“Data analysis is an aid to thinking and not a replacement for it.” –Richard Shillington

One of the ideas of the 4th Industrial Revolution is that we’ve entered the age where wisdom is much more valued and impactful than mere isolated knowledge or experience without reflection. This is an age of mergers: the merger of {knowledge with purpose} and {experience with reflection}.

It’s really the merger of everything: the merger of the arts, the sciences, and the humanities. It is in this context that data analytics become such a discussion…but the discussion cannot be just about analytics.

I find the idea of wisdom an intriguing one. When one thinks analytics, there is an emphasis on making data-driven decisions—sounds logical. Nevertheless, too much reliance on data to make decisions impair the leader’s sense to take risks and build bridges between data and reality (the past, the present, and the future). In other words, the over-reliance on data impairs the leader’s ability to build and grow in wisdom.

Big data analytics expert, Dr. Thomas Davenport, highlighted that sometimes analytical results will contradict our own wisdom. He suggested those contradictions should not be ignored but used to examine assumptions. This is the path to wisdom. Not necessarily through the passage of data analytics but by examining the contradictions and then taking appropriate risks.

Using six sigma methodology as an example, one defines the problem, gathers data, examines the data and assumptions, and then is set out to examine the assumptions through hypothesis testing. Even after testing a hypothesis (rejecting or accepting it), one can only deduct with a high degree of confidence that the result is or is not significant.

The examiner still can make what it is called a type I or type II error (rejecting a hypothesis when it was true or accepting it when it was false). However, wisdom comes from acting, having conviction of the related biases embedded in the analysis and measurement systems, plus the leadership intuition based on business competence. In other words, leaders must go beyond the data.

“To succeed in applying analytics, leadership must correctly judge the merits of analytics and how to best integrate this information into corporate decision making.” –Randy Bartlett

Leaders have to use intuition, apply wisdom, and make sense of the data to inspire value. The very first step is to acquire good information. Good information is required to measure performance of your processes and identify opportunities. This implies data scrutiny. Once one knows the data has integrity, then the facts must be examined because, “all observed facts invite many possible inferences as to what brought the facts about.”[2]

The next step for leaders is to understand how the data has connections to possible explanations, probabilities, and predictions of the future. If the leader can connect those facts with clear, plausible, data driven and business competence explanations, then he or she will best be able to make sense of the data (what the data is saying about the past and the future) and provide business value.

Having big data analytics power is good, but employing it with leadership wisdom creates real impact.

Always motivated, lugo

The author is the senior leadership and strategic foresight consultant for LS|EG. He is also the author of several titles to include peer-reviewed academic works. His doctoral areas of research are Culture, Strategic Leadership and Foresight, and Organizational Development.

Notes and references:

  1. Bartlett, R. (2013). A practitioner’s guide to business analytics: Using data analytics tools to improve your organization’s decision-making strategy. New York, NY: McGraw Hill. 19.
  2. Brennan-Marquez, K. (2017). “Plausible Cause”: Explanatory Standards in the Age of Powerful Machines. Vanderbilt Law Review, 70(6), 1258-1259.
  3. Davenport, T. (2010). Analytics at Work: Smarter Decisions, Better Results. Boston, MA: Harvard Business Review Press.