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Leading Data Conversations: Tips to Talk with the Entire Team

Here are some tips that I've found to help lead these data-driven conversations:


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Rachel S

3 years ago | 2 min read

Recently, a colleague and I were discussing data-driven culture while meeting over coffee. She found some somewhat negative conclusions from a recent data analysis and was struggling with the proper way, if at all, to communicate those findings.

She knew that the analysis, although important, was likely to face resistance and that there was potential for her to alienate colleagues by pointing out business failures and omissions that likely caused some of the issues.

My advice to her: "when we avoid difficult conversations, we trade short term discomfort for long term dysfunction." That being said, difficult conversations are exactly that: difficult.

These conversations can become even more clouded when an understanding of the analysis, data, and methods are not fully understood by all participants in the conversation.

For leaders to foster a data-driven culture that is successful, we must not only encourage participation from all team members, but we must also lead the understanding of the advantages and pit-falls of data.

Here are some tips that I've found to help lead these data-driven conversations:

Start with the Big Picture: Discuss the ways that the organization can leverage data to help tell the story of their team goals and why these goals are important. For example, are there overarching trends or patterns? What are the various sources of data? What are the implications upstream and downstream of each source?

7-Degrees of Questions: Ask questions rather than make assessments or hypotheses. Identify the owner of each data piece and guide the team in question-based exploration. What does the data that we have tell us? What data do we not have? What defines success and how do we measure that?

Create a Forum for Conversation: one of the biggest oversights in data conversations is not including all stakeholders. Encourage all team members along the entire pipeline to participate in the dialogue. Creating formal opportunities for feedback is an excellent way to encourage people to feel comfortable exploring the data and asking questions. Some ways to do this: regular open office hours, Q&A sessions, lunch-and-learn, and hands-on exploration sessions.

Review the Data Pipeline: ensure that all aspects of the data are reviewed within a holistic picture. Data is not created or consumed in a vacuum. How does the data change over time? Are there trends or cycles that affect data patterns or refresh? How does that data from one source or group compare to data from another source? Does this comparison highlight any additional questions or findings?

Make It Real: by encouraging members of the organization to interact with the data, we can create a more physical and real environment. This often fosters innovation when people can see, touch, and play with the data. This makes it real and physical, not some "geeky" conversation. Give people access to data sandboxes, provide training on tools, or create posters and infographics to place around the workplace (one of my favorite methods).

Create Actionable Insights: The final phase of a data-driven conversation is to determine the actionable insights from this exercise. What are the specific actions to be taken? Who will be responsible for each action? How will success be measured and how often will the team review these measures? How will goals be adjusted based on these outcomes? Be sure to plan a specific schedule for the team to review these priorities so that data becomes an on-going conversation.

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Rachel S


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