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  • Article Ask eAIR
  • 12.17.19

From Data Providers to Data Storytellers

  • by Erin DeSantis, Associate Director for Student Success Analytics, California State University, Long Beach

Dear Erin: With the changing role of IR, how do we as IR professionals move from data providers to data storytellers?

Erin-DeSantisI think the thing to keep in mind is that the role of IR is not necessarily changing, but rather it’s expanding. As IR professionals, we will always be data providers to some extent, but the means by which we share information is becoming more diverse. Increasingly, IR professionals are expected to be active participants in shaping the narrative, rather than simply processing data requests.

Taking an audience on a journey with data is a skill, and it helps not only disseminate information to a group, but builds in understanding, trust, and credibility along the way. It is the art of piecing together data elements and findings in a way that weaves the context and the takeaways into one sequence. It also allows IR professionals to be creative in their approach, using a variety of text, visuals, and other elements that might help users understand the data story in innovative and unique ways. It may require one to learn new skills or technologies that will aid in this process as the traditional IR tool set might not be sufficient. As the role of IR expands into this function, IR professionals must also strengthen their tool kit to support the needs of campuses as the culture of data strengthens and expands.

I have highlighted a few elements that I think are key in the transition from data provider to data storyteller:

  1. Understanding the relevant strategic priorities, goals, or mission related to the data story you need to tell

    Understanding what is important to the audience you are working with will help you curate your data story in a way that is actionable and relevant. Understanding the landscape for which you are telling the story will help you home in what is more important to the audience and will guide you as you determine what is not relevant and or actionable and can be left out.

  2. Starting with broad context and leading the audience to the relevant nuanced data

    You want to take the audience on a journey through the relevant data you pulled together to give them the full picture of what you are trying to convey. Start with simple data and basics to set up the context and gradually lead them through more and more nuanced data as you get into the details of the story you are trying to communicate. Broad context in the beginning is important to make sure your audience understands the nuanced data waiting at the end of your data story.

  3. Realizing what data is actionable versus data that is simply interesting information leading to no action

    As you sift through the data and analyze the problem or questions, use your judgement to determine what data can be used to drive change, and what data is just good to know, but cannot drive change or spur someone into action. The idea is to focus on actionable data to help those that are making changes see exactly where they can go or what they can do. Too often, data that is requested or provided is interesting to look at and digest, but the information cannot be used to improve process or make changes.  When telling a story with data we want to make sure there is some action that can come from what we are showing in addition to the understanding of what the data is telling about a particular problem or question.

  4. Being creative with the presentation of information and including the right ratio of text and visuals to convey the story

    In telling a story with data, you need to be able to use visuals to drive home points but also use articulate and concise narratives to help the audience understand key points or any necessary context. Sometimes, even just the title can convey your key story themes with careful consideration of the words chosen. Be considerate of the visuals you choose, ensuring that they portray the data in easy to understand formats but also be creative and find ways to highlight important take home points within the visuals.

  5. Thinking beyond the immediate ask and looking for additional insights that could be relevant
    Lastly, we need use our expertise of the data and look beyond what the requester or audience has asked for, to consider things they may not have thought about. Being flexible and receptive to questions that emerge from data exploration is important.  For telling a compelling data story, sometimes it requires IR professionals to think outside the box or beyond the parameters mentioned  in order to guide users to insights they otherwise might not have discovered.

It is exciting to think about the role that IR is playing in shaping the narrative and helping institutions make progress toward student success and other important goals.

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