Parallels are drawn between BI, big data, and predictive analytics in that they all work well toward making operational decisions while being unable to offer anything for making strategic decisions. Traditionally, the process of decision-making is identifying the available options, understanding the consequences of each option, rating options based on preferences for those consequences, and finally selecting an option based on rules and settings. BI does not always apply terrifically to this process, as Awati states:
However, as I have discussed in a post on the nature of decision making in organisations, in the case of complex decisions not only is it hard to identify all options and their consequences, even preferences and/or selection rules may change as one’s knowledge of the options improves. As a consequence, such decisions necessarily involve informal reasoning – a deliberative process that takes into account partipants’ values and beliefs, in addition to logic and “hard facts”. The important point, as Tim van Gelder notes in a brilliant post entitled, “The missing “I” in BI,” is that none of the BI suites in the market support informal reasoning. The lack of support is especially strange because there are well-known techniques such as Issue Based Information System (IBIS) and Argument Mapping that can be used to facilitate and capture such reasoning.
Where complexity and non-programmable decisions are concerned, capturing and storing decision rationale becomes difficult under the current structure of BI. Until changes are made, BI will continue to be the domain of operational decision-making only. Call a spade a spade, and call a spoon a spoon.