Data Cloud and Formula 1
Everybody loves Formula 1
None more than Salesforce with their sponsorship and customer stories about how Formula 1 is transforming the way they engage with their fans using data.
Formula 1 is a Data Cloud success story. The numbers speak for themselves:
- 500 million fans, growing 30-40% YoY
- 1% of fans attend a Grand Prix in person
- 88% fan satisfaction
Data Cloud enables Formula 1 to connect fan data across properties in real time, delivering better fan experiences and creating customer loyalty. For instance, when fans sign up for an event through the Formula 1 Paddock Club, an immersive, onsite luxury experience, brand representatives can know fans’ names, engagement history, driver preferences, and past purchases from the moment they walk in. Post-race, Formula 1 can personalize follow-up communications with mentions of their favorite driver or merchandise they might like based on previous purchases.
I love car analogies
So I want to use Formula 1 as an analogy for Data Cloud.
We’ve seen interviews with Formula 1 drivers and heard about their amazing lifestyle. The adrenaline rush of driving a Formula 1 car at nearly 200 miles an hour. Traveling the world. The parties. And the grueling fitness regime.
We just get a glimpse of what it’s like to be a Formula 1 driver. Even the Drive to Survive TV series was a snapshot. We don’t see what it took to be a winning team. And that’s rather like the Salesforce success stories that we see for Data Cloud. We get a glimpse of the benefits and the results. But not the detailed step-by-step process. Hint: It doesn’t start with “Install Data Cloud”.
The beginning of the journey to be a Formula 1 driver starts with the Formula 1 simulator to learn to drive a Formula 1 car. Hopefuls come out after hours or weeks with a certificate that says that they can drive a Formula 1 simulator – not a Formula 1 car. For those of you thinking, “I’ve driven sports cars. How different could it be?” Here is a Formula 1 steering wheel.
Thinking about the Formula 1 simulator from a Data Cloud perspective, this is the same as doing the Data Cloud Boot Camp, one of the 3rd party courses, or reading the books, and passing the Data Cloud Consultant certification. In essence, you understand how to configure Data Cloud. You understand the scope and the functionality, and when to use it.
Driving a car on the Formula 1 simulator is not the same as driving a Formula 1 car around a Formula 1 circuit surrounded by other Formula 1 drivers who are equally committed to winning. No simulator can prepare you for that. The heat. The G forces. The noise. Forget winning.
Simply finishing a race without crashing is a major milestone.
To race – cancel that – to even finish a Formula 1 race requires an entire team of experts. It’s not just about the Formula 1 driver – whether they are capable of driving the car. That’s exactly the same with Data Cloud. To deliver it successfully – no cancel that – to even get the correct data out of Data Cloud will take a team of experts.
So there is a hell of a lot that goes between the hopeful driver in a simulator to completing your first F1 race. Most of what the F1 team does is before the race. The race is a fraction of the effort. This is similar to Data Cloud. Salesforce is saying that Data Cloud is 80% planning, 20% build/configure. From our experience, it is probably 90% planning and 10% build/configure. Data Cloud is configured using a familiar interface and is straightforward, once you are clear on what you need to configure.
BTW Here is what a simulator looks like. Yours for $50k to install at home.
And here it is in practice.
Racing F1 is not the same as watching F1
There is no shortage of consultants who’ve been on the simulator and attended a Formula 1 race and will tell you that they will help you be a Formula 1 driver and compete in a Formula 1 race. They’ve never done it, but they’ll learn with you.
We’re seeing newly certified Data Cloud Consultants offering to help you with Data Cloud. But have they actually done it? Do they know what it takes? Do they know the limitations and the workaround that are required? They’ve got the slide decks but do they have a proven approach? They’ve got a certification but do they have a set of tools/accelerators that they know work? They have confidence but do they have the experience? They could be learning with you and maybe failing with you.
Data Cloud is a new product so there are not many deep Data Cloud implementations – yet. At Dreamforce there are a handful of sessions by organizations who have actually delivered Data Cloud projects and are talking about their approach and what it took – Ford, Flight Centre Travel Group, Elements.cloud, Cognizant, and First American Title. In contrast, there are probably 5x as many sessions on how to configure Data Cloud. And for most people learning Data Cloud is the first step. It is important but not enough.
