How to supercharge the impact of your data insights

Here's a story that plays out in boardrooms across North America every day: A VP opens her quarterly dashboard, stares at a wall of charts and filters, and closes it within 30 seconds. She's not lazy. She's human… and humans don't make decisions from spreadsheets masquerading as insights.

When RBC's design team collaborated with data scientists to create their NOMI personalized financial insights system, something remarkable happened. RBC became the first bank in Canada to offer clients personalized digital financial insights, transforming how millions of users interact with their financial data. Digital engagement soared. The difference wasn't better data, but better design that made complex financial information instantly understandable.

Meanwhile, at Shopify, merchants struggled with data-rich dashboards that should have empowered their businesses but often overwhelmed them instead. The company recognized that keeping apps consistent as features scaled was tough, so they developed the Polaris design system to ensure consistency and usability across all merchant-facing tools.

The pre-built User Interface components significantly reduced development time, letting developers focus on enhancing functionality without reinventing basic UI elements, while merchants gained more intuitive interfaces for managing their businesses.

This pattern repeats everywhere: healthcare providers wrestle with electric medical record (EMR) interfaces that contain all the right information but present it in ways that slow down patient care. Financial advisors have access to sophisticated analytics but need intuitive tools to communicate insights to clients effectively.

The $73 Billion Problem

American companies spend roughly $73 billion annually on business intelligence tools. Yet study after study shows that most executives still rely on gut instinct over data dashboards for major decisions. Why? Because having data and being able to act on it are two completely different things.

The real tragedy isn't that these tools are expensive, but that they're invisible. They sit unused in browser bookmarks, gathering digital dust while the decisions they were meant to inform get made in hallway conversations and hurried email chains.

What We Get Wrong About Data

Here's the uncomfortable truth: your data team built and uses a Ferrari, but many users only need a pickup truck. Sales leads toggle between 17 chart types to answer one revenue question. They want to know if they should be worried about something, and if so, what to do about it.

The human brain processes images 60,000 times faster than text. Evolution wired us to spot patterns, not parse tables. 

Picture this: A program manager opens the quarterly dashboard to find six filter tabs, three drop-downs, and a wall of charts. None answer her core question: which service is lagging this month—and why? She clicks away. The PDF summary from last quarter will have to do.

Or consider emergency response: A public safety dashboard displays regional risk data, but first responders, unable to quickly interpret the multi-layered visualizations, turn to their phone chains and email alerts instead.

These aren't edge cases—they're the norm. We've optimized for analytical completeness while forgetting that humans are the ones who need to act on the information.

The Missing Discipline

Nearly every organization is trying to figure out how to manage their data better—make it more usable, shareable, digestible. They're building schemas and interactive dashboards. We’d also advocate for a dedicated effort on doing service design, product design, or UX design for data tools.

This isn't about making things pretty. It's about understanding how decisions actually get made in your organization. Who needs what information, when, and in what format? What happens before someone opens that dashboard? What needs to happen after?

Designers ask fundamentally different questions than data scientists:

- Who will use this tool, and what are they trying to achieve?

- What constraints exist in their environment?

- Where are the current friction points?

- How does this build trust?

When organizations apply these principles to their data tools, they see immediate improvements. Simple changes (like restructuring information hierarchy, clarifying navigation, or improving visual contrast) can dramatically increase tool adoption and effectiveness.

The Science of Better Decisions

The stakes become clearer when we understand information processing. When a Deputy Minister needs to understand budget variances during a crisis, or when a financial advisor needs to assess portfolio performance, the difference between instant visual comprehension and laborious text parsing can determine response effectiveness.

Organizations that recognize this invest in service design approaches, embedding UX researchers and designers into product teams to map user journeys and redesign interfaces. The consistent result: faster onboarding, improved satisfaction scores, and increased user trust.

Experiences Over Tools

The critical shift is recognizing that data tools aren't just technical systems—they're service experiences. Every successful transformation treats dashboards not as endpoints but as moments of service within broader user journeys.

Think about it: your dashboard isn't competing with other analytics tools. It's competing with every other way people get information: Slack notifications, email updates, hallway conversations. If it's not faster and clearer than those alternatives, it loses.

Government agencies in particular face unique challenges: accuracy requirements, accessibility standards, diverse audiences with varying technical expertise. Unlike private companies that can iterate rapidly, government data presentations must be trustworthy, compliant, and serve everyone from frontline workers to senior executives.

Private sector organizations have similar challenges with different constraints—they need tools that work for analysts, managers, and customers simultaneously while maintaining competitive advantage and regulatory compliance.

What Actually Works

The organizations getting this right follow a few key principles:

Start with actual workflows, not ideal ones. That busy executive reviewing performance metrics needs to absorb key insights in under 60 seconds while multitasking between meetings. 

Design for these real-world constraints, not conference room demos. Layer information for different users. Government data serves frontline workers, executives, and public stakeholders. 

Private sector tools must work for analysts, managers, and customers. This requires different complexity levels based on user needs and technical expertise—not different tools.

Make trust visible. Users need to understand not just what the data shows, but how reliable it is. Clear methodology, appropriate uncertainty indicators, and visual choices that enhance rather than distract from information build credibility.

Test with real humans in real contexts. The most elegant dashboard is worthless if it doesn't work in the actual environment where decisions are made. Test early, test often, and iterate based on genuine user feedback, not what the data team thinks users need.

Build accessibility from the start. This isn't just compliance—it's ensuring critical information reaches everyone who needs it. Accessible design benefits all users, not just those with specific needs.

The ROI You Can't Ignore

Here's the uncomfortable truth: your expensive analytics platform may be hemorrhaging money.

According to research from mobile UX company Maze (among others), every dollar invested in user research and design, organizations save up to $100 in support costs, rework, and lost productivity, or more specifically:  That's not marketing fluff… that's math. Canada Post's redesign of parcel services resulted in a 28-point increase in customer satisfaction. Export Development Canada attributes part of its $1 billion annual net income to service-oriented digital experiences.

But the real ROI isn't in the spreadsheet. It's in the executive who can spot budget variances instantly instead of hunting through reports. The financial advisor who closes deals faster because risk profiles are crystal clear. The program manager who catches problems before they become crises. 

When people can actually use your data tools, they make better decisions. And better decisions compound over time in ways that are hard to measure but impossible to ignore.

The question isn't whether your organization can afford to invest in design. It's whether you can afford to keep paying for tools that are not reaching their full potential.

The Path Forward

The organizations leading this transformation share a recognition: the future depends not just on collecting better data, but on presenting it in ways that drive better decisions. 

The solution isn't choosing between data and design—it's recognizing they're inseparable. Data without design is just information. Design without data is just decoration. The magic happens when they work together.

Your data team has built incredible tools. Now it's time to make them human.

Ready to build the infrastructure that empowers your stakeholders with powerful decision-making tools that they’ll actually use? Contact us at hello@button.is to start the conversation about taking these vital first steps.

Button helps government organizations make smarter digital decisions that improve services, reduce costs, and better serve citizens. We're available through multiple qualified supplier lists and procurement vehicles.