Building a Culture of Analysis

By Elliot King, Ph.D.
Professor of Communication, Loyola University Maryland & Founder of the Digital Media Laboratory

The idea that we live in an age of information abundance has been a cliché for the last generation. With huge amounts of data being regularly generated, developing the ability to understand and apply that data for decision support, trend analysis, and predictive analytics has proven difficult.

The problem isn’t the lack of data or tools for analysis. The real challenge is three-fold:

  1. Companies must decide what they “want to know” that they “don’t know” already and identify which data and analytic tools will generate that information.
  2. They must have enough confidence in the information produced to incorporate it into decision-making and organizational processes.
  3. They must continually assess and build on the first two. Are they conducting the right kinds of analyses to improve business performance in measurable ways? Are as many people as possible making fact-based decisions that are leading to better outcomes?

Those three elements are the foundation of what could be called a culture of analysis — a culture premised on the idea that understanding the underlying patterns in past and present data will lead to improvements in the future.

Companies can take several steps to create a culture of analysis:

  • Assess how deeply the idea and practice of analysis has penetrated the organization to date. What analytic tools does the company have? How effectively are they used and by whom? Who utilizes the output of the analysis and how does it help them do their jobs?
  • Ask difficult questions. What information would be helpful to know that is not currently available? Does the company have the resources to develop that information from the data available? Does the company need to cast the information-gathering net wider to include unstructured data from outside databases or from third-party sources?
  • Create a strategy for broadening analytic capabilities. Can elements of the analytic process be automated to accelerate time to insight? Can the way data is visualized and promoted be improved? Can the use of analysis throughout the organization be broadened?
  • Set expectations. What kind of data and analysis must be generated before a decision will be made? How long will decision-makers wait to access that information? If people know that they are expected to justify their actions with data, they will.

Analysis is an iterative exercise. As more data is produced, companies are under great pressure to make better use of it. Developing a culture of analysis is critical in that effort.

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