Analytics and Organizational Change Management: A Perspective

February 5, 2018

LMI Staff

In organizational change management (OCM), it is important for decision makers to see the forest for the trees. Given the scale involved when shifting the way an organization operates, leaders have to be mindful of developing a strategy, managing expectations, and getting stakeholder buy-in. The same is true for Army capabilities development and integration (CDI), where concepts of the future Army are born and set in motion. In CDI, decisions can affect the way the entire Army conducts business. Regardless of the size of your organization, the process of improving and modernizing can be a lengthy and arduous one, and it comes with a fair share of risk taking. To get an organization over hurdles of change, decision makers need the ability to develop a strategy reinforced with data and analytical rigor. The following are some fundamentals for integrating analytics and data into your OCM strategy, and how these approaches have benefited LMI’s business in CDI.

The Goal Posts: Aligning the Objectives

As a manager or project leader, you have to start with understanding where the organization wants to go. When developing a strategy, a leader should align the organization’s objectives and success criteria with a strategy that leverages the appropriate analytical method. Further, the leader has to communicate findings in a way that the organization can get behind. Designing the strategy to cut across these areas can reduce the risk of wasting resources on low-value research and redundant meetings.

In Army CDI, a common objective is to reduce or eliminate a “gap” as defined by a capabilities needs assessment (CNA). A CNA’s purpose is to prioritize the development of future capabilities to meet current or impending warfighting needs. The CNA process gives planners clarity on what direction the Army is taking as it relates to its organizational objectives. What planners are then responsible for is making the needs of the Army a reality. To do so, we develop strategies (also known as courses of action) and employ analytical methods to bolster the path forward.

Choosing an Approach: The Conversion from Business Problem to Data Problem

Once objectives are understood, the organizational problem has to be converted into an analytical problem. Problem statements have to be reframed with questions that can be solved quantitatively and success criteria that are measurable. In this process, the project manager develops representations of reality through metrics and visualizations. The end state is that the analytical method produces results that intersect with the organization’s success criteria, providing insight into the effect of the chosen strategy before it is implemented. Constructing the problem analytically can therefore reduce the risk tied to decision making in an uncertain environment.

Within the CDI landscape, LMI has partnered with the Quartermaster Force Development Directorate, headquartered at the Army Sustainment Center of Excellence, to create the next concept of Army petroleum and water logistics. What makes our approach unique are the chosen analytic methods—scenario analysis and sensitivity analysis. These approaches fall into the area of predictive analytics. We chose scenario analysis because the problem entails closing a particular gap associated with large combat operations (LCO). To create a representation of LCO, a scenario had to be employed.

However, due to the uncertainty inherently imbedded in scenario analysis, we also employed sensitivity analysis to create a space where dependent variables were identified and deconstructed into independent variables. From there, the problem became a matter of changing independent variables to view the effects on the overall scenario.

The benefit of this approach is that decision makers can come to understand where and how extensive problems may be. Further, we can show them what they stand to gain by implementing various courses of action, before the implementation occurs. Essentially, LMI is providing a reduction in the risk associated with uncertainty in decision making.

Bringing It All Together

As a leader, consider the changes taking place in your organization and ask yourself the following: First, are the objectives clear and well understood? Second, is there awareness or discussion of potential strategies or outcomes? Finally, are these potential strategies being measured quantitatively against the success criteria? If not, consider adopting analytics into your approach toward the objective. You will find that better strategies come to the surface, you can better explain how the strategy aligns with the organization’s objective, and you can reduce the risk associated with uncertainty.


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