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Implementation Challenges in the Middle Market

Klaus Schwab, founder and executive chairman of the Geneva-based World Economic Forum argues that we are on the brink of a “fourth industrial revolution” wherein we will transcend the lines between the physical and digital. Central to this transformation is perhaps the most valuable asset of this century – data. Accordingly, the ability to create value from data becomes a critical skillset for companies wishing to digitize their firms.

Despite its promising future, the current state of data science and analytics is not without its challenges. Most companies today are still only tapping into a fraction of the potential from data. Implementation of data science and analytical tools has also been slow in the middle market. While experts estimate that only about 5% of middle market companies have adopted analytics as a practice, some estimates suggest that these companies have “digested” just 0.5% of the data available to them.[1]

For middle market companies, the barriers to creating value from data are commonly found in three areas:

  • Developing the data pipeline can be challenging: Modern data science has modern hurdles. The goal of creating pipelines that are optimized, reliable and repeatable, and have high-speed performance for end-users, is often encumbered by organizational roadblocks and data dependencies. Organizational change is difficult in general, but a firm changing its decision-making processes to be more data-oriented and less dependent on the anecdotal experience of its leaders faces inherent challenges given status quo bias and organizational inertia.
  • Open source tools may create security risk: Open-source solutions are often preferred by data science professionals due to being perceived as better suited for their specific needs and more responsiveness. Unfortunately, many organizations view open-source software as vulnerable from a privacy and security standpoint.
  • Difficulty finding/retaining data scientists: Data scientists and business translators are in high demand and relatively low supply. Further, a recent survey reported that when asked, 44% of data scientists said they plan to look for a different job within the next year.[2] Up to 2.72 million jobs requiring data science skills will be posted by the end of this calendar year, making it one of the highest-demand roles today.[3] This demand coupled with a massive shortage of employees with data science skills in every major U.S. city makes hiring for these roles much more difficult.

Middle market companies are still in a transition wherein they are attempting to match their desire to source, integrate, and glean insight from data to their capabilities to execute. Fortunately, Larx Advisors has a well-credentialed team of analytics professionals and management consultants who specialize in serving the middle market.

[1] Big data and the middle market. (2018, January 16). Retrieved from

[2] Vigliarolo, B. (2020, June 30). Challenges facing data science in 2020 and four ways to address them. Retrieved from

[3] Columbus, L. (2017, May 14). IBM Predicts Demand For Data Scientists Will Soar 28% By 2020. Retrieved from

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