Last week we posted about the shift to data-driven design. In particular, we wrote about the challenges of knowing when to rely on the information gathered in a data-influenced approach, and when to trust our own intuition to guide us to the right design choices.
Data-driven design can—and frequently should—be part of a holistic, design-thinking approach. It can provide concrete, grounded information to support or challenge our intuition and ultimately help lead us to a better end result.
As Cara Tsang, User Researcher (and staunch advocate of harnessing the power of data) at Myplanet points out, the key advantage of data-driven design is in the knowing.
“It’s design that’s grounded in evidence,” she says. “Whether that’s the initial user research we do to learn about the user’s goals, attitudes, and behaviours, or analytics that can help shed light on key factors. Data-driven design gives us information to confirm and support our choices.”
But if we’re going to embrace it, we need to know how to do so effectively—and how to get stakeholders to support our vision of a data-driven design approach that blends the best of gut feelings with the best of graphs.
Step 1: Provide Context
First and foremost, if we’re going to get stakeholders on board for data-driven design, we need to be clear about what data-driven design actually means. And part of that is clarifying what constitutes “data” in the first place.
“I think people who aren’t heavily involved with design research often hear ‘data’ and automatically think ‘numbers’. But it’s really more like evidence-based design, because while numbers can tell us WHAT people are doing, it can’t tell us WHY they’re doing it,” says Cara.
Data-driven design gives us a wealth of “fact”-based information off of which to base design decisions, but even in data there is no such thing as a pure truth.
Pamela Pavliscak, founder of Change Sciences, writes in a piece for UX Matters that, “Just as we wouldn’t look at an archaeological dig and expect to create a complete picture of life in Ancient Rome, we can’t look at any dataset and create a complete picture of the user experience. Data represents an approximation of the user experience, not a matter-of-fact truth.”
It is easy, especially at the enterprise level when we’re dealing with big datasets, to assume there is an absolute truth to the metrics in front of us. But that isn’t the case, which makes it important—when bringing stakeholders into a new design process—that we be crystal clear in what can and can’t be accomplished with data.
“That old joke goes: ‘There are three kinds of lies: lies, damned lies, and statistics’, after all,” notes Cara wryly.
And in a piece for UX Magazine, Pavliscak states that, “Even if data is big, it does not mean it is objective. Bias is inherent in any dataset. Datasets are created by humans, who interpret them and assign meaning, even if a machine runs the numbers.”
Having an open and honest discussion up front about the merits and pitfalls of turning to data in design is the best way to ensure that we set our work and our partnerships up for success.
Step 2: Highlight Enterprise-Specific Advantages
Even though data has limitations, the wealth of available data at the enterprise scale makes it an especially prudent environment for effective use of a data-driven design process.
“Data-driven design is massively important in the enterprise space,” says Cara.
Once we’ve provided context and broadly explained the parameters of what it means to use data in our design process, the next step is to point out the many ways data can improve our work.
“Enterprise systems are so complex and have so many touch points with other processes,” Cara notes.
When design work is less likely to be measured by metrics like engagement or conversion rates—as is the case with an employee tool, for example, which has to be used for work—it can be hard for stakeholders to understand why the data matters. As long as the tool gets the job done, what difference does it make? The reality is, it can make a lot of difference.
“No matter how much a person loves their job, people generally aren’t passionate about using the tool required to do their job,” says Cara. “Our goals should be to decrease the time it takes to complete tasks, increase the accuracy of work, and even to eliminate or automate certain simple but tedious tasks altogether, so that employees can spend their time on more valuable things.” And data can help us to understand if we’ve done these things.
“Designers and Product Managers need to understand how an enterprise product fits into an employee’s workflow, and effective enterprise design (like all effective design) must put the employee's perspective (i.e., the user’s perspective) at the forefront.”
By measuring the time it takes to train a new employee on a tool or the number of calls to internal support teams, we can begin to validate the work we’ve done on making that tool more efficient, easy to use, and effective as a means of getting work done.
“And hey, if you can actually build in elements that DO make an employee love using a tool, well that is design magic right there,” she adds.
And Jon MacDonald, founder and President of The Good, takes a similar line of thinking in his piece for InVision. He says that, “Many organizations struggle to balance their users’ needs with their business objectives. The most effective, high-converting sites serve the user’s needs first.”
He may have been talking about consumer sites, but regardless of whether we’re building a consumer app or an enterprise tool, prioritizing user needs leads to better, more enjoyable experiences and products. And this is where data-driven design can actually be an effective way to sell our ideas and vision to our enterprise stakeholders.
“Grounding design in data gives us—and by extension, our stakeholders—assurance that we’re designing something useful (i.e., stuff that people actually want or need) and usable (i.e., stuff that people can easily use),” notes Cara.
In his talk at UXIM, UX & design expert Jared Spool agrees. “The biggest design opportunities are what frustrates our users... and there are so many things that can frustrate our users.” We can help uncover where those frustrations are and how they’re impacting utility and usability through data.
“Stakeholders ultimately just want their product to work and work well,” says Cara. “Seeing that decisions are made because they’re grounded in real evidence gathered from actual users can help give them confidence that this team they’ve hired (us!) are doing the right thing.”
When we use data-driven design, we can find the most crucial areas for improving or innovating—the places where we’ll see our biggest returns on usability and utility. As Pavilscak notes, “A big part of using data to inform UX design is figuring out what we care about most.”
Step 3: Highlight All The Other Advantages, Too
Pavilscak also highlights the main areas where UX design sees the benefit of data. “When UX designers use data, I’ve found that there are really three main stories: Proving a point, improving an experience, and discovering something new or, at least, something that’s not obvious.”
In enterprise UX specifically, we typically use data to either confirm what our intuition tells us is likely going on (prove a point) or inform us about something we’re not sure about (improve an experience). But we can also use data to discover. It’s something that’s done a lot in consumer contexts—when we’re seeking to establish product-market fit, for instance—but is typically overlooked in enterprise contexts.
“I think more of that research should be done for enterprise, really. Instead of just iterating and improving on legacy systems, why not look at how new technology and new tools can improve your employees’ workdays?” asks Cara.
Getting buy-in on exploratory research can be one of the hardest things to do, but when we are able to use data to offer support, it makes success a lot easier to come by.
Data-driven design has other benefits, as well. Cara notes two areas where relying on data to help inform our designs can improve internal communications and process over all.
The first is in team dynamics: Ownership of ideas and figuring who did something first or best becomes less of an issue when data is steering us in the direction of success. “It can help make decisions within a team—it’s no longer personal at that point, not about who’s “right” or “wrong”—the data just stand on their own,” she states.
And the second is something of particular importance in the enterprise: data can break down barriers among teams.
“User research can also help gain internal buy-in—departments are so siloed sometimes, simply because there’s not enough bandwidth to be aware of what’s going on in other places in the organization. Seeing the findings from research can help break through those silos and help stakeholders understand how to prioritize things.”
Ultimately, data-driven design is only one component of a well-executed design strategy. But it’s becoming increasingly important. In his presentation, Spool noted that “As designers, we need to accept and embrace the world of metrics and use their amazing powers to change the way we’re doing things.” We tend to think he’s onto something.
Data isn’t going away, and learning to work with it and use it to make our work better will be to everyone’s advantage. And once we’ve done that, we need to help our stakeholders see the advantage of embracing the world of data during the design process, too.
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