New to data leadership? Join the club. 

As someone with 20 years of experience in the digital analytics space, I’ve spent some of my career as an individual contributor but the bulk of it in management. Sometimes I’ve had direct reports, sometimes I haven’t. Most recently, I’ve taken on my first director role, which has prompted me to pose a whole new set of questions on how to best manage my own time and that of my direct reports. Ultimately, I needed to understand how to become an effective data and analytics leader.

Part of the challenge of all this is that I’m not aware of any defined course or guidebook on how to train junior analysts, something that lays out “Here’s a good way to nurture an analyst and let them develop versus dictating how they do something.” This is increasingly important in my view, because the fight for strong data is showing no signs of letting up.

Until such a guidebook comes along, here are a few data leadership strategies I’d recommend that you consider.

  1. Embrace diverse approaches. I am the first to admit that I think of myself as a perfectionist, and therefore have firm opinions on how to do things, especially when it comes to an analysis. But as a data leader it’s important to remember that there are typically multiple approaches, and one is not necessarily better than the other, as long as it gets to the right end result. One thing I’ve learned as a leader is that everybody’s process can differ based on what you’re trying to look at and analyze. And I’m sometimes pleasantly surprised when I learn something from an analyst in terms of how they’re looking at a problem. So offer people enough free rein that they feel like they can take a more creative approach to a problem on their own, without having it feel 100% prescribed.
  2. Coach, don’t micromanage. Part of letting go is giving a direct report a chance to take a stab at something on their own, instead of falling into old habits and taking it back over. Resist the urge to say, “You know, I’ll just do this” Or just as bad, don’t hand someone a project and then micromanage them – telling them how you’d do it, and then taking the first stab at it to show them. This behavior does not inspire confidence in your powers as a leader. Instead, check in with them from time to time and offer tidbits of help and advice along the way.

    Of course, managing people and priorities is fine and helpful in terms of the day-to-day logistics of doing a job. But if you’re really coaching somebody and developing them, you care. You want to see that person succeed. From the analyst’s perspective, they will appreciate when someone is taking the time to develop them and tease out their strengths. This will give them more confidence while strengthening your relationship. It also shows that you believe in that person and want them to reach their potential, so they will work harder to get there.
  3. Trust in the process. On a personal level, I try to really trust the people I work with and trust that they know what they’re doing. If your inclination is to be too deep in the weeds and go table by table through an analysis, step back and try to give your direct report some free rein, see where they go with it, and help and guide them to a more narrow focus if needed. There’s a lot of creativity in digital analytics, and you have to let people tap into it. 

    The other part of trusting in the process is to hire people you trust. Analysts I interview have to show me they’ve done some work, they understand how data is captured, and they have a technical foundation to at least say, “Okay, here’s how the data is being collected, and based on that, here’s how I can analyze and interpret it.” If I feel like you’re worth taking a gamble on or a risk, and to develop you more, then I’ll do that. If But if you hire people who don’t know the basics and know what they’re doing, a lot of the work will bounce back to you.
  4. Mentor the presentation as well as the analysis. One area where experience really does come into play is presenting to an audience. More junior analysts have a tendency to present their work as, “Okay, here’s a dashboard, here’s an analysis, and have at it. It’s pretty self-explanatory.” But that’s almost never the case. Good analysts are curious at heart and will always figure out how to get to the insight they need. Where they need coaching is in evangelizing, socializing, and explaining their work. So help people by getting them to ask a few questions before they present. For example:
  • Why should anyone care about this visualization?
  • What do I want people to get out of it?
  • How do I get them there without overwhelming them?
  • How do I encourage questions? 
  • What would my recommendations be based on this analysis?
  1. Cut yourself some slack. After years of management experience, I still occasionally give in to a bit of Imposter Syndrome. How do I know I’m the right person to lead this team? If you do feel this way, pause and remember that you know a great deal, that there is a lot you can help your direct reports to do, and that you can trust your experience and instincts. Resist the urge to hang back and let someone else handle things. Being a data leader and implementing a workplace data leadership strategy will require you to push yourself forward. The other reality is becoming comfortable with the fact that data teams are almost never staffed appropriately. Certainly they are more rounded out than when I started in this industry, but don’t beat yourself up for feeling like you’re behind the eight ball. That’s always been the case on some level.

Stepping up into leadership
While we are coaching and mentoring our direct reports, the other thing we can’t forget to do as data leaders is to earn our seat at the table. For example, if you’re collaborating with the CMO on questions of what visitors do when they get to your site, where else we might be targeting that traffic, and where we can do A/B testing, you build a tight and necessary relationship between analytics and marketing teams. In order to do that, Marketing has to explain what their strategy is, what’s going on the marketplace, and what they’ve seen. It’s very difficult to analyze an ambiguous question when you don’t know the whole context. 

As more companies realize the importance of analytics and why they need it, it’s up to us to show our organizations how to become more data literate, how to act in more data-driven ways, and how to use data to drive the business. Developing comprehensive organizational strategies as data leaders is how we turn analytics from a supporting team into a Center of Excellence. Which, incidentally, will go a long way toward attracting the next generation of data leaders.