Army commanders face significant decisions when trying to overcome challenges and solve problems. But too often, one of the best sources of information and insights remains unexplored or excluded from the decision-making process—data analytics.
In the early 2000s, as the Army expanded its combat operations in Iraq, commanders at echelon struggled to identify trends and gain insights into local, regional and national environments, to include trends in adversary activities. Hours were spent locating and consolidating disparate data sources (for example, surveys, Combined Information Data Network Exchange and nongovernmental sources) and “cleaning” data in order to feed rudimentary software tools like Excel and Access.
Despite the time commitment, these efforts provided marginal impact on key decisions—there was simply too much squeeze for the amount of juice. Several years later, the Army experienced similar challenges in Afghanistan.
Since then, industry has modernized datacentric tools considerably, in large part thanks to technological advances in compute-and-store capacities, transport capacities, data platforms and data analytic software. The Army has only scratched the surface in taking advantage of these technological advancements, but the benefits are noteworthy.
For example, the Army’s response to the COVID-19 pandemic, in certain instances, leveraged some of these innovations effectively to support decisions at the unit, garrison and enterprise levels.
Unfortunately, many Army organizations have yet to experience the full benefit of datacentricity despite many of the service’s current challenges—such as recruiting, talent management and supply management—being data rich. With the explosion of data sources available to commanders, it is imperative to embrace datacentric practices and incorporate them into decision-making processes because future wars will be decided on who best leverages data.
Through data analytics, commanders create information advantage to deliver decision dominance. In other words, having analytically informed options available at speed helps commanders win on the battlefield.
So, it’s not surprising that seminal documents, including the National Defense Strategy, Deputy Secretary of Defense Kathleen Hicks’ May 2021 memo on creating data advantage and Secretary of the Army Christine Wormuth’s February message to the force, encourage an accelerated transformation to datacentricity. Stated simply, a datacentric organization is one that leverages available data and analytic capabilities to support decision-makers with information and insight. Providing a framework will help commanders accelerate transformation to a more datacentric Army.
Commanders who establish and sustain datacentric units can achieve two broad objectives: improved performance and decision advantage/dominance. Performance improvements are achieved using empirical data to inform decision-making, which has the potential to reduce errors often caused by an overreliance on intuition, perception, bias, false narratives or misinformation.
Decision advantages are achieved by devoting more time to analytics and less time to compiling information or integrating multiple proprietary applications. This is particularly powerful when predictive analytics are applied using sophisticated capabilities associated with data science, machine learning and artificial intelligence.
Success, from the enterprise level to the tactical level, is increasingly reliant on data. The sheer amount of data generated and made accessible at every echelon across the Army is astounding. This, combined with increased connectedness over time, means the importance of commanders transforming to datacentric units will only intensify.
Speed on the modern battlefield is measured in milliseconds—the time it takes a data to transit the globe. Therefore, the ability to glean insights at scale and speed is important to create and maintain decision advantage at all echelons.
Before discussing what it takes to become datacentric, it is worth recognizing what should not change as a result of embracing datacentricity. Datacentricity should not be approached with the mindset that the Army is replacing its leaders with analytics. The goal is to enhance the quality of analysis used to support their decisions, not replace them. In fact, effective decision-makers will use all available information to inform key decisions, including analytics, experience and other factors.
The most challenging part of establishing a datacentric unit is the cultural transformation required to ensure personnel at all echelons fully embrace datacentricity. Promoting this culture will transition the Army to the digital age with greater speed, efficiency and understanding.
A framework set forth in an October 2010 article in Harvard Business Review by Babson College, Massachusetts, professor Thomas Davenport and two others, “Competing on Talent Analytics,” suggests that changing an organization’s culture begins by aligning functions, systems, processes and data to answer six analytic questions.
The first three questions help leaders obtain information, while the last three focus on insights leaders can gain.
Here are the six analytic questions, each with follow-up questions to help convey how they can be applied to key Army challenges, such as managing the service’s inventory of munitions:
1. What happened in the past?
After looking over reports and dashboards, did the Army manage its munitions inventory optimally in the last cycle?
2. What is happening now?
As real-time alerts are absorbed, is the Army on track to achieve its munitions inventory goals in this cycle?
3. What will happen in the future?
As data and information are extrapolated, can the Army still achieve its desired munitions inventory goals in future cycles?
4. How and why did something happen?
Based on modeling or experimental design, what caused the Army to fail in achieving its munitions inventory goals in the last cycle?
5. What is the next best action?
Are there recommendations that can be made to determine what levers are available to improve management of munitions inventories in this cycle?
