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Story-Based Analytics Produce Insights that Persuade Decision Makers

story-based data analytics, data-driven story tellingMost high-level business executives obsess over data. Public relations and marketing professionals have recently followed their lead. Data now swamps PR and marketing teams. Sometimes they seek data just for the sake of collecting numbers that impress their c-level executives. That’s not optimal by any means and often isn’t persuasive

While data can help improve performance, over-reliance on data is a mistake. Data without context or meaning will fall flat or lead businesses down the wrong path.

“All the key performance indicators (KPIs) in the world — without context and meaning — won’t help your team make sense of the successes and challenges you’re facing when it comes to your business’s greater transformational change,” argues Justin Grossman, CEO of meltmedia, a design & development agency, in Forbes.

Key performance indicators (KPIs) can measure progress toward goals, but they lack the context — or the “why” — behind results, Grossman says. They often don’t reveal the underlying story behind the data.

Story-based analytics offer a better solution.

Create paragraphs in story form to describe what you expect to happen, he advises. For instance, cite the increase in website visits needed to meet goals for sales-qualified leads.

Story-Based Analytics Requirements

A story-based analytics approach, Grossman says, requires:

  • Using metrics to learn, not just measure.
  • Adapting to data in real time to gain insights.
  • Understanding that metrics may shift as you progress.
  • Embracing all data, even if it reveals poor results.
  • Knowing your stakeholders and their perspective well.
  • Ruthlessly pruning data to ensure accuracy and relevance.

Good Stories for Powerful Persuasion

Stories are user-friendly, more persuasive and more conducive to decision-making, say experts writing in the Harvard Business Review. Stories can lead to more rigorous data analysis, stated Judy Bayer, director strategic analytics for Teradata International, and Marie Taillard, a professor of marketing and director of the Creativity Marketing Centre at ESCP Europe Business School in London, UK. Stories help test theories.

“In a world that’s flooded with data it becomes harder to use the data; there’s too much of it to make sense of unless you come to the data with an insight or hypothesis to test,” the pair write.

Create a narrative, or storyline, with characters and a plot. The storyline enables an authentic human element to surface that would be more difficult to extract from the data alone.

In any report to a boss, offer your insights on the story behind the numbers. What is the impact on business results? How does the data impact corporate goals? How does the data affect corporate reputation?

Florence Nightingale’s Story-Based Analytics

When Florence Nightingale studied mortality rates during the Crimean Wa, she found that most soldiers died not in combat but from preventable diseases caused by poor sanitary conditions in hospitals. She created a diagram to convince British Parliament and Queen Victoria to invest in better sanitary conditions, ultimately saving he lives of countless soldiers. In other words, she employed data storytelling – numbers combined with plot and hero.

“Data storytelling was in important in Nightingale’s time — and it matters even more in today’s digital data-abundant world,” states Christy Pettey, senior director, public relations, at Gartner,

Pettey cites three key elements of story-driven analytics:

Visualizations. Visualizations like charts and graphs illustrate how data changes over time. No one visualization works for all situations. Select visualizations based on the kind of data being presented and the audience viewing it.

Narrative. A good narrative includes a beginning, middle and end. But the end should be a set of options or questions that trigger critical thinking.

Context. Context around the data provides value and motivates people listen and engage. Like visualizations, the context should be chosen based on the audience.

Bottom Line: Data analysis without context or meaning often fails to persuade or product meaningful insights. Numbers alone may add up to nothing. Combing data with a story can reveal the “why” behind the figures, produce meaningful results, and improve decisions.