of freedom, multiple comparison error and, when statistics are required for different sub-groups, sample size. There are cognitive reasons relating to respondents providing less accurate data in longer interviews. There are instrument design reasons, with smaller number of decisions being able to be tested with better quality instruments (e.g., adding pictures to questionnaires). There are researcher effort reasons, with researchers needing to concentrate on a single decisions being able to allocate more time to this.