Article

Business Intelligence: Moving from Tools to Applied Capabilities

By Steve Discher
Executive Vice President

Whether you call it business intelligence, predictive analytics, artificial intelligence, neural networks, or a data warehouse, the desired results all center around effectively using data and analytical tools to make better business decisions. Advances in technology and tools coupled with the demands of the marketplace have driven forward-thinking companies beyond the traditional reliance upon trends, ratios, and variances into the domain of sophisticated models and simulations. Today, BI, as many now call it, has quickly become the umbrella label covering most of the new and long-standing information-generating practices. Given the competitive advantages created by better-informed decisions, the big question is: Where is your company in the evolution of BI capabilities?

Speaking with clients about their company’s evolutionary progress, we repeatedly hear a common set of questions focused around execution—specifically, applying the tools versus choosing the tools themselves. The most common ones include:

We have found that one of the most common challenges that companies face as they move further into the world of BI is the tendency to focus on the solution instead of the problem. This is especially true for newcomers to the BI game. Companies often center their attention on the quality and sophistication of the actual data and tools rather than the problems they want solved. How many data sets? How accurate is the data? How well is the data integrated? What supplemental data should be bought? What kinds of analyses can be generated from the data we have? And who are the vendors with the richest functionality? All good questions, but the focus wrongfully revolves around availability of tools and data instead of the problems to be solved and the decisions to be made.

At the same time, decision makers are looking for the information coming from better use of analytical tools. They typically ask questions that are similar to those just listed yet more specific to solving a particular business problem. For example: What trends and opportunities exist in claims losses, fraud, or subrogation? How can we better pinpoint underwriting and pricing opportunities by customer/product/channel segment or segment combination? What trends in claims litigation will lead to better outcomes? How do we explain a price change to a customer with our channel partners?

Unfortunately, aligning these two groups’ efforts can be a challenge. More often than not, once the tools are available, people become dazzled by the “shiny objects” and their new analytical outputs. Process takes precedence over results, and the intended informing of decisions gets overlooked. A case in point; recently, a client conducted an enhanced analysis of claims that clearly identified material opportunities. Translating these opportunities into reality stalled because there was no change management in place for modifying claims adjuster practices.

Knowing where you are is the first step to getting where you need to be. Because not every company is at the same starting point in terms of leveraging BI, the Nolan Company uses a capability maturity model to assess how much an organization has evolved (see below). This framework can be used to determine how aggressively a client may want to pursue expanding their BI capabilities.

Business Analytics
Capability Maturity Evolution