Getting data visualization approved: The work we often skip

We've all been there, you have this brilliant idea for a visualization, you've nailed the design, the technical execution is spot-on... and it gets rejected.?Aouch.?This happened to me one too many times until I realized that?getting our ideas approved has little to do with design skills and everything to do with the work we do before opening any design software.

1. The Why & Why Now

The most overlooked questions are often the most important ones. Before we open our design software, before we even think about those gorgeous charts, we need answers to these:

• What specific business problem are we solving?
• Why does this visualization need to exist now?
• What decisions will it influence?
• What actions should it drive?
• What's the cost of not having this visualization?
• How will success be measured?

When I worked on the Long Covid story, that clarity helped refined our story. We initially experimented with telling multiple stories, wanting to show how diverse the Long Covid experience could be. Giorgia's story would be one among many, aiming to be more representative of the broader community. But when we really dug into our 'why,' we realized our primary goal was to raise awareness about Long Covid's impact on one's life. That's when we decided to focus solely on Giorgia's data. It created a more powerful, focused narrative that served our purpose better than trying to tell multiple stories.

2. The Who & What

Here's the thing about audience - everyone says "know your audience," but few actually do the work to understand them. Your visualization isn't for "everyone". Get specific about:

• Who's the primary audience? (Job titles, roles, departments, habits, beliefs...)
• What's their data literacy level (and relationship to the information you're about to share?)
• How will they actually use this visualization?
• What's the key message they need to understand?
• What context do they already have?
• What related data have they seen before?
• Where and how will they view this visualization?

Let me share another story. During the American Opportunity Index refresh, the team kept requesting more features, more filters, and more complexity. At first, I couldn't understand why - until after several sessions with them, I realized they were trying to answer the needs of three distinct audience groups. So, rather than build one complex interface, we created three focused pages:

• One for quick, high-level insights: the Top 100 dedicated to the press and newsletter.
• One for specific comparative analysis: a page to allow the relevant comparison of each company by sector
• One for detailed data exploration: a complete alphabetical list with all data points to allow any user to quickly find their own company and drill down into the submetrics

It turned what could have been an overwhelming interface into three intuitive, purpose-built experiences.

3. The Brand & Cultural Context

Don't get me wrong - style guides are important. But when it comes to data visualization, there's often a disconnect. Style guides rarely address how to handle charts and data, and despite all the best practices we know about data visualization, the reality is that people often judge charts through their personal and organizational preferences. This is why we need to understand how the organization, and the team, relates to visuals:

• What's their actual visual identity in practice? Does the organization embrace all colors from their palettes or prioritize some before others?
• What's their comfort level with different chart types?
• How does the client team typically make design decisions?
• What previous designs have they loved or hated (from their internal work and from other inspiration sources)?
• What's their comfort level with pushing the boundaries of creativity?
• Who are the key stakeholders in the approval process?

Let me share something a bit wild: I once designed an entire data-based app based on a client's office hallway. The client couldn't articulate what he wanted visually (and actively disliked his own brand guidelines). I asked him to share ANYTHING he liked visually. So he shared a photo of his office: a brutalist concrete hall with large pillars, movie posters, and red comfy chairs. That became our inspiration - the final app design embraced brutalist principles with bold reds, and it was a hit.

TLDR: When clients become prescriptive about features ("I want a button here" or "Use this type of chart"), they're not trying to design. They're trying to solve a problem they can't articulate. Our job isn't to follow their requests. It's to understand the real problem they're actually trying to solve.

Till next time,

Gabby

?? Quick Reminder: If you're here for the data visualization wisdom and impact-driven strategies rather than career insights and behind-the-scenes of an information designer's life, head to How to Inform the World.