Successful organizations, as assessed by market presence and financial measures, depend on a host of integrated resources and systems to survive and thrive. Data and personnel are the two most important resources on this side of grace that an organization can leverage. Personnel perform physical work ranging from administrative (e.g., phone calls and typing) to operational (e.g., installing a new wastewater pump). Data is applied to improve the organization’s (or the individual’s) understanding regarding the effects of this work, both positive and negative. One of these resources is growing at an unprecedented rate. “Data generated in every two days is equal to data generated from the beginning of time until 2003” (Ahmed & Pathan, 2019).
Unfortunately, the concept of effective and efficient data collection, storage, and analysis is still foreign to many organizations. “The idea of making decisions based directly on historical data is not new, but it has received relatively little attention in economic and financial literature” (Grechuk & Zabarankin, 2018). The question becomes: Why?
Perhaps the lack of fixed or prescribed utilization models gives some leaders the sense that the current data revolution is a passing fad, something they can ignore or “push through”. This may cause the implementation of data systems through unproven deployment models. It may also be because the variations between organizations requires variations in business analytics systems and practices. Repeated studies and common sense both reveal that “leadership that embraces analytics-based decision making produces better decisions”, and, at the same time, “leaders vary dramatically in the degree to which they encourage analytics” (Bartlett, 2013). This variation increases at an exponential rate with the inclusion of Big (versus little or smaller, fixed sets of) data as a unique factor. Regardless of the challenges or issues, the solutions begin with the business leaders themselves.
Business leaders, whether enterprise-wide advocates (e.g., Chief Information Officers (CIOs), Chief Analytics Officers (CAOs), etc.) or mid-level advocates (i.e., product or process level managers), have been entrusted by God with the responsibility to make sound, moral decisions. These individuals have, in a manner of speaking, the responsibilities of Biblical Judges. “According to the instructions that they give you, and according to the decision which they pronounce to you, you shall do” (English Standard Version Bible, 2001, Deuteronomy 17:10). Working professionals, at least those with greater than sophomoric experience, know that when the Chief Executive Officer (CEO) speaks, the employees (his followers) often listen and obey. This may sound oversimplified and archaic, but that does not make the statement untrue.
With this level of authority in mind, one can quickly realize how a leader’s comments and decisions concerning data analytics can rapidly “infect” (not affect) an organization. Positive communications, including inquiries, regarding data capture and utilization fuel the organization towards the exploration, designation, and exploitation of the right data systems and practices (e.g., statistics, the mislabeled “Machine Learning”, etc.). On the other hand, negative comments or non-verbal expressions steer the organization away from data, away from analytics, and in fact, away from opportunities with the exception of those that simply occur by random chance.
Ahmed, M., & Pathan, A. (2019). Data Analytics. CRC Press. https://doi.org/10.1201/9780429446177
Bartlett, R. (2013). A Practitioner's Guide to Business Analytics: Using Data Analysis Tools to Improve Your Organization’s Decision Making and Strategy. McGraw-Hill.
English Standard Version Bible. (2001). ESV Online. https://esv.literalword.com/
Grechuk, B., & Zabarankin, M. (2018). Direct Data-Based Decision Making Under Uncertainty. European Journal of Operational Research, 267(1), 200-211. https://doi-org.ezproxy.liberty.edu/10.1016/j.ejor.2017.11.021