At first glance there is not much similarity between a Formula 1 team and the public sector. High speed cars, intense on track battles between drivers and stunning views of Monaco harbour is not what comes to mind if you think of government work. However, to both compete in F1 and provide services to citizens, data management is key. Success relies on teams being able to find and analyse the right piece of data in the proverbial haystack as quickly as possible whilst reducing costs as much as possible. This is a format that F1 teams have been working to perfect for decades, and recently a new tool has been added to their arsenal in the form of modern data and analytics platforms using artificial intelligence (AI) and machine learning (ML). Whether it’s analysing wind tunnel data to perfect the shape of the car, or reacting in real time during a race to update strategies, digital tools are turning data into actionable intelligence. Similarly, UK Government has implemented significant data and digital tools to enable policy making in response to the COVID-19 pandemic.
Winning a grand prix takes more than just the driver and a car. It relies on teams of engineers, often distributed across wherever the race is in the world that weekend and their home base. These teams need to sort through vast amounts of data produced by the hundreds of sensors on the car, and find the right piece that can help them shave a few seconds off their time, which in F1 can mean the difference between 1st and 14th in qualifying. Without AI and ML, this process could take hours, but instead it can be done in a couple of minutes, and then shared with the relevant people in real time, saving valuable time.
This dynamic working style is already seen in UK Government with, for example, the “check an HGV service” that was designed to keep goods flowing across the border as seamlessly as possible for Dec 31st 2020 and involved cooperation between 26 different departments. This success should be replicated across government, ensuring that teams are able to find and share the most important data to make the decisions they need to provide a high quality service to the UK public. Government already has several data sharing programs between departments, including examples such as the Food Standards Agency and HMRC.
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Working within budgets and at speed
It is no secret that the last year has put public finances under a big strain, but even before this budgets had been shrunk year on year. Meanwhile, people want a modern service that reflects their experiences with other innovative companies like Amazon or Apple. Again, there is a parallel between UK Government and Formula 1 teams, which are required to work within a strict cost structure, and find new ways to engage with their fan base. For example, automating the lower value, repetitive tasks through the use of AI and ML, and keeping better track of inventories with new IT systems to prevent waste provides significant cost savings. Allowing teams to focus scarce resources on the areas that make a difference to performance and service deliverables to citizens.
As well as working within a tight budget, there is often a need to complete projects as quickly as possible. In F1, this means finding improvements to the car before the next race, while for Government it is responding to a national problem to support citizens. A good example of this is the job retention scheme from HM Treasury, which helped 11.3m people remain in work and 1.3m employers stay afloat. This was rolled out in a matter of days, a feat that would have been near impossible to achieve with systems of the past. Likewise, the mobilisation of resources to create the COVID contact tracing app and Lateral Flow Testing; which has been used to help manage the pandemic and support early prevention. These initiatives relied on teams using the latest technology to empower employees to be able to make important decisions and enable effective policy decisions.
The parallels between the public sector and F1 demonstrate how all organisations can approach digital transformation to get the most out of data either to compete effectively or deliver efficient services to citizens.