Our benchmark research on business analytics suggests that it is counterproductive to take a general approach to the topic. A better approach is to focus on particular use cases and lines of business (LOB). For this reason, in a series of upcoming articles, I will look at our business analytics research in the context of different industries and different functional areas of an organization, and illustrate how analytics are being applied to solve real business problems.
Our benchmark research on business analytics reveals that 89 percent of organizations find that it is important or very important to make it simpler to provide analytics and metrics. To me, this says that today’s analytic environments are a Tower of Babel. We need more user-friendly tools, collaboration and most of all a common vernacular.
With this last point in mind, let’s start by defining business analytics. Here at Ventana Research, business analytics refers to the application of mathematical computation and models to generate relevant historical and predictive insights that can be used to optimize business- and IT-related processes and decisions.This definition helps us to focus on the technological underpinning of analytics, but more importantly, it focuses us on the outcomes of business and IT processes and decisions.
To provide more context, we might think of the what, the so what and the now what when it comes to information, analytics and decision-making. The what is data or information in its base form. In order to derive meaning, we apply different types of analytics and go through analytical processes. This addresses the so what, or the why should I care about the data. The now what involves decision-making and actions taken on the data; this is where ideas such as operational intelligence and predictive analytics play a big role. I will look to our benchmark research in these areas to help guide the discussion.
It’s important not to think about business analytics in a technological silo removed from the people, process, information and tools that make up the Ventana Maturity Index. In this broader sense, business analytics helps internal teams derive meaning from data and guides their decisions. Our next-generation business intelligence research focuses on collaboration and mobile application of analytics, two key components for making analytics actionable within the organization.
In addition, our research shows a lot of confusion about the terms surrounding analytics. Many users don’t understand scorecards and dashboards, and find discovery, iterative analysis, key performance metrics, root-cause analysis and predictive analytics to be ambiguous terms. We’ll be discussing all of these ideas in the context of business technology innovation,
our 2012 business intelligence research agenda and of course our large body of research on technology and business analytics.
Organizations must care about analytics because analytics provides companies with a competitive advantage by showing what their customers want, when they want it and how they want it delivered. It can help reduce inventory carrying costs in manufacturing and retail, fraud in insurance and finance, churn in telecommunications and even violent crime on our streets. The better organizations integrate data sets and utilize both internal and external information in a coherent fashion, the greater the value of their analytics.
I hope you enjoy this series and find it useful as you define your own analytics agenda within your organization.