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Vive la Révolution (or Long Live the Revolution)

The revolution is upon us! “Advancement of Industry 4.0 will be driven by a smart, interconnected, pervasive environment. A well-equipped industry will be capable of planning ahead with a clear strategic vision and focusing on how smart products and processes can be developed” (Ahmed & Pathan, 2019, p. 238). Developing and sustaining a competitive advantage during the fourth Industrial Revolution requires the right people in the right roles as previously discussed, but emphasis should also be placed on the importance of careful and deliberate strategic planning and integration and continual improvement.

Strategic Planning and Integration

“The overarching objective is to integrate business analytics into the business strategy” (Bartlett, 2013, p. 116). Organizational strategic planning can be conducted in several ways using different methods. Two common approaches utilized today include the Balanced Scorecard and Hoshin Kanri, although the latter is typically only utilized in organizations that embrace the Lean methodology. Regardless of the level of sophistication of the method employed, the process used to facilitate the design and maintenance of a strategic plan does not need to be complex. This is true for each core capability and/or value stream that an organization hosts, including analytics. In the end, “we need to address whether (or not) the decision makers have access to the facts, the business strategy is fully leveraging data analysis, and the facts are adequate to support decision making and the business strategy” (Bartlett, 2013, p. 126).

Considering the customers I have served over the years, the integration of analytics (or other sources of competitive advantage) into and in support of the corporate strategic plan typically begins with a performance- or needs-based assessment, often generically referred to as a gap analysis. An “enterprise-wide approach is to build a value diagram outlining the flow of value within the corporation”, and this diagram includes key aspects such as a measurable vision, operational and process levers, initiatives (or projects), and the supporting technology (Bartlett, 2103, p. 118).

This planning tool is extremely similar to the Balanced Scorecard’s Strategy Map, “where the energy, priorities, and actions of people are mobilized, aligned, and focused. Its purpose is to fulfill the results for the Enterprise Performance Management framework leveraging cause-and-effect relationship linkages via feedback measurements to the organization” (Cokins, 2020). From a top-level view, Strategy Maps visually communicate the linkages between the end goal, the quantified vision, and the tactical initiatives and support (including analytics and technology) required to achieve it. This enables organizations that desire (or need) to better focus on the introduction or (continuously) improved integration of analytics in their culture and discrete decision-making processes in a(n) (initiative- or project-) specific and measurable manner. More so, the Strategy Map, like the value diagram, builds a systematic visual base upon which corporations can plan and execute efforts focused on continual improvement.

Continual Improvement

“We want to integrate continual improvement into every project” (Bartlett, 2013, p. 132). In an analytics-driven culture, this includes improving the analytical methods analysts use and how they use them, and also “continually improving the infrastructure to accommodate greater analytic breadth, better solutions, and more speed” (Bartlett, 2013, p. 133). Many of the organizations I support adhere to a failed principal, a fallacy, wherein each and every project is expected to consistently and constantly generate a Return on Investment (ROI) regardless of the type of project or the project execution phase (e.g., startup/initiation, execution, measurement and discovery, etc.).

This is not to say that the expectation for returns from any effort is nonsensical. In fact, it is Biblical. Jesus discusses this principle in Luke 14 when He states, “for which of you, desiring to build a tower, does not first sit down and count the cost, whether he has enough to complete it? Otherwise, when he has laid a foundation and is not able to finish” (English Standard Version Bible, 2001, Luke 14:28-29). Traditional projects, those that follow the Project Management Body of Knowledge, lend themselves to this approach. They require detailed planning at the outset and “insist on defining project scope and product description during the planning phase, which does not suit the nature of big data projects” (Ahmed & Pathan, 2019, p. 224).

Unfortunately, this expectation is extremely difficult to manage from a process or system perspective and fails to recognize the risk associated with the projects and the non-linear progressive nature of technical projects, which may induce or experience momentary obstacles or failures throughout their execution. “We need to make incremental technical advances – each of which can be a temporary economic failure – until we reach the coveted final one that generates wealth”, focusing on “those improvements that will produce the greatest ROI” (Bartlett, 2013, p. 120, 133). Leaders and managers in any organization, especially those engaging in the initiation or refinement of their business analytics programs, need to keep their eyes on the financial targets for certain. However, understanding the nature, benefits, and timing associated with advancing analytical efforts (and support) may help to maintain realistic deliverable expectations and further integrate a logical sense of patience throughout the corporation, discounting short-term losses and advocating for long-term wins.


Competitive advantages come in many forms including superior customer service, accelerated delivery lead times, product and/or service diversity, lower price points, etc. Today, during Industry 4.0, the value of data and the associated analytics is being realized, but not as an end unto itself (i.e., the practice is not the goal). Corporations are discovering that it is difficult if not impossible to achieve or improve any competitive advantages without an effective and efficient analytics program – the analysis fuels increased understanding and better decisions regarding which advantages to pursue or develop, which to refine, and which to abandon.

Two important aspects that drive successful analytics programs include careful and deliberate strategic planning and integration and the pursuit of continual improvement at the organizational level and within the conduct of analytical processes and procedures. Corporations “want to ensure that (they) are applying the full depth and breadth of (their) statistical capabilities”, but they also “want to run analytics like a profit center” (Bartlett, 2013, p. 127, 121). This journey requires patience and there are no shortcuts, however best practice methods are available, including the development of a Strategy Map and the recognition (and appreciation) of non-linear project progression.


Ahmed, M., & Pathan, A. (2019). Data analytics. CRC Press.

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.

Cokins, G. (2020). The strategy map and its balanced scorecard. The EDP Audit, Control, and Security Newsletter, 61(3), 1-16.

English Standard Version Bible. (2001). ESV Online.


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