(and what to action in your data and analytics delivery to make it ‘simpler, faster, easier’ for your customers)
The dashboard was live. It had everything: accurate data, built-in filters, integrated definitions. The team had followed the brief, hit the deadline and declared success. But weeks later, almost no one was using it. Stakeholders across the organisation were still making ad-hoc requests asking for manual reports.
If this sounds familiar, you’re not alone. It’s the defining challenge of enterprise analytics: on-point execution that creates limited user impact.
In complex enterprises where legacy systems, matrixed structures and disconnected priorities are common, it’s easy to focus on delivering data to meet the functional requirements and miss delivering the user experience that makes all the difference.
Because data only creates value when it’s actually consumed, understood and acted upon. Technically correct outputs that are hard to navigate, slow to arrive or context-blind are, in effect, invisible. More critically for executives, they represent wasted investment and missed competitive advantage.
Consider this: organisations that prioritise data experience see dramatically higher adoption rates and faster decision cycles. Yet most analytics budgets still allocate the majority of spend to infrastructure and tooling whilst underinvesting in the consumption experience, the very layer where business value materialises. How often is a user experience designer actually embedded in a data or analytics team?
Here are six experience-first principles that turn good data work into great business outcomes, and what to action to make it happen.
1. Insight Isn’t Impact Until It’s Used
Insight only matters when someone uses it to make a decision, change a course or take action. But many data and analytics teams still equate ‘done’ with ‘delivered’.
A dashboard that’s opened a few times but never embedded in day-to-day. An insights report emailed but never leading to operationalised improvements. These aren’t just wasted effort, they’re lost opportunity. For leaders, they represent failed ROI on analytics investments and decisions being made with incomplete information while better insights sit unused.
The cost extends beyond the obvious: teams continue manual workarounds, decisions are delayed, competitive advantage erodes and executives lose confidence in data and analytics investments. Unadopted analytics leaves your organisation visually impaired, despite paying for the 20/20 vision premium.
Opportunity: ‘Design for Actionability’ Track usage, not just delivery. Measure the gap between what’s produced and what’s adopted ongoing. Build data experiences around the user’s moment of need, not the team’s preferred method of output. The organisations winning with analytics are those that obsess over consumption, not just creation.
2. The Consumption Layer Is Where Value Lives
Pipelines, models and platforms matter – but to the business, the only thing that’s real is what they can see and use.
Poor layout, inconsistent design, overwhelming filters or unclear metrics can all derail good work at the final mile. This is where most organisations lose the battle for data-driven culture – not in the back-end architecture, but in the front-end experience.
The irony is stark: organisations will spend on perfecting data pipelines, then lose users with a poorly thought-out and designed interface.
Opportunity: ‘Elevate the Last Mile’ Treat reports, dashboards and alerts like front-end products. Apply UX, visual design and accessibility principles, as you would when delivering for an external customer in a competitive environment. If the user’s first impression is ‘too hard’, they’ll find a workaround or disengage entirely.
3. Human-Centred Data Design
Dashboards and tools are often built for the user, but not with them. The result? Technically sound but practically frustrating to use.
Enterprise analytics teams must borrow from product teams: build empathy, observe real usage, co-create. Because unless the design is intuitive and relevant, it will be ignored, regardless of how right it is.
The most successful transformations happen when data leaders shift from ‘building what’s asked for’ to ‘solving for what’s actually needed’. This requires deep understanding of not just the data and analytics request itself, but also of the business context driving it, and the wider competitive market environment surrounding it.
Opportunity: ‘Design With, Not For’ Embed users in design from day one. Use journey maps, wireframes and lightweight usability testing. Validate not just the insight, but the flow, the format and the experience of using it. Make your business stakeholders co-creators, not just consumers – their investment in the process drives adoption.
4. Make It Simpler, Faster, Easier
If it takes a user three emails, five clicks and a data dictionary to find what they need, the experience is broken.
And if the insight arrives days after the decision, it’s not just late it’s irrelevant. Timeliness is not a bonus, it’s a baseline. For a business, the organisation with faster insight-to-action cycles wins.
Think of it this way: every friction point in your data experience is a competitive disadvantage. While you’re troubleshooting filters, your rivals with smoother analytics workflows are making better decisions, faster.
Opportunity: ‘Reduce Friction Ruthlessly’ Map the real path from question to answer. Remove unnecessary steps. Pre-filter, pre-calculate, pre-load. Automate where it adds value. Match the cadence of your insight delivery to the cadence of business decision-making. Every friction point is a competitive disadvantage.
5. 80% Right Isn’t Enough
Many data requests are met with a technically correct answer that misses the real point. Getting the brief right is no longer enough. The gap between ‘asked’ and ‘actually needed’ is often where the real value lives.
Great analytics goes beyond the task, it understands the business context, anticipates the next question and adds unexpected value. This is where analytics teams transition from cost centres to strategic assets, by delivering insights that leaders didn’t even know they needed.
For executives, this principle is crucial: teams that only deliver what’s asked for will never drive the insights that transform organisations. The breakthrough moments come from analytics professionals who think like business partners, not data processors.
Opportunity: ‘Understand the Why, Not Just the What’ Coach your analysts to think like strategic partners, not just data responders. Encourage curiosity, challenge the request, dig into the business intent and aim to surprise with relevance. Create space for analysts to understand business strategy, not just execute data tasks.
6. Design for Surprise and Delight
The best analytics experiences don’t just deliver the expected, they deliver something better. A perspective the user hadn’t considered. A comparison they didn’t ask for. A visual that makes the complex clear.
These moments build trust, credibility and loyalty. And they’re rarely the result of luck, they’re designed in. When stakeholders are genuinely excited to open your analytics, you’ve achieved something powerful: data becomes embedded in culture, not imposed upon it.
Opportunity: ‘Go Beyond the Ask’ Deliberately design for delight. Bake in layers of context, benchmarking, callouts and commentary. Use design not just to present the data, but to elevate the meaning and impact of it. Make insights memorable, shareable and actionable.
Conclusion: Here’s What to Action
In a world where experience defines product success, why wouldn’t the same apply to data and analytics?
In large, complex enterprises, we’ve invested heavily in collecting and managing data. But the real differentiator now lies in how that data is experienced. The shift from data delivery to data experience isn’t just operational, it’s strategic.
These principles are not just UX niceties, they are performance enablers. When the consumption experience is fast, clear and meaningful, adoption grows. When adoption grows, data becomes embedded in decision-making. And when data is truly embedded, organisational transformation and agility accelerates.
Here is what to focus on: treat Data & Analytics UX as the value amplifier for business outcomes. Invest in the final layer. Remove friction. Deliver delight. Shift your team’s mindset from building tools to enabling decisions. Challenge the assumption that ‘users just need the data’ to they need the right data, presented right, at the right moment. Do this deeply for every request or initiative.
The common resistance of ‘we don’t have budget for UX’ or ‘it takes too long if we spend time on UX’ misses the point. Experience isn’t cosmetic, it’s the difference between analytics that are embraced and analytics that are unused.
In the end, your data strategy isn’t measured by what you collect; it’s measured by what gets used. Perfect data consumed poorly loses to good data experienced brilliantly every time.
Simon is a senior leader in AI, Data and Digital, specialising in Strategy, Transformation and Product. He builds enterprise capabilities that drive measurable business value and deliver exceptional customer experiences.
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