Back to The Lab

What It Takes to Create a Data Visualization Culture

By Tim Weinheimer

Data visualization culture has transformed from a niche discipline to an opportunity for disruptive growth.

Digital publishing and social networking innovations demand a faster, more immersive creative experience. Digital leaders are beginning to understand how visualization is key to making that experience possible.

A new kind of data expert is driving this change. Data visualization practitioners are helping organizations redefine what it means to be “data-driven” by making critical information immediately useful to the people who need it most. In fact, the global data visualization market size is projected to reach USD 19.20 billion by 2027, exhibiting a CAGR of 10.2% in the forecast period. However, some organizations are better at utilizing highly visual data than others.

The Need for Data Visualizations

Visual content is easier to understand and processed much faster than text and numbers. James Haight of Blue Hill Research explains, “The brain operates with neural networks that allow us to predict patterns based on external stimuli at great speed. And once we learn a pattern, the brain is excellent at recognizing it again. What’s more is that one of the greatest inputs into our brain’s pattern recognizing process is, you guessed it, visual imagery. So, in this sense, data visualization tools play into our biological sweet spot. The human mind may not intuitively understand complex statistical models or things like ‘R squared’ values, but we are quite adept at picking out patterns from visual displays.

Human brains process visuals 60,000 times faster than they do text.
University of Minnesota

Data Visualization Challenges for Organizations

The vast majority of decision-makers at data-driven organizations agree that visualization is of strategic importance. Many of these organizations will undergo a pilot project, incorporate human-centered design into a key report or another deliverable, and simply stop there.

Without ongoing effort, the tremendous benefits of visualization culture never truly materialize. Leaders never quite gain the ability to spot and mitigate system-wide risks or optimize inefficient processes the way they expected.

Sustaining that effort requires more than top-down direction on data visualization initiatives. It requires a cultural shift that addresses the three major challenges of adopting a data visualization culture in an organization:

Resource Constraints. Establishing streamlined processes for data visualization can require shifting resources from other projects. It may demand expertise that would otherwise go to immediate, high-impact projects in which leaders have a key stake.
Cultural Resistance. Bridging design, communication, and data science are foreign to many people, and it takes time. Since data visualization initiatives involve a great deal of creativity, employees cannot treat them as a list of boxes to be checked. There needs to be buy-in from every level of the organization.
Reproducibility. It’s easy to fall into the trap of completing a single data visualization project without reproducing those results over a longer timeline. If decision-makers and data professionals don’t see the results of their work, they won’t feel incentivized to keep innovating in the same direction.

Wharton School of Business study found that the use of data visualizations could shorten business meetings by 24%.
Wharton School of Business

How to Put Data Visualization at the Center of Your Company Culture

The demands of data visualization represent new territory for most teams. We rely on these key steps to make data visualization a central part of our clients’ culture.

Building Trust-Based Relationships Between Teams
Data visualization is a collaborative effort that requires participation from multiple departments. Identify key members of your sales, marketing, and analytics teams and engage them on projects in ways that help build a relationship of respect and trust. These insights might even come in the form of a data culture awareness and readiness stakeholder survey to gauge the current understanding, applications and usages of data inside of the organization.

Start Small and Develop Reference Points
There’s nothing wrong with being ambitious, but multiple small projects on familiar topics will get you farther than a vast,, disruptive company-wide initiative. These small projects help everyone establish clear reference points that inform future projects, building reasonable expectations into the data visualization workflow.

Find Solutions to the Industry’s Core Pain Points
When bringing together disparate teams, it helps to keep everyone focused on common pain points they all intuitively understand. These are often big, industry-wide problems that employees and managers face every day. When data visualization addresses these issues, it immediately demonstrates its core value.

Step Into Design Thinking
The key thought process behind data visualization is human-centered design. The point is not to create and share dozens of impressive-looking charts. It’s to use data to tell a story that includes all the information decision-makers need – and none of the information they don’t.

Obtain Senior Leadership Advocacy
Having an internal data visualization champion is a significant predictor of successful cultural change. The more authoritative and influential that champion is, the better. Senior leadership advocacy is obviously an ideal case, but top-performers in any hierarchical ladder rung can also make excellent assets.

Use Internal Resistance to Build a Dialogue
Engaging data visualization champions is easy. Debating with naysayers is more challenging – and there will always be a few. The earlier you establish a dialogue with these people, the better you will be able to build a data visualization workflow that addresses their concerns instead of ignoring them.

Identify What a Great Data Visualization Culture Looks Like
Don’t give in to the temptation to start making major changes to data workflows before every stakeholder has had their say. It’s essential that everyone involved understands – and agrees on – what having a great data visualization culture means before major changes happen.

Data: The Perfect Storyteller’s Tool

Organizations with a robust data visualization culture know how to tell compelling stories. These stories, backed by conclusive real-world data, form the backbone of those organizations’ interpersonal communications.

It’s not technical knowledge that makes data science such a valuable asset but the ability to organize data in a way that resonates with audiences. Data visualization is a tool for creating true stories with unique, personalized insights. These stories pinpoint what matters most to stakeholders, using high-impact analysis to address their most pressing needs.

At White Lion Interactive, we’re making daily inroads to immerse our team of experts in using their imaginations to reimagine what data can do for our clients — starting with their culture first.

Share

More Lab Intelligence

Why Data Validation Matters to Businesses

Data validation means checking data for correctness and completeness. Data validation can be described as a series of tests and rules on the data to certify its quality and integrity.

By Jake Stevens