BI data storytelling pegged as key to driving executive action

At the 2014 TDWI Executive Summit in Boston, consultant Tony Bodoh provided tips and outlined a step-by-step process for creating effective business intelligence presentations that motivate business executives to take action.

The proper use of both qualitative and quantitative data to create a story is the key to convincing business executives to take action based on business intelligence and analytics findings, consultant Tony Bodoh said at the 2014 TDWI Executive Summit in Boston. In a session there, he outlined the data storytelling steps that he thinks analysts should take in developing a BI presentation for executive approval in order to drive operational...

and cultural changes within an organization.

Bodoh, who is president and CEO of Tony Bodoh International LLC in Nashville, Tennessee, said BI and analytics teams need to recognize that there are two distinct processes in creating a successful BI presentation: building it and then presenting it. First, data analysts must build a compelling story through what Bodoh called the discovery process, which involves proving what the data is showing, simplifying the overall theme, exploring the possibilities, finding a business-oriented story to tell, incorporating an emotional element and ending up with a plan for success -- and a hook to get people's attention. The storytelling process consists of the same basic elements, but Bodoh emphasized that they must be reordered instead of simply walking business managers and users through the analytics process. To get execs to embrace BI data, he said, the delivery of the presentation should begin with the hook and the overall theme, continue into the specific data story, delve into the emotional aspect, prove the thesis with real data and conclude by outlining the possibilities and a proposed action plan.

Many business executives still say they go with their gut in making business decisions. As a result, one tactic that Bodoh highlighted as vital is engaging their emotions through the use of qualitative, unstructured data in BI presentations. "Emotion fires a half-second before logic can kick in," he explained -- therefore, "logic follows emotion." Unstructured data, such as customer feedback, can be analyzed and organized with text mining tools and CRM systems, according to Bodoh. He added that by presenting data stories first through qualitative data and then following up with the quantitative facts, analysts are able to capitalize on the brain's natural functionality, as "we justify what we feel instead of feeling what we've reasoned to."

Capturing people's full attention is also essential to a successful presentation of BI and analytics data, Bodoh said. To help get executives fully engaged with the data, he advised using multimedia approaches to communicate information to them -- and identifying the forms of communication preferred by different individuals. Bodoh stated that most people are visually oriented, so it's a safe bet that including images in analytics presentations will heighten their interest in the data. However, if an executive is sound-oriented, it would be preferable to include an audio clip with, say, excerpts from recordings of customer feedback.

A final data storytelling tip Bodoh provided was that a BI presentation should include exactly three steps for taking action. Less than three, he said, makes the plan seem incomplete and not thoroughly thought out -- but more than three becomes overwhelming. And that isn't a good way to motivate business executives to drive meaningful business changes.

Hannah Pullen-Blasnik is an editorial assistant for SearchBusinessAnalytics. Email us at editor@searchbusinessanalytics.com and follow us on Twitter: @BizAnalyticsTT.

Next Steps

See what TDWI Boston attendees had to say about the benefits and challenges of agile BI and data warehousing

Get advice from consultant Lee Feinberg on helping business users to visualize data -- and decisions

Read tips on what to look for in evaluating and selecting data visualization software

This was first published in August 2014

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