First 90 days as a data leader: Establishing data teams as value centres

So you’ve stepped into the role as a new data leader.

It can be both exciting and daunting. On average, data leaders only last in their role for 18 months on average. Recently, I've been asked by several data leaders why that is the case. Is it because they get headhunted for more lucrative opportunities, or because they fail in doing their job?

Unfortunately, it's most commonly the latter. Most data leaders focus on democratizing data and AI, making it accessible and available. But, since 90% of data is generally not of good quality, it ends up with serving bad data the everyone. The result? Lost trust in data, in data teams, and data leaders. If this goes on, the momentum declines and challenges start building, not seldom leading to that data leader being replaced.

The first 90 days are critical for setting the tone, establishing priorities, and building momentum. A while back, I spoke to John Steinmetz, an established data leader, to share his best advice when entering a new role as VP of Data, Head of Data, or CDO, and we’ve summarized it here. Here are the key strategies to ensure your early days as a data leader pave the way for long-term success.

01. Prioritize business challenges first

Your primary focus should be on understanding and addressing the core business challenges. Data for the sake of data isn't valuable unless it drives meaningful business outcomes. Identify the most pressing problems and align your data strategy to solve them. This not only demonstrates the value of data initiatives but also helps secure buy-in from stakeholders.

02. Hire engineers early

We’ve heard this one before. 70% of B2B startups opt for an engineer as the first hire, and that’s something to learn from that regardless of the company size. One of the standout pieces of advice from the conversation was to "hire engineers first to automate and structure data accurately." Engineers are the backbone of any data team, ensuring that data processes are efficient, scalable, and reliable. Bringing in skilled engineers early on will accelerate your ability to tackle data-related tasks and optimize processes.

03. Consistency over accuracy

When it comes to data quality, there are generally six dimensions to consider. While accuracy in data is important, John emphasized that "consistency over accuracy is key in data management." Consistent data processes build trust and reliability, especially when communicating with C-Suite executives. When stakeholders see consistent results, they are more likely to have confidence in the data and the decisions based on it.

The six dimensions of data quality.

04. Leverage your network

Being a data leader can also be a lonely task. "Use your network. Reach out to people in your network," was another critical takeaway from the webinar. Building and maintaining professional relationships within the data community can provide invaluable support and insights. Whether it’s seeking advice, sharing best practices, or finding new opportunities, a strong network can significantly enhance your effectiveness as a data leader.

05. Foster collaboration and communication

Success in data leadership isn’t just about technical skills—it’s also about how well you collaborate and communicate. Engaging with your team, stakeholders, and the broader data community fosters an environment of trust and continuous improvement. Encourage open dialogue and make sure everyone understands the role of data in achieving business goals.

Key takeaways

So, to summarize the best advice to make the first 90 days a path to future success, here are the key takeaways:

• Hire engineers to ensure efficient data management and problem-solving.
• Prioritize business challenges to focus on impactful solutions.
• Maintain consistency in data management to build trust with C-Suite executives.
• Leverage your network for guidance, support, and professional growth.
• Foster collaboration and communication within the data community.