Data Teams as revenue generating function
Couple of thoughts on how I see data teams can bring in more measurable contribution to the company
Let’s start with several positions on how data teams are perceived in different companies.
Data companies and data-driven companies
An essential part there is data culture. When I talked on my podcast with the CTO of one Data Company, it was pretty evident that data is an asset for them; they have data governance meetings where all departments by the function come in and discuss potential changes or when it’s needed to add more information and how it will affect other teams. A high level of trust and established data contracts allows them to move fast and efficiently, especially when data is involved. This minimises friction between data teams and other parts of the organization.
So these companies have a clear vision of how data brings revenue. It’s a product that they offer. The data team’s role is crucial for their success. I guess no point in continuing since it’s not that frequent in at least my experience.
Support function only
From my experience, I see that many companies are saying that we’re data-driven and doing this and that with our data. The thing is that usually, data teams are viewed only as support functions. You go to them only when s$$t hits the fan. I’ll cover couple of situations that leads data team to be stuck in this position.
Mindset
Many companies say they're data-driven, but it’s gut-feeling-driven or highest-paid-person-decision-driven. Both of them are similar but also quite different.
To shift from this is super hard, and it’s because it’s a behavioral change. Moving from gut-feeling-driven is easier since you have the data, insights and suggestions that pan out as accurate while gut feeling was wrong. The gut feeling will adjust and be more data-informed, so it will most likely become a combination of gut feeling and data-driven and evolve based on the data you’re being shown.
Moving to highest-paid-person-decision driven is super hard. In a lot of cases, it’s actually because of ego and not willing to admit mistakes. Since it’s the highest-paid person replacing them is tricky - usually because it’s upper management. I’m not even sure how to get out of this situation if you’re in this one - good luck and write me up if you have a solution for this; very interested to hear.
Constant fire-fighting or priority shifts
Not sure how about you, but I’ve witnessed a lot of situations where you plan things, but suddenly something goes wrong, and you have to drop everything and help out. Sure, it makes sense occasionally, but if it happens constantly - you can’t focus on anything long-term since you already know it won’t matter. Remember that the data team is all over the place with constant context switching and working as an actual service centre. Here’s a ticket; complete it. Oh - you’re done? Here are five more that accumulated while you were finishing the previous one. It’s not sustainable, and you won’t have people bringing you insights or suggestions on what to do next when they have a non-stop flow of requests.
Transformations
Even if you’re moving to more data-driven approaches, there will come a time when one setup will not work, and you’ll have to switch. I.e. Centralized → Decentralized, or vice-versa. I’ve seen some situations where a team is stuck in the middle and unsure how to move forward. Kind of clear responsibilities, but you’re still heavily covering other areas while they’re not your primary responsibility. You’re now stuck with commitments to specific areas, but fire-fighting and context-switching are still.
Vision and commitment to it
In my eyes, what can help here is to set a clear vision of where you want to be and commit to it. This boils down to dealing with other stakeholders and often pushing them back. If you don’t have good fundamentals, you’re making a GIGO approach (Garbage In, Garbage Out).
Couple of moments that it also heavily relies on the team you have. You might need more senior people to accomplish this crusade. In some cases, more strict approaches must be taken, saying exactly what needs to be done and checking upon status until it’s done. It might look for some members as micromanagement, but it will be fine if you handle the communication well. This, in my eyes, applies to a more junior concentrated team - you can’t expect people who didn’t see the good approaches just magically to come to them. Your job is to navigate them, steer where needed, and sometimes take action yourself.
From the manager’s perspective, your job is to be an umbrella - know the workload, how the team feels, and what’s on their plate and steer the bulls$$t away. Keep teams focused on only a couple of things. Less context switching and showing that you are committed to what was agreed and how it aligns with your long-term vision.
Metaphorically speaking, if we’re floating in the middle of the ocean and we’re not seeing a coastline anywhere, it doesn’t give me much motivation to try to achieve it. Rowing in one direction at least gives a purpose and belief that maybe you’ll see a coastline at some point instead of switching directions often and going back and forth.
How can the Data team bring money to the table?
Let’s say you're doing quite well. All of the abovementioned things are starting to disappear. You’re heavily involved in different areas; people deliver insights, suggestions and even data products. What’s next? How to make data teams revenue-generating?
I think that data teams are always, in one way or another, a revenue-generating function if decisions are based on data. The only issue is that it’s hard to measure, or no one tries to.
To achieve this data team has to measure changes and impacts of their enablement of others and get revenue attribution from the same sales and engineering teams. It’s a group effort. Similarly, as marketing attribution is done, data team attribution/contribution should be made uniquely based on the situation. The only question then is left: value vs cost.
Let us check on the importance of the different components involved. Each company has people, tech and processes. In my eyes, people are always a key component. People choose technology; people build processes too. Now looking at the processes vs technology. Without technology, in my eyes, even if you have all processes in place, it might not scale or work at all. So get an MVP with People and Tech and scale it using the processes. I might be heavily influenced by the fact that I come from the engineering side, and to me, some parts of the processes are heavily embedded in the tech itself, but this is still what I believe to be the priority of these three.
Take it with a grain of salt since I’m making these assumptions based on my experiences and exposure to different company sizes. People call the shots and prioritise what gets done when also the industry. My approach is to go fast, break things, fix them and go faster. Processes slow us down, but in different scenarios, they empower people and make uncertainty disappear.