Joe Perez, a senior systems analyst, and team lead at the North Carolina department of health and human services zoomed in with the How to Get an Analytics Job podcast to talk about the actionability of data.
What brings about actionability in data?
Data becomes actionable when it can be analyzed and optimized to inform decisions. Typically, the decision makers who are on the receiving end of the data analysis have these insights communicated to them via data visualizations that tell a data story. Joe Perez kicked off the interview with a quote
“data storytelling is both an art and a science”
He went on to explain how data visualizations are the most powerful when they find this balance between art and science and how they need to blend to get the right mix.
Part of the “art” that goes into data storytelling is not only quantitative data but also the qualitative data. Quantitative and qualitative data are not mutually exclusive. The anecdotal evidence is part of the data story however, one should not rely solely on the quantified anecdotal data to derive insights. Specific anecdotal examples should be used, when possible, to personalize the story of patterns or results that you found from analyzing the data. This is like complementing a visualization with explanatory text. Anecdotal data should be shown as a complement to the concrete quantitative data. Stakeholders will understand the result better when you give anecdotal examples that provide a narrative thread along with the graphs and tables.
For example, if you’re reporting that Sales in the North Region hit 50 thousand for the quarter you don’t want to just leave it at that. Just about anyone could come up with that number and report it. You want to dig deeper with the data. What else is there to know about those sales? How does this quarter compare to the previous quarter? If it was greater or less than, why? You need to think of all the additional insight you can derive from the data. Some of the factors that can be analyzed could include events that drove the numbers, for example a pandemic, or a change in manufacturing technique or price. There is a plethora of questions that could be answered by digging deeper into the data and the more answers that you come up with the more insights that can be derived. A key part of using data to inform business decision includes having a fluid data story with visualizations and reports that connect with each other and can be easily comprehended by stakeholders. Curating this data story empowers the decision makers in an organization to directly use your analysis to drive decisions that produce value to the business or organization in question.
When you give both, the concrete quantifiable measures/numbers and the narrative thread that looks at the bigger picture, your analysis resonates more with the people hearing about your analysis. At the end of the day, the data you are analyzing will only become actionable if the people making the decisions can see and understand the insights you pulled from the data in the same light that you as the analyst see them.
I will end the post with the words of Joe Perez,
“Data is only actionable if it enables you to make a decision, answer a question, or solve a problem”
If all three of those goals are accomplished through your data analysis then you have achieved success.