“If you torture the data long enough, it will confess.” — Ronald Coase, Economist

Data. We know that in today’s world, it is practically another form of currency. However, despite the massive amount available, most of us still remain largely unable to interpret storytelling with data. 

Both fortunately and unfortunately, this skill has never been more critical. 

Unfortunately- because this skill is so rare. 

Fortunately- because if you know how to harness it in the right way, you will hold immense power. 

What am I talking about?

Storytelling.  

The importance of stories has been an integral component of human history since before we could even capture them in written form. Stories are how we warn future generations, how we teach, how we comfort, and how we invoke feelings in each other. 

No matter who you are or what stage you are in your career, knowing how to use data to tell a story will not only lend you empirical credibility, but also emotional credibility. 

Combining these two highly effective methods will make you unstoppable. 

Storytelling With Data Technique #1: Use Data to Identify Discrepancies

The first technique we will discuss is to use data to identify discrepancies. What does this mean?

There is a lot of data available, and usually, interpreting it is not a straightforward task. 

Statistical tests can be used to determine whether results are statistically and practically significant, but it is still up to us to decide how the significance of any given results feeds into the story we tell about our own performance, business, scientific discovery, or campaign for social good. 

To create a compelling story, highlight contrasts in the data, and explore the nuances others are afraid to touch. 

Apply It!

1. Examine Your Data for Outliers
   • Are there data points that deviate significantly from the rest?
   • Example: While analyzing customer satisfaction scores, you find a region with consistently lower ratings despite similar service levels.
2. Spot Contradictions
   • Do the trends contradict assumptions or expectations?
   • Example: Your data shows that customers aged 18-24 prefer a product feature designed for older demographics.
3. Highlight Missed Opportunities
   • Are there gaps in performance or coverage?
   • Example: A dataset on healthcare access reveals underserved rural areas despite high national averages.
4. Link Discrepancies to Key Questions
   • What story does this discrepancy tell? How can it frame a problem or opportunity?
   • Example: The gap in customer satisfaction rates can highlight a need for targeted regional initiatives.

Storytelling With Data Technique #2: Pair Data With Case Studies

Numbers are cold. 

So give them some humanity.

Storytelling is about invoking emotions in others, so make sure the statistics you use to illustrate your point are also paired with examples. 

Dive deep into the cold, hard numbers by shining a light on the individual cases that make up that statistic. 

Apply It!

1. Identify Relevant Case Studies
   • What real-world examples align with your data insights?
   • Example: When analyzing educational data, find a school that implemented a successful program improving student performance.
2. Show the Human Impact
   • Who does this data affect, and how?
   • Example: Data showing increased income inequality is paired with a story of a single parent struggling to afford childcare.
3. Bridge the Micro and Macro
   • How does the case study illustrate broader trends in the data?
   • Example: A local renewable energy project exemplifies the nationwide rise in solar adoption.
4. Focus on Narrative Flow
   • How does this case study bring the data to life?
   • Example: A graph of decreasing homelessness rates is paired with an interview of a formerly homeless individual benefiting from housing policies.

Storytelling With Data Technique #3: Leverage Comparative Analysis

Any good story depicts some sort of change or difference. 

That’s just what comparative analysis is- depicting changes through data. It’s about comparing different datasets or studies, zooming in on “before and after”. 

Why does comparative analysis matter?

Because it is the call to action. 

Regardless of your story, the call to action is its purpose. 

Whether you are convincing an employer to hire you, an investor to take a chance on your startup, or a reader to buy your book, the effectiveness of your use of data ultimately boils down to whether it leads others to act in the desired way. 

So highlight comparisons in the data and create a compelling call to action.     

Apply It!

1. Choose Comparison Variables
   • What variables make sense to compare? (e.g., time periods, demographics, regions)
   • Example: Compare sales before and after a marketing campaign to assess its impact.
2. Find Key Differences
   • What significant variations stand out in the comparison?
   • Example: In a survey of work-life balance, remote workers report higher satisfaction than in-office employees.
3. Use Ratios or Percentages
   • How can relative measures make the comparison more meaningful?
   • Example: Instead of saying 100 more people attended an event, state that attendance increased by 20%.
4. Visualize Comparisons
   • How can visuals make the comparison clearer?
   • Example: Use side-by-side bar charts to compare revenue by product category.
5. Draw Conclusions
   • What story does the comparison tell? What actions does it suggest?
   • Example: Comparing customer satisfaction across regions reveals that personalized service significantly improves ratings.

A Visual Guide To Storytelling With Data

To summarize these three techniques and start using data to tell the story you want, use the flowchart below!

Thought to Action 

1. Spark Conversations: Encourage your audience to question, discuss, and explore the data, turning your story into a collaborative learning experience.
2. Leverage Free Resources: Learn from free resources online to maximize your awareness of other disciplines, such as statistics, data analysis, and marketing. 
3. Identify Trends in Happiness: Use journaling or mood-tracking apps to correlate daily habits with emotional well-being and tell a story of what works for you.
4. Link Data to Decision-Making: Use your findings to provide actionable insights or solutions to real-world problems, bridging the gap between analysis and impact.
5. Cross-Pollinate Disciplines: Apply insights from multiple fields (like psychology, design, and communication) to craft multidimensional and engaging data stories.

Sources

No external resources were used in this post. 

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