Analytic groups within an organization have a bewildering array of tools and technologies available to them, from relational databases, search plus advanced statistical modelling, to name a few. The majority of these tools have been designed to allow one or more types of questions to be answered easier than before, yet these organizations are still facing the same fundamental problems:
What if your BI organization can reduce this backlog, by opening the data to more resources while increasing the number of questions types that can be answered?
Juxtaposed to the BI group is the organization as a whole, in many cases the questions they need to answer are getting more complicated, through both internal and external drivers, that may include, some of the following:
Each point on the graph represents a question, or set of questions can be answered, with a value based on the vertical position and the appropriate cost of answering that question, based on the horizontal position. For each question there is an associated risk of low, medium and high, this represents whether the organization can guarantee they know the outcome. This demonstrates that high cost, high value questions typically are risky to answer as the outcome cannot be guaranteed.
Two observations about this graph, high value answers normally require a higher investment, but are not guaranteed to get the result required. For instance during a merger a lot of IT investment is required, but it might not give the expected increase in revenue. As the IT investment is high to answer these questions, the chances are they will not be asked, or they will be answered subjectively.
Organizations are inherently looking for a chart similar to the one below, where really the cost of each question is drastically reduced, essentially allowing more questions to be answered and the break-even for each becomes a lot lower.