By Joshua Smith, Chief Master Sergeant (Ret.)

In 2020, I assisted hiring DOD’s first dedicated human performance (HP) analytic team, which was assigned to the first DOD Human Performance Group, whose mission was to support the Air Force’s Battlefield Airmen pipeline programs. This organization, with supporting assets, was the first of its kind within the Department of Defense (DoD) structure.

While this offered a certain amount of freedom in one sense, it also meant going through a trial-and-error process that changed how we looked at hiring, onboarding, and developing team members, configuring a productive working environment, and connecting the numbers on their screens to the real-world scenarios in which candidates performed.

The resulting lessons apply to anyone trying to build an effective human performance (HP) analytics group in a military or civilian setting. 

Strategic Use of Contractors

Within our HP program, we had a nine-person analytics team that would come on board over the next 18 months. It would eventually be composed of GS (general schedule) and active-duty military members, but the whole team complement wasn’t scheduled to join us for about 24 months.

During the interim, we contracted out some of those positions. We’d reduced those contract positions when the GS and active-duty personnel were hired. The advantage of doing it this way, especially within the DoD, was that it justified the manpower requirement. We weren’t trying to fill them organically as an additional duty as we waited for the hiring of the entire team. When asked why we required these positions, we could explain that contractors have been filling these duties for a couple of years, providing manpower data to justify the positions.

Balancing Domain Expertise and Civilian and Military Backgrounds 

When building a high performance analytics team, leaders need to hire experienced members with a background in the human performance field and the drive to think outside the box.

As we put together our initial group for our first program in 2018, we didn’t research enough to know that we should’ve found more people already in HP research positions. Instead, if we came across someone with a master’s degree and 20 years of experience, we figured they should be able to crunch our numbers. But it soon became apparent that this wasn’t always the case.          

Our first hire came from the oil industry; he was challenged by transitioning from the oilfield to human groups. In their previous scenario, they had a pump that kept going at a continuous rate, seven days a week, 365 days a year, so there was consistent data.

A human might have an off day because of their nutrition or not sleeping well. Maybe they forgot to put on their wearable device, so there’s no information. The analysts didn’t understand why the data was inconsistent and coming in the way it was. 

Even when we brought our active-duty people and GSs over, some of those we hired – like our epidemiologist – didn’t come from the human performance side of the house but civilian health care. They still had challenges because when you look at the data for our guys, they are typically in the top five percent against an ordinary human within the United States. Running a performance program for such individuals differs from general population health care.

But eventually, we put together a good group of talented staff with the right mix of human performance know-how, military and civilian experience, and data analytics skills. That combination was crucial. When someone comes in with military knowledge, they know all the jargon, and they’re going to think in a certain way, but sometimes that isn’t the right way. When you’re bringing in an outsider, they don’t know all the terminology but might have a new and different perspective. That’s why we built an all-inclusive team and got a bit of both. 

Dialing In Onboarding and Work Environment

In our Prep program, implementing a solid onboarding program was one of the keys to getting these different roles and backgrounds to work well together on our human performance team. We didn’t care whether they were military or civilian, an analyst, nutritionist, or strength coach – we eventually started taking five days to show each new hire around, introduce them to everyone, and point out where everything was. Plus, another few weeks to continue that indoctrination process. 

The onboarding phase helped them understand how we did things, get to know our unit-isms (practices and terms specific to our group), and grasp what our mission was.

It took us a while to get to this point because leadership initially gave us 90 days to get the program off the ground, so the first six or seven people who joined had to start running right out of the gate. But after about a year, we put that onboarding process in place. 

Another change we had to make was the working environment. At first, we put our initial six hires in a bullpen-style office. That didn’t work well because they were used to having their own offices and now got distracted by people walking across the room, noise, and other outside entities that disrupted them throughout the day. This led to us finding more space, redesigning cubicles, and making other changes so our team members could concentrate.

Connecting Data, Operators, and Analysts

It is very challenging to find someone in the analytics world who wants to get out from behind their desk. When it’s raining in the middle of the night, and they’re watching instructors gather data and individuals perform, only then will they truly grasp the reality of where that data is coming from.

In their minds, they might think they’re just looking at a number. That’s true; we don’t want to skew them in a specific direction. But they still need to understand the context and why there might be gaps in the data. By getting out there and seeing what’s happening, they could become part of the solution and find ways to fill those gaps.

