Learn more about the problems we are passionate about solving. Hopefully you find this content relevant and helpful. Please don't hesitate to reach out to learn more.
Taylor Culver
Jan 2023
I’ve always been a people person. In high school and college, I was involved in a bunch of clubs and social activities. Honestly, I’m pretty simple, I just liked getting people together to have a good time. In college, I was given the opportunity to be the social chair of my fraternity - which was much harder than it seemed. Thanks for reading Data Management Survival Guide! Subscribe for free to receive new posts and support my work. It may surprise you, but it’s hard to get people to show up to parties. Especially when you’re talking about hundreds or thousands of guests. Anyone who’s spent time in event planning gets it. Getting people to show up (and pay) was a battle of communication, persistence, influence, and patience AND parties are fun, especially in college where during this time of your life, everything is exciting. Do you know what’s not fun though? Getting teams and people to collaborate with data. Especially getting cross-functional teams to work together to solve data problems. A complex, often boring, yet highly politicized topic fraught with egos makes frustration and disengagement inevitable.
I have a confession. When I became the head of business intelligence for a middle market services company, I didn’t know how to write SQL. Because I couldn’t write SQL, people challenged my credibility and I began to doubt myself.
Since then I have learned a whole slew of technical skills (including SQL) which has garnered me new levels of respect from some of the most technical folks I know in Silicon Valley.
Let me tell you though, now having spent years trying to get good at these technical skills, I can confidently say you don’t need to be a technical savant to be a great data leader. In fact, these harder technical skills, probably limit many data professionals ability to lean in on their soft skills.
There’s a big lie out there, and I’m guilty of believing it myself. Especially early in my career. Organizations are not as far along with advanced technologies than they would want you to believe. Most organizations remain hobbled by “legacy technology” or “technical debt” that prevents them from running business processes efficiently or performing basic arithmetic on core KPIs. This leaves organizations fraught with highly talented and underutilized professionals.
Vlookups anyone?
I have spent the past 10+ years working with organizations and data. What separates the good ones from the bad ones is 1) the data leader’s ability to influence, and 2) the organization’s willingness to collaborate which is a direct reflection of executive leadership.
When it comes to data, organizations are in desperate need of clarity on roles and responsibilities within the data strategy to drive real business outcomes.
Remember:
I firmly believe that for organizations to compete with data requires more of a cultural change than a technical one. Don’t get me wrong, you need databases, and reporting tools, which come with their nuances and challenges. Still, without people adopting these tools in a way that elevates their productivity they become recurring expenses without a clear link to measurable value.
Another thing I’d like to note is that companies like Facebook, Amazon, Tesla, and Google all share one thing in common - they don’t have Chief Data Officers because their teams and people know how to work with each other to make data actionable without significant executive oversight.
I’d also like to note that the average tenure of a Chief Data Officer is about 2 years.
Executive leaders need to empower a data leader from within.
Here’s why. The data leader already has the influence and credibility with their peers to enact change. Something you can’t hire for today.
The problem: they don’t have years and years of experience. Guess what, that’s OK. You can hire consultants for experience, but you can’t hire for influence.
As a data leader, your job is not to write the best query, deliver the most elegant dashboard, or bring a new perspective to your organization that radically shifts everyone’s mindset to data. But rather, your primary job as a data leader should be to bring clarity to your organization.
A former boss told me, “Taylor, what makes data hard is that anyone can have an opinion on it.” Her wisdom couldn’t be more true. Everyone wants to participate in the data strategy, they can’t help themselves, they just struggle to do so in a constructive way which becomes frustrating, and if left alone can become toxic.
Your organization craves clarity and a good story. Your executive leaders need a compelling why to focus on “data” versus mission-critical strategic topics like “growth” or “risk”. Your business leadership needs to know why working on “data” will help them win business or improve productivity.
It is human nature, especially intelligent people, to lean in on their intellect. Therefore we are drawn to complex problems. Data brings tons of complexity. The complexity distracts from the fundamentals.
When organizations ignore the fundamentals such as 1) our data strategy needs to make commercial sense, 2) in order for our organization to participate in and deliver results with data we need clear roles and responsibilities that find themselves going in circles.
Sometimes the cost of perfect data isn’t worth the expense and that’s why it remains imperfect.
Here are some guiding principles that will help you drive traction.
People didn’t come to our parties because we had the best refreshments. I mean it’s college, you’re working on a budget. When throwing parties, the first question I’d routinely get is “who else is going to be there?”
It was knowing who else was going to be there that was the motivation to show up and participate. Giving the person the ability to anticipate and plan for what they would do to prepare, engage, and get out of the experience is what they were asking me for.
To be a people-first data leader, you need to get people to understand who else will be there, what they will be doing, how they can participate, and why it all matters if they participate. Everything else is secondary - including data.
