Imagine you’ve joined a 1000 person company as their new head of data. What do you do first? Here’s a blueprint that I follow as a consultant, take what you’d like for your leadership role.
Focus on people and pain points
Don’t start with tech. Start with listening. Implementing a new stack won’t win you any points with anyone. The first two weeks you should reach outward. Meet with the leadership of each department, ask them how things are going, what their gaps are, what data would help them make better decisions. Prioritize.
Get one quick win
Of the pain points you just heard, pick one. Not the most technically interesting. Pick the one with the biggest business impact and the widest visibility across leadership. Did the COE have a pain point?
Find a way to solve it fast. A POC, a dashboard, a cleaned dataset. Get it done in a week. Then iterate based on feedback.
This serves a few purposes: you prove value immediately, you learn how the organization actually operates when it comes to data requests, and you learn one area of the business.
Focus on leadership
You’re a data leader, not a data builder. Yes, you’re probably a killer analyst or engineer but that’s not your job anymore. Your job is to unblock your team so they can ship. You can’t write all the code yourself, and frankly, you shouldn’t write any of it. Instead, focus on hiring, mentoring, and removing obstacles. Build processes that let your team move fast without you being the bottleneck.
Keep the team lean
I mentioned focus on hiring, but I don’t mean grow a large team. In the first 30 days, determine the smallest team that can actually do the job for this org.
I love the idea of having one analytics engineer or SME per business pillar. Individuals who deeply understand their area of the business and become trusted partners to the business team. They’re not just answering questions, they’re extensions of the team. How many you need depends on three things: the complexity of your business, the variety of data requests, and your organization’s appetite for data. Let those constraints dictate your hiring plan.
Evaluate Infrastructure
By now, you’ve been passively evaluating the company’s data infrastructure. You’ve sat with teams, understood their workflows, and noticed the friction points. You know where data lives, how it moves (or doesn’t), and where it breaks.
Now it’s time to document it. Create a brief assessment that covers:
- Current state: What tools exist? What’s working? What’s not?
- Pain points: Where does your team spend the most time wrestling with infrastructure?
- Gaps: What’s missing that would let your team ship faster?
- 90-day roadmap: What’s the smallest set of changes that unlocks the most value?
Don’t over-engineer this. Your infrastructure recommendation should be grounded in the actual problems you heard from teams, not in what’s trendy.
At the end of month one, you should have built relationships, proven value, repositioned your role, and created a roadmap. The hard part, continuously executing with excellence, comes next.
About the Author
Jeff is a Data and Analytics Consultant with nearly 20 years experience in automating insights and using data to control business processes. From a technology standpoint, he specializes in Snowflake + dbt + Tableau. From a business topic standpoint, he has experience in Public Utility, Clinical Trials, Publishing, CPG, and Manufacturing. Jeff has unique industry experience in Supply Chain Planning, Demand Planning, S&OP. Hit the chat button to start a conversation!
