Creating a Data Visualization Culture

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Creating a Data Visualization Culture

As insights from cloud BI impact your business, more and more people will want to use your visualization tools. Why? Because pictures speak a thousand words and convey a clear message. People respond to visuals that clearly tell a story, much more quickly and passionately than they do to lengthy descriptions or tables full of data that they have to interpret.

“A well-designed, meaningful visualization leverages our intrinsic hard wiring to understand complex information visually.”

Lindy Ryan
Research Director for Radiant Advisors

While some of your co-workers may consume and review raw data readily via spreadsheets or mathematical models, most don’t. Many may operate in a world where tables are as in depth as they get with numbers. By introducing them to data visualization, suddenly everyone can easily cross each others’ language barriers and instantly communicate, visually--via bar charts, scatter plots, heat maps and other dataviz mainstays.

By creating a data visualization culture, you’ll ensure everybody’s using and sharing data visualization best practices that work for your organization. That way, everyone’s information sharing throughout the organization is more likely to be focused, strategic and effective.

Can you really get everyone thinking visually?

By systematically creating a culture that utilizes and shares BI visualization wins with each other, you can help everyone at your organization simultaneously learn a visual language and know what works best. One way to build that culture is through a data visualization competency center. This center educates users on visual design principles, provides best practices and proven standards, and fosters a culture of communication, collaboration and collective learning that enables a review network for newly created data visualizations.

“An environment that fosters sharing, storytelling, and networking of visual assets across the organization replaces the red tape of policies with a culture of education and collaboration.”

Lindy Ryan
Research Director for Radiant Advisors

Why would you want to standardize the way analytics are shared?

“Poorly designed data representations can distort the message of data, fail to guide the audience toward meaningful conclusions, or lose the attention of the stakeholder altogether,” says Ryan. “This creates risk.” If you wish to reduce the risk that incorrect or inadequate visual communication could cause—like, for instance your company taking the wrong action (or missing a well-supported, but poorly-documented opportunity) then listen up!

Create a culture that helps you use dataviz more effectively.

Say you’ve discovered some fantastic business insight. You want to share it with everyone and keep their attention, not inadvertently distort the truth. No one wants to risk sending your business “in the wrong direction.” As humans, we want people to understand our message. We want them to connect with us and respond to our message. And we also want to shine--we want to take credit when the company takes the right action based on our insight, not get blamed for misleading the troops.

Want immediate and actionable and intriguing insights?

Of course you do. Intuitive self-service analytics tools enable business-oriented people to independently create and share their own personal analytic discoveries. When that creation and sharing is “done right,” everyone gets what they want!

“Organizations that have a genuine passion for data are more likely to cultivate a culture of collaboration to uncover faster data correlations and reveal new insights from their data.”

Lindy Ryan
Research Director for Radiant Advisors

You shouldn’t have to be a data scientist to extract insights from your data. “Guided visual discovery” helps non-technical users understand analysis step-by-step and choose the type of dataviz that best tells their story at a glance. By leveraging information from millions of interactions to offer you best practices, GoodData suggests better ways for you to explore data and help others see what you mean.

Grow a culture that’s collaborative and shares collective wisdom.

Collaborative learning creates competitive advantage. “Data visualizations highlight the connections between data. However, used in isolation these are no more useful than are data silos,” says Lindy Ryan. That’s why she stresses the need to collaborate with subject matter experts and engage in group critiques before publishing new – or revised – visuals.

As your dataviz culture matures, so do your decision-makers.

Sending out metric-driven notifications and scheduled email reports get your employees consistently interacting with visual stories. Interpreting data visualizations becomes more intuitive. People get excited by the insight unveiled, and they start creating, reading and responding to data visualizations more effectively. The more systematically guided analytics is ingrained in business processes, the more informed and agile decisions are made... and that’s good for every organization.

Radiant advisors data visualization competency center

Written by GoodData Author  | 

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