In keeping with our tradition of interviewing leaders from the federal government, we spoke with a West Point professor, Col. Nicholas Clark, who specializes in teaching statistics to military personnel.

Col. Nicholas Clark is an associate professor in the department of mathematical sciences at West Point. He is the former director of the Center for Data Analysis and Statistics at West Point and was instrumental in creating its applied statistics and data science major. In 2021, he created the 10-hour Data Literacy 101 course that served as the foundation for the current data literacy training in the Army.

Tell us about the efforts you lead to promote and provide data literacy skills within the Army.

In 2021, I took a year-long sabbatical from West Point to work in an Army operational unit. I noticed a chief impediment to implementing data science solutions was a lack of basic data and statistical literacy skills. This affected the data scientists, as data collection (by any soldier in the field) was often of poor quality, poorly labeled, inconsistent, or unusable for some other reason. Even if the data was of a high enough quality that a statistician or data scientist would feel comfortable analyzing it or building predictive algorithms from it, the operational force didn’t know what questions they wanted answered in the first place or the question would change in scope halfway through the analysis.

Working with the Army on their data literacy effort, for me, is an incredible way I can contribute across the service domain.

To address this, we created a short, 10-hour course called Data Literacy 101 to teach foundational skills in formulating a good data-driven question, reading data, working with data, analyzing data, and communicating from data. After giving the course to the command a few times, I started getting more requests from other units for the training. I spent the remainder of my sabbatical traveling across the country delivering the course.

Once I returned to West Point, we realized it wasn’t sustainable for us to keep giving the course in person. However, we firmly believed in-person education was preferable to online training, especially for the population we were trying to teach—people who perhaps hadn’t had a statistics course in 10 years, if at all, and likely had a misguided notion of what data or statistics is. So, we attempted to put together a course teaching others to give the training.

We ran our first instance of the train-the-trainer course (which we renamed train-the-educator to differentiate what we were doing from typical Army training) in June of 2023. Nearly 100 soldiers and civilians throughout the Army attended the 40-hour course, and we will have another iteration this spring.

Center for Data Analysis and Statistics
There are 27 centers and institutes at West Point that provide resources for faculty and cadets to engage in scholarly work relevant to the Army and nation. The Center for Data Analysis and Statistics has existed since the early 2000s and initially focused on providing statistical resources for faculty and cadets at West Point and local community members. I had the opportunity to run the center from 2011–2012 and then again from 2018–2020. In 2018, we decided to expand the center and focus on the needs of Army clients outside the academy.

Through these efforts, we have built several pipelines to Army organizations and now receive dozens of research requests annually that we give to faculty and cadets (often cadets majoring in applied statistics and data science) to work on. One of the unique components of our academic program is that many of our applied statistics and data science majors take a year-long research course during their senior year and work on a project generated through the relationships developed by the Center for Data Analysis and Statistics.

Col. James Starling, who currently leads the center, has elevated the quality of the research proposals and research done by our cadets to a level you would typically see in either graduate school or industry. But, perhaps more importantly for our mission, the research also directly affects the needs of our operational partners, meeting the needs of the Army.

Applied Statistics and Data Sciences Major
One of the most important mandates for West Point is to remain on the leading edge of academic program content and classroom pedagogy. In 2018, Col. Krista Watts, the senior statistician in the department at the time, asked if I thought the time was right for us to create a new major at West Point. We weren’t sure if it would be a major in applied statistics or in what was emerging as a distinct academic discipline in data science. Our internal market research determined cadets were interested in both.

At the same time, we read “Curriculum Guidelines for Undergraduate Programs in Data Science” in Annual Review of Statistics and Its Application and determined that, with just a few tweaks to our current course offerings, we could meet the recommendations from that report.

However, we thought statistical modeling was one of our program’s strengths. We wanted to retain that flavor in our new major, so we split the difference and called the major applied statistics and data science. By including statistics in the title, it became easy to differentiate our efforts from other programs housed in computer science departments that are perhaps more computationally focused than our major.

We have graduated two classes of applied statistics and data science majors, and we typically get about 20 cadets in each class (out of about 1,000) who select it for their major. As we built out the program, we established an external advisory board consisting of senior members of the government, industry, and academia who have been amazing in helping us continue to shape the program to ensure we are meeting the needs of these three constituencies.

We are in the process of seeking ABET accreditation under the Applied and Natural Sciences Accreditation Commission, which we thought was an important external review of our program. It also ensures we don’t let our curriculum drift and we continue to provide a high-quality education for our graduates. Most importantly, it helps to ensure we provide Army officers who can lead teams of statisticians and data scientists in the future.

What was the impetus for these efforts?

While we consider multiple constituencies when we build our academic program, the mission and identity of West Point is clear. We “educate, train, and inspire the Corps of Cadets so that each graduate is a commissioned leader of character committed to the values of Duty, Honor, Country and prepared for a career of professional excellence and service to the Nation as an officer in the United States Army.”

This is great for us as it gives us clear direction when we consider new initiatives. Are we contributing to the mission, or aren’t we? When we looked at our applied statistics and data science major, it was clear the Army needed more officers to lead a data-driven force. This came to us through our internal market research and anecdotally from senior leaders in the Army who told us we needed to produce more officers who could effectively work in and manage these technical teams.

The same held true for our data literacy efforts. Ultimately, we think this serves the needs of our graduates, as it creates a workforce for our applied statistics and data science graduates to manage effectively. If all we’re doing is creating a highly technical small cadre of officers without addressing the lack of statistical literacy in the workforce, we will only create officers who can’t effectively function. This, we think, would contribute to our applied statistics and data science graduates leaving the Army. We think this is a two-pronged approach. Build leaders who can effectively work in and manage a technical workforce while giving the force tools to increase their baseline data and statistical literacy levels.

