Stories, signals, and sense-making: how Business Intelligence becomes intelligent

Stories, Signals and Sense-making: how Business Intelligence becomes intelligent

Guest post by Donald Farmer, currently the principal of TreeHive Strategy and he previously led design and innovation teams at Microsoft and Qlik.

 

Ever since Business Intelligence emerged as a technical and commercial practice, the promise has been that the right information, delivered at the right time, in the right format would help us, as users, to make better decisions.

Sadly, that has rarely been the case. The classic formats of BI – dashboards and reports – have been useful for monitoring business, but seldom insightful enough for proactive decision making. BI has always been retrospective, looking back over data in the wake of events that have already occurred. The technology barely guides the all-too-human user, giving just the facts and leaving the most stressful work to you.

But surely we have Predictive Analytics? The very name describes its forward looking approach. Algorithms extract patterns, often deeply hidden, from existing data, and project those forward. Predictive Analytics successfully powers numerous business scenarios, calculating credit scores in finance, stock levels in manufacturing, special offers in retail and more.

So what is the problem? Simply that Predictive Analytics is still a specialised area, most often requiring tools that are not designed for regular business users. As a result, when algorithms and their outcomes have been integrated with BI, it is too often quite an effort for users to grasp the implications unfolding from the statistical methods involved.

Stories and Signals

The truth is, human beings are not wired for either static reports or statistical modelling.

Instead, we pay attention to, and remember, narratives which have direction and flow. We don’t represent the world internally in our minds as data structures and algorithms, but as stories which have structure and character, even when attending to abstract concepts. Just as a salesperson may struggle to meet their numbers, so stock prices struggle to pass through notional barriers. That’s a story, not an analysis.

But we’re also quick to notice new information, irregularity and warnings. Patterns and exceptions jump out at us with remarkable lucidity, as we evolved to detect predators literally doing so. We pay to attention to alerts and we are sensitive to changes in regular patterns.

The New Sense-Making

So how are we to make the best of these diverse styles of cognition in business decision making?

Fortunately, new technologies and techniques of visualisation, messaging, and machine learning, enable us to integrate the best of traditional Business Intelligence, Predictive Analytics and human sense-making. The task is to bring together, with a light touch and in a single environment, the various ways in which human cognition and machine analysis, usually regarded as separate techniques, can work together.

Firstly, users must be able to build Stories. Rather than just presenting results in a dry, static manner, it really helps if we can construct a narrative that flows from one observation to another, from doubts to decisions, supported by data and effective graphics. Users and their collaborators need to be able to drill into details, because you’ll find that good visualisations raise questions rather than just illustrate answers. And it’s important to do this in a far more interactive style than slide presentations. There is no good business question to which the answer is “more PowerPoint.”

Stories are great for communication and collaboration, but we also need to be alert to Signals that draw attention to changes in our situation. Predictive Analytics can indeed help here, but only if seamlessly integrated with our regular tools. Technology should work with our business knowledge, without requiring theoretical expertise, yet still picking up hidden qualities that we ourselves may not find in the volume and complexity of today’s business data.

A New Version of Business Intelligence

Yellowfin have pulled together many of these ideas in their new release. That this is version 8, tells you how such capabilities have evolved over time. There is a shift in the center of gravity towards more predictive insights; but there’s also solid experience, and an attention to design and practical business uses, which makes a real difference when integrating radical technologies with well-established BI techniques.

Existing users will find a system that is familiar, but more insightful and engaging, and simply so. New users will encounter a refreshing analytic experience, one that works with their natural sense-making in the ever-more-complex jungle of business data.

Of course, there is much more in this release than just these features. But I am personally pleased to see that the latest developments in Business Intelligence work so naturally, and so well, with the marvels of human intelligence.

 

Find out more about the innovative Yellowfin suite here.

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