Getting Return on Experience Through Analytics

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By going a step further, analytics can be added to the more classical BI solutions in order to increase the benefits of BI and thus improve the Return on Experience (ROE).

A good overview at DM Review and get the Babson version here.

I generally agree with his overall premise, but believe that analytics is not limited to the application of sophisticated statistical routines by a group of propeller heads in the back office, which might be one interpretation of his work. I do not think that is his intent, but it would be easy to read it as such.

Given today’s extremely competitive environment in nearly all business segments, there is an increasing need for visual business data to improve a company’s position. Two primary methods to produce this visual business data are available. The first, visual, interactive analytics applications, enables the visualization of complex data sets in order to understand their relationships. The second is dashboards, whose goal is to deliver a simple-to-read, complete overview of business operations. While both of these applications can add enormous value to a business, melding them into a single solution can deliver far more and significantly improve the decision-making process.

The simplest dashboard provides visual information using as few colors as possible and standardizes their meaning. For example, red might indicate something negative, yellow a risk, and green a positive. While this type of dashboard allows a business situation/problem to be visualized, it does little to help decide what steps should be taken. By adding interactivity, the dashboard allows decision makers to see the underlying data that pinpoints the exact reason for a specific indicator. Having this data available, the decision-maker can recognize a problem and its source and take corrective action – without having to suffer through potential lengthy response times or a development cycle involving the IT organization.

While dashboards definitely add value, they are incapable of supporting the complexity of the complete decision-making process. Visual, interactive analytics applications take that major step and excel at deciphering complex data to aid in the decision process. A key element in successfully implementing visual, interactive analytics is to make sure you find an easy-to-use solution. A second critical factor is to find an application that “guides” the user.

All business users should get the maximum of guidance to automate repetitive tasks. The purpose is two-fold. First, the business users should be able to focus on adding value, not on spending time accessing data, constructing queries, and formatting reports in order to get their business-critical information. The more that can be automated and guided, the easier the task will be.

In accordance with different user roles, the right mix of freedom and guidance is essential in order to ensure an optimal decision-making process, yielding confident business decisions. The second important result derived from guided activities is that they help the organization better utilize the experience of its employees. Best practices can be put in place and shared with others.

The outcome of guided and interactive steps will always feed another step in the decision-making process. By understanding and sharing the outcomes of all the activities within the decision-making process, a company will get the best return on its experience, something that is essential to avoid repeating bad decisions. The ultimate result will be a visual, interactive closed loop, involving both visual interactive analytics and visual interactive dashboards, to constantly improve, in a measurable way, the decisions of the organization.