Nearly all organizations do some kind of analysis or reporting that leverages data. As an outcome, countless decks are produced containing a myriad of charts and graphs, showcasing diverse metrics and results – but only some of them provide useful and actionable analysis that clearly and convincingly articulate “the story” behind those data points such that a broad audience can understand what they mean and act upon their valuable insights.
When it comes to crafting analytic findings in a way that contextualizes results for data users, follow these four steps to bring your reports to life through storytelling.
Craft a descriptive analysis
To start, recognize that data doesn’t always make sense by itself. Consider starting with data visualizations that show results relative to other data points. This will help create a baseline for comparison and create the framework for deeper analysis.
For example, the importance of a handful of critical markets becomes more evident in the visualization below when set against the backdrop of other destinations allowing us to more clearly articulate the story around the related business opportunity.
From there, use other techniques like decision-tree analysis to make correlations that help in projecting expected outcomes and identifying meaningful inflection points or data variables. (If you don’t have an analyst on hand, look through this simplified how-to for decision-tree analysis.)
Layer on business challenges and opportunities
Part of the storytelling process should connect data back to the business goals of an organization. The data should be reviewed with business objectives and opportunities in mind to help identify both successes and potential problems revealed within the data.
For example, your company may have the overall goal of increasing ancillary redemptions by 25 percent by year-end, with the secondary goal of increasing Millennial redemption by 50 percent. If your redemptions are exceeding your original goal, but the data shows Millennial redemption is down, this should be addressed in the narrative of your analysis findings. Making these connections will make your findings more concrete and thus actionable.
Look beyond the painting and focus on the brush strokes
You always want to look at the most granular data available, going beyond metrics that can sometimes lead you astray like metric averages. When working with big, broad numbers, you could be missing out on additional storylines within your data associated with more refined statistics like medians, skew or distribution.
Further, creative data segmentation will also allow you to identify trends within your customer base that aren’t readily apparent on the surface. These insights will provide organizational leaders with the rationale they require to justify further investment and achieve organizational buy-in on how to best address key business objectives and opportunities.
Conclude with an action plan
No matter how you present it, make sure your findings result in a narrative that end in actionable recommendations. The end of the story should always lead to a place of applied learning and action. This provides context for what the data represents, what it means for your organization and how it can be used to make more informed decisions moving forward.
While metrics are the foundation for your analysis, translating them to actionable insight through compelling storytelling is just as important. For instance, if you’re looking to reduce the number of customer calls to a call center, the number and duration of those calls should only be Chapter One of the full story. Challenge yourself to dig down and capture the whole story, in this case, by identifying the nature of the calls, the profile of those who call, and what those calls mean to the business and customer satisfaction.
Combing through the data at this level will allow you to create a story arc that engages broad internal audiences and takes them on a journey beyond the basic numbers.
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