Predictive ideation?

Most innovations are incremental rather than radical, that is, innovation resulting from improvement to existing designs rather than abrupt change. This may suggest, where innovation is primarily a rational problem-solving process with an emphasis on business viability of the product, that designers be guided by algorithms to optimise innovation. Designers, accordingly, would compile a history of ideas taking as its basic unit of analysis the unit-idea, or the individual concept, then instruct algorithms to search for indirect and non-obvious correlations in the data to help identify and develop innovative ideas. For example, a US website developer has developed an algorithm to analyse and rate pop music providing predictive insights into "number one" record hits. The algorithmic approach to innovation, however, is not new - for example, the theory of inventive problem solving (TRIZ), or multidisciplinary design optimisation (MDO) in a range of industries, and the application of algorithms is now part of everyday life, from internet searches to financial trading to climate modelling. Although computation cannot fully replace activities that require human judgement, personal preference or true decisions, algorithms make more kinds of knowledge codifiable and therefore may help advance innovation processes and reduce dependence on solely empirical or experimental means of generating design data. In this sense, algorithms can function as an ideation tool.