The “greedy search” for the optimum product design
A product is made up of many different characteristics. Hair dryers, for example, are available in various shapes and colours with different attachments, heat settings and motor types. Each of these characteristics affects the customer’s decision as to whether or not to buy.
The composition of characteristics that go to make up a product is the product design. Launching new products is a very costly business. Failure is not an option, and an optimum design is crucial in avoiding it. Innovation is also important for existing products, and there is a lot to be gained from simply adapting some of the features.
Tailor-made optimisations of product designs
A useful method of determining whether customers would buy a particular product is a conjunct analysis. Respondents are given a set of products and asked to choose their favourite. This is repeated until it becomes clear to what extent the customers value each feature. The aim is then to decide on the characteristics and pricing that will maximise profit, market share or both. In a market with two simple products, this can often be done manually. But once a company offers a range of different and more complex products in a large market, more advanced methods become key. In the example of hair dryers, we are dealing with as many as forty different product types, all unique combinations of 14 characteristics.
Standard optimisers are not suitable for problems of this kind, so at Blauw we apply methods that lend themselves to optimising product design. The use of ‘greedy search algorithms’ has been found to work well.