Taking Pole Position in Your Industry: Agility in Formula One
Truth be told, most large organizations don’t exactly resemble perfectly tuned machines. In stark contrast is the breathtaking teamwork, focus, and precise execution we witness during Formula One (F1) pit stops. An F1 fan myself, I will explore the world of F1 in this blog post about digital transformation. Why? Because behind each on-podium champagne shower stands an ultra-high-performing, innovative, agile, and data-led organisation, obsessed with continuous improvement.
As much as the pit stop draws the attention, it actually isn’t the best example of collaboration in F1. In a pit stop, each individual performs a specific task with little interaction and with hardly any need for communication or creativity. The only interdependence is between the finish of one task and the start of the next and at the completion signal that releases the car back into the pit street.
So, let’s look beyond the pit stop to what F1 teams can teach us about agility, innovation, and the right culture.
The first thing that sets an F1 team apart from most organisations is that F1 employees chose to work in the industry out of passion. They love racing and passionately want their team to succeed. You’ll realize how emotionally involved everyone is when you see the reactions in the garage when a driver overtakes a rival or crashes out. No need to measure employee engagement scores through a survey! I’ve experienced similar passion when I was CIO at Airbus and Qantas, and in certain humanitarian organisations for instance, but it’s all too rare. Yet when your employees believe in what your organisation does, it gives them the energy, motivation, and even courage they need to perform at their best. It’s a force multiplier! Invest the effort to define purpose beyond profit. Make it genuine, meaningful, and differentiating. No one beats the Monday morning blues with a vague mission statement that could apply anywhere.
What Does Success Look Like?
Once the mission is clear, you need to define success unambiguously and ensure that it’s measurable. F1 teams have two simple scorecards that provide this clarity: the drivers championship and the constructors title. The former tracks the points accumulated by each driver during the season; the latter does the same by team (each of which has two drivers piloting the same car design). Of course, the teams operate within constraints like driver safety and budget caps, but the goals are really the two titles. Every Sunday evening on a race weekend, every member of the organisation learns for certain whether their team was successful or not. That’s far from true in many organisations that I talk to. In the words of Toto Wolff, Mercedes Petronas team principal, “In business you can always find excuses. You can twist the story in your favour. But in motor racing, the absolute truth of the stopwatch will tell you whether you have done a good enough job or not.”
Everyone Is Needed
Clarity in purpose and explicit success measures define the collective outcome. Successful F1 teams also ensure that each employee, from the pit crew to the administrative office staff booking the flights, understands their contribution to success on race day.
Ask a few of your employees how they think their job contributes to the organisation’s success. It can lead to fascinating discussions and will teach you a lot about your people, and what the world looks like from their viewpoint. A few years ago, I decided on a radical organisational change after putting my full organisation chart up in my office. I couldn’t understand the purpose of over a fifth of the boxes on the wall—not a great sign of clarity of contribution.
Data Drives Decisions
OK—we have a meaningful mission, our measures of success are clear, and our teams understand their contribution. Now we need to think about the how, the way in which we execute.
Knowledge is power. In F1, that’s literally the case with so much focus on improving the power unit of the vehicle. F1 cars are full of sensors that spew out terabytes of data for analysis and simulation. Every decision during a race, from timing a pit stop and choosing the tyres to engine settings and brake balance, is grounded in granular data. Every design change and engine tweak is judged by confronting it with car performance data. Only the data decides, not politics or status. And you will not see anyone “polishing” the data as we see in large organisations; while doing so might keep management happy for a moment, the disillusionment would be all the bigger when the reality hits on Sunday.
Beyond understanding reality, data makes it possible to (virtually) explore situations that have yet to occur. F1 simulation capability has achieved astounding accuracy. Even the best drivers spend hours in simulators to better understand the dynamics of their car and to eke out another tenth of a second of performance.
Making data central to decision making and using it to simulate scenarios can help most organizations eliminate biases and envision the future. Interestingly, as much as the F1 teams use data, they also recognise its limitations. To complement the hard measurements from the hundreds of sensors, engineers pay special attention to the “feel” of the car as experienced by the driver. Sometimes the data indicates all is OK but the driver senses something is off. This interplay between objective measurements and human observation is even more powerful than data alone. As Jeff Bezos said, “When the [customer] anecdotes and the data disagree, the anecdotes are usually right.” Data are objective, but they can come from faulty sensors, be incomplete, or need more context.
Speeding Up Innovation
High performance is not a matter of one-off optimisation. F1 teams make thousands of modifications to a car in a season, even during the race. They improve performance in general, but also adapt it to changing circumstances such as grid position, track and air temperature, altitude, and race situation. Of course, it takes a big effort before the start of the season to design and build the best possible car, but that’s only the starting point, not the finish line. In contrast, how often do we see large organisations focus all their effort on a Big-Bang go-live date, with few people available or accountable for tuning and optimization after that day? In doing so, they forego many potential benefits. There is no way that every need, requirement, or opportunity can be identified in the planning and design phase without being tested by day-to-day reality.
Continuous improvement also reduces risk compared to big leaps into the unknown. It allows us to learn and discover needs and potential solutions as we go, leading to better, faster innovation. Another sizeable benefit of building constant change into your operating model is that you can deal with change and uncertainty better than your competitors. Most organisations I talk to optimise for stability and have mechanisms that prevent rapid adaptation. To thrive and grow, you need to learn to pivot rapidly.
Free the People
The mind-boggling rate of innovation and adaptation we see in F1 requires highly empowered teams and employees. Imagine if the overhead in decision making and approvals we’re used to in the corporate world were applied to every design change of the car. Of course there are decisions with irreversible impacts that do need approvals from outside the team. But it is clear when that is and is not required. The bias should be towards trusting the competence of the teams and making them feel accountable instead of requiring constant management approval.
Some executives fear autonomous teams will create chaos and anarchy. This fear is understandable when their organisation lacks clear purpose and unambiguous ways to measure success. If these are missing, autonomous teams will indeed lack a compass that ensures collective success.
In one of my roles as CIO, I visited a number of business teams that delivered extraordinary results implementing small-scale autonomous teams. These teams delivered better quality, lower cost, and more employee agency. But executives never scaled up these initiatives to the enterprise level because they feared loss of control: they believed the only way to align teams was via direct hierarchical oversight.
Back to the Pit Stop
I mentioned in the first paragraph that the emblematic pit stop isn’t the part of F1 we should look at for innovation and agility. So instead, we looked at purpose, metrics, motivation, employee contribution, use of data, iterative change, and empowering people. And yet the highly standardised pit stop delivers astonishing results and often has a make-or-break impact on the race. The high degree of standardisation is actually perfectly fit for purpose for pit stops, even though it would never work for aerodynamics optimization, for instance. This shows us two final important traits of high-performing organisations: knowing when and what to standardize or automate, and when and where to empower smart minds to solve complex problems together in creative ways. The need for organisations to become more agile and innovative for customers doesn’t mean that every task or area needs to bubble with creativity and reinvention. That would be swinging the proverbial pendulum way too far to the opposite extreme. But organisations and their customers would tremendously benefit from riding that pendulum a fair way towards less rigor and more frequent change.