Here are the DF24 sessions that are talking about implementing Data Cloud.
Ford
https://reg.salesforce.com/flow/plus/df24/sessioncatalog/page/catalog/session/1718915779670001QA5v
Flight Centre Travel Group
https://reg.salesforce.com/flow/plus/df24/sessioncatalog/page/catalog/session/1718915783372001QW9L
Elements.cloud
https://reg.salesforce.com/flow/plus/df24/sessioncatalog/page/catalog/session/1718916059353001QEPG
https://reg.salesforce.com/flow/plus/df24/sessioncatalog/page/catalog/session/1718915652577001QQLA
Cognizant
https://reg.salesforce.com/flow/plus/df24/sessioncatalog/page/catalog/session/1718915996812001Q5fR
First America Title
https://reg.salesforce.com/flow/plus/df24/sessioncatalog/page/catalog/session/1718915990613001Qjfj
Implementation Best Practice
Elements.cloud has also documented the implementation process down 3-4 levels as a UPN process map. This is being made available to anyone. This means that any one of you can follow it and deliver a Data Cloud Project. It includes links to valuable training, help articles, and templates for the documentation that you need – process, DFD, ERD, metadata dictionaries, and user stories. Yes, you will need documentation. Data Cloud will punish you if you don’t implement in a rigorous way with good documentation.
Here is a video of the approach
Getting started
For the first F1 race, let’s pick the most forgiving circuit. So, not Singapore. Singapore is easily the hardest. Two hours of pure concentration in high humidity and heat, with relatively few straights to relax. One mistake could wreck your car on every single corner. Runoffs aren’t a thing in Singapore. Australia’s Melborne has definitely got to be the easiest. It’s a point-and-squirt track. The weather is mild and although it is a street circuit, it has a proper race track feel to it with it having plenty of grass and gravel runoff areas.
For the first Data Cloud use case, pick something that is simple technically and has the fewest politics. Something that can deliver some benefits, but can build confidence and momentum with Data Cloud. Quickly.
You need a COE
I wrote an article talking about a Center of Excellence (COE) and making the analogy with a race car team and the executive support, team, standards, and tooling that you need to be successful. A COE was a great idea for a complex Salesforce implementation, but I would suggest that it is a prerequisite if you are planning on implementing Data Cloud. A COE will make sure you have the core competencies in place to deliver the project successfully.
Data Cloud requires a structured, rigorous implementation approach. It is a cross-departmental project which means you need executive sponsorship to resolve conflict and agree priorities. You need good documentation standards to support your business analysts and architects through the planning phases. Data analysis and data governance will be central to the project, so you need great metadata management. Expect to invest in tooling (Elements.cloud) to support your teams and ensure coordination. You cannot, and will not be successful, using adhoc GoogleDocs and GoogleSheets. Unless of course, the scope of Data Cloud is trivial and you have no plans to build past your initial use case.
F1 vs Data Cloud
Here are some aspects contrasting Formula 1 and Data Cloud
Vision
F1: Win a race
DC: Personalized customer engagement – Customer360
First milestone
F1: finish a race
DC: 1st use case
Budget
F1: $657,837 to enter the team… then budget to run team, capped at $135m
DC: Starting at $0 (consumption based pricing)
Team
F1: owner, race director, engineers, logistics, data analysts, pit crew, driver….
DC: exec, project manager, business analyst, data analyst, architect, Data Cloud consultant, Admin, Dev, Release Manager
Product
F1: car
DC: Salesforce and Data Cloud
Approach
F1: Plan, processes, documentation, metrics, tooling
DC: Plan, processes, documentation, metrics, tooling
First use case
F1: Singapore: lots of run-off
DC: Simple use case, unify individual
Summary
There are strong parallels between finishing a Formula 1 race and implementing Data Cloud. In comparison, implementing Salesforce is driving your EV to the shops. Cooler, cleaner, and more efficient than that 1970 pickup. But within the reach of everyone with some training. Don’t underestimate what it takes to race an F1 – or implement Data Cloud.
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7 minute read
Published: 29th August 2024