This vendor-written piece has been edited by Executive Networks Media to eliminate product promotion, but readers should note it will likely favour the submitter's approach.
For as long as I've been involved with the field, the hard-headed school of "we need a cost benefit analysis" or "build me a return on investment (ROI) justification" has defined the business-benefit of Business Intelligence (BI) as mainly its ability to "speed up and improve decision making."
With the rise of self-service BI, the first part of that aspiration has been successfully satisfied. People are getting decision-relevant data quickly. However, the second outcome -- improved decision making -- is a less certain result (and also much harder to model in an ROI calculation than is agility).
What is it that really makes the difference when it comes to decision-making outcomes? The answer is simple: learning is what makes the difference. Through exploring data and asking and answering the Socratic question why?, people are able to learn and gain insights about their organization and its situation, ultimately improving decision making. I'd argue that the real-world benefits of BI are largely derived from assisting institutional learning. This is often overlooked; I very rarely see the question, "How will this BI software promote learning?" asked in RFIs.
In turn, institutional learning is built on individual learning. As such, to get the most benefit from data for the most decision makers, BI needs to better align with how people learn much more completely than it has before. To do so, in the next few years BI will begin to support a fuller range of human learning styles. The visual representation of data is dominant in 2015, but not all people that need to use data are equally visually oriented. Humans use an individual mixture of sensory inputs to learn, often defined as three learning styles: auditory/reading, visual, or kinaesthetic.
In the near future, business intelligence will make use of information delivery media to engage all three learning styles. For example, for auditory learners, auto-generated narratives in written or spoken form will describe the shape of the data selected or the contents of a chart. Using technology or devices that "speak" these narratives may provide a compelling option for people who learn through hearing.
Also in the future, haptic feedback and 3D printing will likely play a role in creating tangible outputs for the kinaesthetic learners who assimilate information best when they can physically get their hands on something. However, it seems that it doesn't need to be that complex. Qlik's experience and research on multi-touch user interface points found that people retain and ascribe more importance to data if they touch it, even where all they're actually touching is a piece of cold glass. This is why designing BI software products specifically for the touch screen experience is about more than just getting on mobile devices.
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