The Downside of Data
New technology and a glut of fitness trackers are making it easier than ever to measure everything from your steps and your sleep to your bar speed and HRV. As the old saying goes, "what gets measured, gets improved", but what happens when seemingly everything can be measured?
Dude, Coach, Nerd
I'm a dude, a coach, and a nerd (in roughly that order)—by the laws of nature I'm basically obligated to get excited about new technology, especially when it promises to give valuable insight into performance. Over the years I've used various gizmos and gadgets to track my steps, my sleep, the length and quality of my sleep, my HRV (Heart Rate Variability), my bar speed, body fat percentage, blood pressure, jump height, heart rate, bar path, VO2 max... you get the idea.
While the accuracy of some of the newer technologies may be questionable, the ability put affordable technology into users hands to gather some this much raw data represents an absolute revolution in the fitness industry.
The question is, does all this technology actually make us any better, and secondly, is there a chance that some of it could actually make (at least some of us) worse than we were before?
The Upside
Despite representing a stunningly broad scope of performance and physiological data, every last bit of fitness technology is essentially offering the same promise: the chance to validate and improve upon whatever is being measured. Knowing how high you can jump and knowing your HRV score (a measure of autonomic nervous system regulation) are two very different measures, but in theory a coach or client, armed with new knowledge, can take specific actions designed around that data. For example, a low HRV score may be a sign to back off of the day's training intensity, or a reminder to put as much into your recovery as you do into your training.
The Downside
Sounds good, right? Well, that depends on what we do with all of that data.
Recently I've found myself cautioning new trainers to limit their information gathering to only those things they can and will take action on. Measuring something just to measure it is a sure-fire way to depersonalize the training experience and clutter a coach's focus. As examples: a client concerned with weight loss probably doesn't need maximal strength testing, and a football lineman may not be concerned with how many pushups they can do or what their body fat percentage is. By measuring everything, we run the risk of trying to improve everything; of forgetting the goal and just chasing results. Results are great, if they're the right results. And if trainers can get lost in too many data points, so can you.
The second pitfall I've come across is simply paralysis by analysis. Our attention is a limited resource, and is easily spread too thin. Best-selling business consultant Jim Collins is known for saying that, "If you have more than three priorities... you don't have any." If we try to measure everything at once, pretty soon we're just staring at a bunch of flashing lights on a variety of tracking devices.
"If you have more than three priorities, then you don't have any."
–Jim Collins
The third data-driven pitfall I see people stumble on is a case of misusing the information they're given. Here's a simple example: someone hoping to lose weight buys a fitness tracker that tracks their activity level and gives them an estimate of the total calories burned over the course of the day. In theory this encourages the user to be more active. In practice, this sometimes results in the user deciding they've "earned" that dessert; just look at how many calories they burned!
I've seen HRV monitoring drive a similarly inverted dynamic: while lower HRV scores are indicative of more a more sympathetically-driven autonomic nervous system and can be used to adjust workload, they can also be a reminder to the athlete or client to ensure they're taking care of themselves outside of the gym. Too often though that steadily dropping HRV score becomes a reason not to train hard rather than a reminder to recover a little "harder".
The Bottom Line
In the spirit of the following reccomendations, let's keep this simple and bullet-point it.
Unless the data gathered will inform or change a behavior, skip it. Behaviors win. Every. Last. Time.
Keep data (and related goals) in alignment; working on sleep quality and HRV is probably a better choice than working on max strength and VO2 max.
Choose the three measurements that best inform the desired outcomes and behaviors, and put the rest away until they fill a need. Don't use a hammer when you need a wrench.
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