Share a specific example or two in which your work or that of the center has informed an Army decision or policy.

Probably the most straightforward example of this was during COVID. In March of 2020, I was taken out of the department, put on our superintendent staff (college president equivalent), and asked to build out statistical models for the spread of COVID-19 and analyze the risk of bringing back the corps after spring break. In those days, we didn’t have a ton of models to fall back on, but we ended up building out a parametric model for the reproductive number of the virus and were able to quantify the risk (and uncertainty) that led to the decision to delay the return of the corps.

Our superintendent at the time was impressed by our ability to quantify the risk when few people were doing this outside of statisticians and epidemiologists. He realized knowledge of applied statistics and data science was pretty rare in the Army, so he offered us to the United States Army North (ARNORTH). I traveled down to San Antonio, Texas, and helped inform decisions on where to place medical resources and assess overall risk to the Army writ large.

While COVID was obviously a tragedy, it highlighted how quantitative skill sets can directly contribute to military readiness. Also, it highlighted the importance of having a data workforce that can help make sense of large quantities of data.

Why is it important for the Army to have a data-literate workforce?

As the number of sensors on the battlefield has increased, the amount of raw data an individual in the Army is exposed to has drastically increased. Gone are the days when we could just take all our data and push it to a small number of individuals to analyze. Rather, we (meaning everyone wearing a uniform) need to quickly process the data, make decisions, and—more importantly—know what we don’t know.

Everyone is capable of computing descriptive statistics from a data set; we also need to ensure everyone can know when descriptive statistics don’t answer the question we want to answer. We will never have a force full of data scientists or statisticians, but we can have a force full of individuals who know how to leverage these assets and to know what they don’t know.

How does your work fit in with US Army priorities?

Secretary Christine Wormuth, in her 2022 message to the force, directly stated her number two objective is “to ensure the Army becomes more data-centric and can conduct operations in contested environments, which will enable our ability to prevail on the future battlefield.”

It’s clear to us that, to meet this objective, we need a workforce that is data literate and officers who can effectively lead and manage the scarce resource of data scientists and statisticians in our force. We don’t think there is solely a technical solution to this objective, and, often, it feels like individuals are seeking a magic software or algorithm that can ‘make the Army data-centric.’

In the Army, we talk about DOTMLPF-P, which stands for Doctrine, Organization, Training, Materiel, Leadership and Education, Personnel, Facilities, and Policy. For us, creating a data-centric organization means addressing each level of DOTMLPF-P, and our efforts are directly affecting training, leadership, and education.

How has the Army’s relationship with data and data-driven decision-making evolved since you graduated, and how do you envision it evolving in the future?

I was a West Point graduate in 2002 and branched into military intelligence. I like to say I majored in math at West Point because I didn’t know what I wanted to do with my life. Perhaps that isn’t far from the truth. I always enjoyed math, especially theoretical math, and I think my senior research project had something to do with the algebraic structure of music. So, clearly not applied work.

However, in 2004, I found myself going to the Middle East for the first time and I was handed a spreadsheet with the number of IED [improvised explosive device] attacks over time. Not knowing what else to do, I relied on the two statistics classes I was ‘forced’ to take as part of my math degree and built out (clearly violating a ton of statistical best practices) a regression model that showed the command there was a pattern to the attacks.

I began to see that, even back then, there was a ton of data we were not effectively leveraging to inform decisions. I decided that if I ever got the chance to go back to grad school, I would major in statistics, which I was able to do (MS in statistics from George Mason in 2011 and PhD from Iowa State University in 2018).

I think we are still addressing not knowing how to effectively leverage data. The issue is rarely a lack of data. Rather, it is not knowing what we want to answer from data and a lack of independent data. Most of the data we collect is redundant and, though we think we have lots of information, we don’t. We are just collecting the same thing repeatedly.

I think the drive to collect more and more data will continue, unfortunately. However, I am hopeful the efforts we are part of—building out applied statistics and data science majors and creating a data literate workforce—will help us ask better questions of the data we have and ensure future data collection efforts involve collecting data that doesn’t already exist in another form.

Tell us about your journey to becoming a colonel in the Army and being a West Point professor helping the Army-wide data literacy efforts.

West Point is unique in several ways, but our faculty model is a blend of military officers and civilians. Our military officers are typically selected earlier in their career, and we then send them to get a master’s degree before having them serve as an instructor for two to three years. Then, they can apply to be a senior faculty member and we will send them back to the force for two to three years, and then to a PhD program. These individuals again serve for two to three years in the department and return to the force. Beyond that, there are academy professors (which I currently am) who are tenure-equivalent faculty members and permanently stationed at the academy.

Serving as an academy professor at West Point has been a phenomenal experience for me. It’s amazing to educate students who have chosen to serve their country. I have also gotten to serve as the program director for the applied statistics and data science program, allowing me to help shape the curriculum and assessment process for our department.

Just as other schools expect their tenured faculty to contribute beyond teaching, we expect the same of our senior officers. Working with the Army on their data literacy effort, for me, is an incredible way I can contribute across the service domain. Not only does it provide an important contribution to our primary constituent, but it also shows Army officers at West Point are doing more than teaching in the classroom. We are directly contributing to meeting the needs of the force.

Editor’s Note: The views expressed in this interview are those of Nicholas Clark and do not necessarily reflect the position of the United States Military Academy, Department of the Army, or Department of Defense.