It’s a frustrating but common experience for an aspiring data leader to put in a lot of work on a complicated data analysis, build a beautiful presentation, then watch it fall flat when leaders and program stakeholders clearly don’t understand the impact of the analysis. 

These experiences often reveal a gap between what the content creator wanted to present and what their leaders saw. Part of maturing as a data leader is realizing that managers in your organization see things from different perspectives that may go far beyond the program at hand, and that part of your growth is a function of helping them see the local but also the system-wide impact of your data.

Bringing together our experiences as individual contributors and managers in a large data-driven business, here are some strategies you can use to level up on your data leadership skills and the data talent of the team members you mentor.

  1. Explain what the numbers are saying. Your data must be verifiably accurate, of course, but what conclusions should stakeholders be taking away from it? Asking yourself this question in advance and having well-reasoned answers will make for more successful presentations and raise your profile as someone who has a more strategic perspective. Remember that data is not just a random collection of numbers: data insights and recommendations are products that you can manage, promote, and evangelize.
  2. Deepen your data empathy. As you’re pulling data for your next analysis, creating findings and making recommendations, it’s important to build data empathy. This means asking what your findings mean for the organization as a whole and whether you can link any of your insights to support broader priorities. Empathy comes into play by thinking through the potential implications of your analysis to stakeholders from product managers and software engineers to enterprise architects and even your legal department. If your data suggests that a change in a product or service is warranted, how could the impact extend your circle of stakeholders, to their stakeholders, and even to up to your C-Suite? 
  3. Build your change management skills. Making the most of your data analysis is a form of organizational and people change management. It therefore requires that you become adept at creating a cycle of impact, based on knowing:
  • who you’re looking to inform
  • what’s in it for them  
  • how you want people to take action
  • the outcomes you’re looking to generate
  • who might help you manage any resulting change (and who their stakeholders are)
  • the potential outcomes and impact
  • how you’ll measure that impact

    Start by looking at the dashboard you’ve created. It’s only truly effective if you know what you want to do with it, what its implications are, and who you need to convince. 
  1. See data from both sides. There are often benefits to unlocking insights, but risks and implications as well. Sometimes the findings you uncover are not what you wanted or anticipated. Part of leadership is considering the risks to you, your company, team, organization and partners. Your role is not to hide these implications, of course, but to be ready to discuss what they mean, and whether they should lead your organization to de-emphasize a certain course of action. Also be ready to handle exceptions. For example, you may meet colleagues who disagree with your source data even after you’ve demonstrated that it’s clean. Sometimes the only way to allay their concerns is by influencing someone they trust. 
  2. Manage up and out. Unless you know what your managers (and their managers) are thinking, it’s nearly impossible to understand their perspective and interpretation of topline business goals. It’s also easier to inadvertently leave them out of your considerations, so make the time to manage up and out. Meet with leaders, attend their meetings as an interested listener, talk to them about their stakeholder groups, and learn how they think about the role of data – and what you can teach them about it. Ask them about what’s on their radar. But also ask what’s not on their radar, because understanding what isn’t a priority to someone is often as important as knowing what is. Knowing managers as people and not just professionals also helps you to take on a leadership perspective; one that, ideally, you’ll be adopting soon enough yourself.
  3. Practice good data politics. What is holding the next generation of data leaders back from going to senior levels? It may be the things that are left out of conversation and feedback. A direct report may be a very strong analyst with great technical domain skills, for example, but they may not be aware of what they need to work on to move up. It’s on us as data leaders to articulate those things and say them out loud. You can call this practicing data politics, but that doesn’t need to be a bad thing. Data politics are just organizational dynamics that need to be addressed as you manage people and help them define the right path forward.
  4. Think at scale. Being excellent at your job is a prerequisite for any role in data, but you always should be looking for ways to connect the dots between what you’re working on and the organization’s top priorities. A powerful term for this is thinking at scale. The next time you have a high-stakes presentation coming up, build a great presentation where the broad implications of your analysis are clear. Include all the information you need to, but don’t read it off to the room. Instead, tell a strong story in a fluid but compelling way. Use human language to make sure that people who don't have the background or have daily contact with you understand your work. And be aware of who has shown interest in your work and who you’ve had trouble influencing in the past.  

As we work to improve our organizations’ data talent and train the data leaders of the future, we also need to advance in our own careers. That’s why it’s critical that we build not just a great data viz, but a great data network. We need to become better data influencers, creating impact that extends to our teams, our departments, our companies, and even our industries. That’s the scale where the power of data truly creates meaningful change.