Seven Ways to Scale a Data-Driven Culture

Without the right culture, even the best technology tools won’t get you where you want to go, say the co-founders of Data Culture.
November 23, 2020

Data isn’t just a tech solution. For Gabi Steele and Leah Weiss, founders of the consultancy Data Culture, it’s also a “people” solution. Even within companies that enthusiastically embrace a cloud-based modern data stack, a substantial gap often exists between the business and data sides of the organization. This gap is actually an opportunity to build a data-driven culture across the company. Combining a culture of data with a cutting-edge modern data stack allows the company and team members to reach amazing new heights of success.

“Data isn’t just a .csv that you export, or a report, or an analysis,” said Weiss. “It’s a way of adding rigor to your thinking in terms of hypotheses you want to test. It’s a prioritization framework. It has to be integrated with the business to be successful.”

At the Fivetran Modern Data Stack Conference 2020, the duo presented their best advice for fostering transparency and creating more meaningful connections across both sides of a company to drive better outcomes.

How to Build a Data-Driven Culture

1. Invest in building the domain expertise of your data people. “You will get amazing results from your data people if you work to bring them into the business,” said Weiss. Your data team is probably used to the “get me this” request—a dashboard, a report, etc. But if they fully understand your thought process and the “why” behind your requests, they can deliver even more valuable insights to decision makers.

2. Share business challenges with them. Tell them why you want to build things, how you want to act on those insights and why the data you’re asking for will move the company forward. We say this all the time, but if everyone in your company could write perfect SQL, it wouldn’t necessarily save the company money,” said Steele. “Having more tech capabilities is great, but being able to address business challenges is what changes the way your organization runs.”

3. Brainstorm solutions with them. Speak in the language of well-defined problems, which can kickstart brainstorming that ultimately leads to better solutions. “Data people, I think, are by nature incredibly creative people, but they’re not always asked to use that part of their brains,” said Weiss. Don’t neglect the ideas they could bring to the table.

How Data Analysts Can Support a Data-Driven Culture

1. Resist the tension between business analysts and data analysts. You might recoil when your business analyst colleagues declare their love for Excel. Deep breaths. It’s okay. Keep trying to form friendships and build bridges, because that’s how you will come to understand their needs and then deliver tools and insights they’ll use.

2. Invest in ambassadors and build a data community. There are scrappy people within your business who understand the power of data and how it can help them do their jobs better. Invest in those people, said Weiss and Steele, who started up a data community when they worked together at WeWork. “Turn that annoying person who’s Slacking you all the time into the person who sits in a room with you and learns SQL,” Steele said.

3. Embrace inclusivity. While it’s true that you’re solving some complicated and difficult technical challenges, that doesn’t mean you shouldn’t bring new voices into the conversation. Don’t let the data side feel like an “exclusive club,” they advised. Bring people in, and don’t make things seem more technical than they need to be when you’re sharing ideas with colleagues from other disciplines.

4. Focus on diversity. Hire people with different backgrounds who enjoy solving business problems as much as they love solving technical problems. Case in point: Neither Steele nor Weiss started their careers in data or majored in STEM fields — so just imagine how increasing the diversity of thought on your team can bring about valuable new perspectives. “What we’ve seen time and time again is that when you introduce voices from people who’ve had different experiences into the data conversation, that’s the best reward here,” said Steele.

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