Beyond the Numbers

If you could spend a day immersed in the analytics operations of any organization, which one would you choose?

For me, it would be the NFL.

Yes, it’s playoff time and the hype is high. I can count on one hand the number of NFL games I’ve attended in person in my lifetime. I’m just not that keen on large, loud crowds, or the high costs. Instead, I prefer to watch from the comfort of my own home.

I'm not a fan of American football for its physicality. Although the athleticism can be amazing to watch, the injuries that come with it aren’t desirable for anyone. However, I do appreciate the game's strategy and the teamwork required both within and between the offensive and defensive lines and various special teams. Lately, I have been most intrigued by the vast amount of information collected and the insights derived from it.

I recently launched my SaaS advisory business Tremolofy and joined the Advisory Boards at Fidsy AI & Data Orchestration , a conversational BI platform, and ues.io , a no-code low-code app builder platform. I’ve even found time for my (shameless plug) Feltscaping art where I cherish the time and space to let my creative mind rejuvenate and run without restraint. Amidst all of that, I have been pondering ways to utilize my creative thinking, process orientation, and pattern-finding skills to analyze the intersection of data, AI, and app strategies. My goal is to find ways to enable every employee to access and reveal cohesive, coherent, accurate, and meaningful insights that can make them more efficient and effective in their roles.

I’ve also been watching a lot of NFL games.

So it’s no surprise to me that I’ve been struck by one thing during this NFL season.

Data.

I actively watch American football early in the season. By mid-season, I am also likely knitting while “watching” football. By that point, after hours of otherwise unproductive “couch time”, I’ve found what I enjoy most is listening to games while working on something more tangible, and looking up for any interesting replays. Even when I do watch, no matter how much I’ve tried to understand play formation over the past 30+ years, I just can’t see it, and I often can’t follow the ball after the hike. But by listening and “hearing” the game through the experience of the former NFL player-now-announcer, I’m able to understand it. And when they drop in key stats and trends… then I’m sucked in. I’d miss that information if I were in the stadium (pretty sure I’d be staring at the big screen or my phone most of the time anyway).

Have you ever stopped to consider what must go into collecting, analyzing, and delivering all of the data required to provide you with the current at-home-fan experience?

Think about it. Every time a commentator shares a stat or trend about a player or a team, I imagine them looking at one of many screens and dashboards surrounding them in the booth. There must be some visual cue highlighting what to say next and why it matters. Sure, the why is probably obvious to them based on their experience, but very few people can remember the number of data points an announcer may share during any given game.

It’s all made possible by the NFL’s Next Gen Stats (check out the helpful timeline graphic). The production behind it must be immense to track all 32 teams playing 17 games over 18 weeks for a total of 272 games, plus the 13 playoff games. The skeptic in me wonders if there aren’t scores of people running behind the scenes to make that information available at just the right time for a seamless flow of meaningful insights through the announcers back to the viewers. Meaningful insights is the operative phrase… showing data is one thing. Interpreting the data into actionable insights is, as they say, a whole other ball game. I don’t have any firsthand knowledge of the system or much knowledge of it in general, only that of a fan listening to the information shared. Which leaves me wondering about a lot of what it does and how.

Regardless, what the NFL has done is impressive and it has greatly enhanced the fan experience for me, someone who’s always searching for patterns and asking “how” - how processes work and how processes can be improved. The operational systems side of me would love to see it in action someday and understand how it’s all working.

The past few NFL seasons have been even more interesting because of three words that have crept into the script after every 3rd down attempt fails or when a team decides to go for the extra point or two-point conversion after a touchdown. You know the one… “the analytics say…”. (The Analytics… the phrase already sounds like a named entity, and my thoughts always turn to an AI dystopia.) To add to the vast amount of data collected, organized, transformed, aggregated, synthesized, etc., and ultimately turned into meaningful insights, we now have AI leveraging Machine Learning models churning through all of that data and finding patterns of behavior and determining the most likely outcomes. In real time. It’s not just being used for the aforementioned situations, but available at every play and even being utilized for player safety. The data is coming from every single player and official as well as the pylons, sticks, chains, and balls. (Back to the skeptic in me… that’s a ton of information for an announcer to wade through while having an active dialogue. To know just where on the screen(s) to find a particular stat would take precious time.) Access to that information greatly improves the fan experience, because with understanding comes relatability, and as Aristotle famously wrote, "The more you know, the more you realize you don't know," fueling an increased desire for more. Case in point, check out the NFL article “Introducing the Next Gen Stats Decision Guide” to dig deeper.

My Customer Journey Orchestration background finds it all so fascinating. I’ve seen companies both large and small struggle for years to collect, much less connect, all of their customer data in a manner that allows for fast insights and meaningful action to improve the same customers’ experiences. It’s an ongoing effort that takes continuous planning, commitment, staff, analysis, and of course time.

On the other side of the fence, one of the focus areas in my SaaS product operations advisory work is consulting technology companies on product usage and customer adoption telemetry models, and in that work, I’ve found software companies’ customer data to be in a similar state. Even for technology companies that leverage a single “North Star Metric”. Not that a North Star Metric is bad or wrong. I’ve just seen a disproportionate or lack of focus on other factors that feed into and influence that metric. (I’ll share more on usage and adoption telemetry modeling in later posts.)

This common connected data struggle is why the NFL’s analytics solution is so impressive and fascinating. They knew the outcome they wanted to achieve and were aggressive in tackling it (pun intended). They intentionally started at the source - collecting data where it happens and when it happens consistently across all teams. Anything tracked outside of that system just can’t have the same impact.

Ultimately, I continue to ponder ways to improve customer experiences, be it fans or otherwise, across all manner of businesses through the improved collection and connection of impactful data.

I’m sure there will be more exciting advances as the NFL builds new analytics capabilities in their pursuit of improving player safety and the fan experience.

You can bet I’ll be watching, even if I’m also knitting.