The One Formula for Metrics
Tags: Lean, Performance Management, Metrics, Agile, Software Development

The One Formula for Metrics

by Antony Marcano

Lewis Hamilton, 5-time Formula One World Champion by Morio, from Wikimedia Commons

When competing at the top tiers of motorsport, from sports & touring car racing to Formula One, huge quantities of real time data are the difference between qualifying first or second.

Drivers like current F1 World Champion, Lewis Hamilton, are competing for that last 0.001 of a second. This can be the difference between winning or losing the race. A significant amount of both real-time and post-race data is there just to help the driver improve their performance.

Many lean and agile teams leap to introducing their equivalent of Formula One levels of team-improvement metrics and data–well before they’re ready to. They overburden themselves with swathes of Software Development Performance Index (SDPI) metrics, infinite amounts of code-quality metrics, cycle-time, lead time, variance, and so on — because they’re the ones to have, right?

When starting your journey into using metrics and data to drive team-improvements, you can choose your metrics more wisely…

When you start learning the basics, a stop watch is enough

75mph Junior Rotax Kart piloted by a 14 year old Damani Marcano

The road to Formula One, and many other forms of racing, begins in professional-grade racing go-karts.

Karting at this level can end up with hugely sophisticated levels of data analysis, but the lesson is really in how the young driver gets there. One metric at a time…

When you start learning the basics in a kart, a stop watch is enough… F1 amounts of data will do more harm than good at this level.

At first, you work on basics. The racing line, braking, steering input. Once you can take the kart round reasonably consistently, with visibly good technique and on the racing line, a stop watch is no longer enough. Now you want an electronic dash to log sector times (tracks are split into 3 sectors).

An electronic dash and sensor unit showing actual vs. theoretical lap times.

Now you see the delta between your actual time and theoretical best, based on your best sectors across all laps. You can see, which sector makes the biggest difference. You focus on improving that first. What you learn improves the other sectors. You’ve improved your skill.

After much practice, you are more consistent in a lap and in each sector. What you need to improve can’t be seen with the naked eye. The variance is too small and open to perceptive distortions and bias. Now you need to know time deltas corner to corner.

You plug your electronic dash into a computer to graphically analyse time–deltas. You see lap times are consistent but there’s big variance between corners lap to lap. You try to get these consistently matching your best–one corner at time.

It’s about the right speed at the right time.

Damani Marcano & kart racing coach Terence Dove, analysing performance data.

You need to know why your time was better between two corners on one lap but slower the next.

You start looking at speeds: corner entry, minimum (mid corner), exit & top speeds in your data logging software. You look for where you are going too slow, even too fast into each corner.

You carry more speed mid corner in one. You brake sooner and harder to slow down enough in another. It’s about the right speed at the right time.

Now you need more data… And so it continues. A never ending cycle of new questions, new data, more precise and more focused to super sophisticated levels of analysis, even before stepping up into a full-spec race car.

Damani Marcano, age 16-17, in the 2017 Volkswagen Racing Cup, Brands Hatch,

Some organisations and software development teams take on too many metrics too soon. Just because that’s what others measure doesn’t mean that’s what you’re ready for.

Focusing on what you need for where you are today will get you better, faster, sooner.