Sometimes you can use those real-world experiences to serve a dual purpose: connecting your staff with the applications of their work and getting end users more on board with data monitoring. We could do a much better job of taking the data from an individual, processing it, and providing feedback to them. Once we give the information back to the operator in a way that makes sense, they’re much more invested in it. With a system like Smartabase, they can visually see what the data looks like if they drank the night before or didn’t sleep. 

Our programs had what we called HPTs – human performance technicians. They’re the ones who were looking through daily surveys, putting the sensors on the candidates every single day, processing the data post events, and acting like a crew chief for that human.

They quickly started to belong and know when guys aren’t performing, especially after a couple of weeks of working with them. But sometimes, it was helpful for an HPT to explain to the person analyzing the data what was happening during certain events. You want everybody to be part of the team, and to achieve that; your analysts need to be able to connect with the people they’re serving and see some of the benefits of what they’re doing.

After a couple of the significant 18-hour events, we’d bring in members of the analytics group to explain to candidates through the data how their teams performed and areas they could improve in areas they can control, like sleep, nutrition, and hydration.

This placed the team members in front of the students and helped them see how their work contributed. It also allowed each candidate to say, “That’s the guy who is processing my data.”

Hopefully, creating that team or family-style atmosphere helped everyone remember that we should all be working together and working towards the same cause. Because ultimately, the goal is to get each operator as close to their optimal performance as possible, 365 days a year.

Communicating Clearly to Get Leadership Buy-In

Organizations may have all the data in the world, but without buy-in from staff willing to adapt their programs based on the team’s analytics, you will not achieve your strategic goals.

For example, our analytics team confirmed the highest injury rate by events within a program. When they presented this data and recommended moving the event two days earlier in the training program to reduce injury risk, the course staff refused to modify the non-graded event, and injuries during the event continued.

Hiring staff members who don’t merely possess solid technical skills but know their audience and can communicate to them in a way that makes information understandable and applicable is vital to obtaining better buy-in from leadership.

Part of the challenge when we hired civilians was that they were often unfamiliar with military jargon and culture, which compromised their ability to share findings with other groups in a way that could be understood and acted upon.

We had one gentleman who was very frustrated because he couldn’t grasp the terminology we used for two years. When he started putting presentations together for leadership, we had to say, “This can’t go up to an O-6 because it doesn’t provide our points in words he can relate to.”

We also had to educate that the exact role or rank you’re sharing information with is significant. You can’t present data to a general as if they’re a squadron commander and hope they will understand it the same way because you will fail to get your point across.

It can take forever to get to an upper-level leader who can decide to continue funding your performance program, so the analytics team has to understand everything you’re going to share, why, and who you’re presenting to because you only have one chance to generate expectations. If you miss the mark, you will spend the next few months changing the perception. 

That comes back to knowing your audience and conveying complex concepts in simple terms. We had a program manager who was brilliant in how his brain worked and how he could process information and come up with a solution. But if you put him in front of an O-6, I’d have to tell him to use the terminology for someone who did not have an exercise physiology degree because the colonel has an aerospace background.

Another team member now works for the Detroit Lions. She had a brilliant mind but could talk to people like she was explaining the subject to an elementary school teacher. She’s the one we’d ask to present to O-6s and O-7s because she could level with them, and they’d say, “OK, that makes sense.” 

If analytics team members get out and see how things are being done, it gives them real-world knowledge. Then when they’re presenting to an O-5, O-6, or O-7, they can explain what the data means and then say that two weeks ago, they were out at two o’clock in the morning watching this event, which shows how the information is represented in this way. That’s more effective than cramming the audience with data and hoping they can make sense of it.

Continuing Professional Education

A critical element to maintaining a highly functional analytics team once you’ve hired everyone is the continual professional development of its members.

This can include attending and presenting at conferences, learning the latest programs and tools, and working with database developers to improve your organization’s system. Too often, we hire highly skilled personnel but fail our staff by not continuing their professional development. So, the team stagnates over time, relying on their existing capabilities and knowledge while systems continue to advance year after year.

We brought in some talented individuals to our HP analytics team. But technology and processing capabilities are evolving rapidly in the fast-paced world of human performance. Individuals who are reluctant to seek out higher education and personal improvement could be too far behind the power curve in a couple of years.

In some industries – like oil, which I mentioned earlier – data analytics hasn’t changed much, but the human performance realm is constantly advancing. We see computer systems and algorithms entirely different from those a few years ago. If your staff isn’t taking courses, keeping up on the newest techniques, and going to events, your team might get left behind.  

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