Why organizations fail to create value from analytics, part 1

Analytics is a hot topic today, with many companies looking to them as a means to create innovation and competitive advantage. And yet, the reality is that most analyses fail to produce tangible economic value. Once managers experience an analytics initiative that fails to materialize into value they can easily dismiss new analytic initiatives, a phenomenon that can be described as “Analysis Paralysis.” This type of failure occurs because there is no clear understanding about how to create value from analytics.

There are two key premises that summarize the process of creating value from analytics:

  • First, the insights from analytics create opportunities
  • Second, the operationalization of insights creates tangible economic value

The key issue here is the understanding of the difference between an insight creation and operationalization. These are two entirely different processes and unless they are connected the value remains elusive.  

Let us focus on the first premise first. Opportunities can be discovered in many ways, for example, by observation, by gut feeling, through R&D, and other methods. But today, opportunities are increasingly being discovered through analytics. The reasons for that are:

  • We collect a lot more data today – a process that was difficult and costly in the past
  • We collect not only transactional data but also behavioral data, which lets us see what and how people do things
  • We also collect social and customer support data that lets us understand why people do things

In the past, the only way to learn how and why customers did things was through observation. Today these questions can be answered with data analysis. Insights from data analysis have the added benefit of being fact-based, which removes the subjectivity of observational and gut feeling type of conclusions, and thus tends to be more accurate and reliable.

On the other hand, data analysis is time consuming. There are thousands of analysts in the U.S. workforce whose daily job is to sift through data and discover insights. And in fact, most organizations have a glut of insights produced by those analysts that are distributed via power points, visualizations, spreadsheets, etc. As economists know well there is an opportunity cost to acting on insights, as you have to select which ones to focus on and which to ignore. Hence, managers have to understand that insight by itself is not sufficient to create value. They need to move forward with the operationalization of the best opportunities.

What does it mean to operationalize an insight? Check back soon for Part II for an exploration into what operationalizing insights involves.

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