6. What is the best or worst case for the future?
Using predictive analytics, optimization and simulation models, what is the best possible munitions inventory outcome the Army can achieve if it pulls each of its levers?
This framework is useful for commanders to orient to where and how data analytics can be incorporated into daily practices. It should be used as a starting point, not an end state.
Regardless of the echelon, it is important that these questions are aligned to commanders’ needs for both information (that is, commander’s critical information requirements) and insights, not just what the available data supports.
Commanders should use this framework by focusing first on questions No. 1 through No. 3 (information), which involve the basics of what happened and what is happening. As commanders become more steeped in datacentric practices, they can find increased benefit by focusing on questions No. 4 through 6 (insights), which involve why things happened and what will happen.
The value proposition of leveraging this framework is the inherent linkage it creates between the commander and the unit’s subordinate activities to drive effective decision-making. This is important in developing an enduring datacentric culture that transcends people, personalities, tools and technologies.
After adopting this framework, commanders should foster this cultural transformation by educating and developing the workforce, creating an end-to-end data ecosystem and enforcing datacentric practices.
Educating personnel at all levels is an important contributor to datacentricity. Commanders should ensure that leaders at the executive level take advantage of opportunities to attend courses that emphasize ways to conduct quality data analytics.
For example, senior leaders can participate in a data analytics decision-making course that equips them with a deeper understanding of available tools and techniques, an ability to identify potential uses to conduct data analytics, and training on how to convey insights garnered from data analytics to drive implementation and results. Similar courses are available to a wider range of soldiers and civilians through the Army e-Learning program.
In addition to prioritizing training opportunities, commanders must understand what data they have access to, how it can be used, how it aligns with their organization’s strategic goals and what limitations impact their ability to conduct data analytics effectively. This will help discover the data that is available and, more importantly, the data not available. Commanders then can begin to understand how more useful data can be generated or captured.
Likewise, commanders must ensure that existing or available capabilities, tools and personnel are adequate to perform analyses that address their most critical needs. This will require commanders to place greater focus on developing the workforce to better support datacentric activities.
Talent management is imperative to achieving datacentricity. It is necessary for commanders to ensure that individuals conducting analysis are skilled and equipped to succeed. Analysts—be it operations research systems analysts, data scientists or other subject-matter experts—should have the skills to employ effective analytic techniques and clearly communicate analytic results.
But the list of personnel who require increased skills training spans more than just analysts. Individuals including simulation officers, information technology professionals and data engineers all should receive opportunities to hone their skills in order to further instill datacentric practices across the enterprise.
Another key aspect of datacentricity is creating a data ecosystem to enable personnel to conduct data analytics. Cloud architects and data engineers must facilitate the storage and computational needs of the organization’s analysts. The organization’s data ecosystems should ensure data is accessible to analysts.
During the past several years, the Army has established data platforms like Vantage and cloud-based analytic environments like cArmy that should be employed. Recently, cArmy expanded its customer base to provide users with access to a general-purpose cloud environment hosting many Army applications and data systems. By delivering common shared services, cArmy enables customers to focus on data analytics while benefiting from cybersecurity and other advantages of cloud computing.
Practice What You Preach
Creating a datacentric culture also requires engagement, both internal and external to the organization. Commanders must practice what they preach on a consistent basis to successfully drive improved performance and decision advantage through data analytics. Internally, commanders should focus on reducing barriers and eliminating “ownership” issues, particularly with data sources that provide value to multiple divisions within the unit.
This approach helps commanders ensure that the most important data is visible, accessible, understandable, trusted, interoperable and secure. Externally, commanders should collaborate with others to gain data access from, and share data with, other organizations.
Becoming a datacentric Army should be imperative for every commander at every echelon—the stakes are simply too high and grow daily through inaction. Commanders must lead this transformation. The path to datacentricity will be disjointed given the constant evolution and innovation of technology and workforce turnover.
Commanders and commands that establish a datacentric culture that transcends these factors can navigate the dynamic nature of future challenges, maximize the use of information and insights developed through data analytics, deliver decision advantage and, eventually, deliver decision dominance.
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Maj. Gen. Karl Gingrich is director of program analysis and evaluation, Headquarters, Department of the Army, the Pentagon. He is also the senior Functional Area 49 operations research/systems analyst in the Army. Previously, he was director of capabilities integration, U.S. Cyber Command, Fort Meade, Maryland. He served combat tours in Iraq and Afghanistan.
Bryan Shone is deputy director of program analysis and evaluation, Headquarters, Department of the Army. Previously, he was director of policy and resources, U.S. Army Office of the Chief Information Officer. He holds a doctorate in economics from the University of Tennessee.