Designing for Enterprise Users

Designing for Enterprise

For decades, enterprise software was the ugly duckling of product design. The primary focus was on features, with little to no attention given to usability or aesthetics. As for the people using the software? Pretty much an afterthought. End users were seen as a captive audience with very few options other than “you’ll eat it and you’ll like it.”

Over the past ten years, a significant shift occurred, as a new breed of enterprise products came to market. This shift, dubbed “consumerization of the enterprise,” is characterized by a much-needed emphasis on design and usability, as well as go-to-market strategies and aesthetics that are more in line with consumer products.

Having spent the bulk of my 20-year career in digital product design, this has been a welcome change. Not only do enterprise users have higher expectations for what a product can and should should be, enterprise companies are now actively investing in design as a key differentiator.

This shift bodes well for the people that use these products as well as the designers that design them, whether in-house or at external agencies. But does this mean that we should approach designing enterprise products the same way we do consumer products? Arguably, there are still important differences – both at the audience and feature level – between designing for consumers and designing for enterprise.

Following are a few to remember:

  1. Different levels of complexity. Many consumer products, especially apps, focus on solving for a few core use cases. Elegantly solve for the 80% case, and you’ve addressed a huge part of the design challenge. Much of the products we design are in the analytics, big data, and security and dev-ops spaces. Products in these domains need to satisfy a variety of personas and use cases in order to be truly useful The use cases and flows tend to be more complex that a typical consumer product. How do you provide views into the data for the different user personas? How can you visualize large amounts of data in a meaningful and actionable way? As a designer, I actually like that complexity. The design problems you need to solve in enterprise are often not straightforward; you can’t always reference best practices. You’re not building a better mousetrap, you’re designing for an entirely new type of interaction or class of product. Our design teams love digging into challenges like this – cerebral puzzles that require a completely new approach to problem-solving.
  2. Enterprise users still have limited choices. While go-to-market strategies for many enterprise products have become more consumer (e.g. Freemium business models), once a company has decided on a product, the end users are still a bit of a captive audience. In other words, enterprise buyers have more choices and opportunities to easily evaluate different products, but end-users are still left with few options other than using the product or not. For better or worse most people will still use a badly designed tool if it’s of good value. So the opportunity there is to improve the user experience for people even though they’re not empowered to choose an alternative. But again, that requires slightly different thinking than a consumer product, where the end user is also the decision maker.
  3. Strong domain knowledge is key. Understanding what end users will really be doing with a tool, and how the tool itself works, is absolutely crucial if you’re going to design an engaging and effective user experience. While most people have experienced online shopping or taking photos with their smartphones the same is not true for analyzing large quantities of data or managing a code repository. For the type of products we work on, strong domain knowledge is critical. For example, understanding some of the fundamental concepts of data science (structured vs. unstructured data, strict schema vs. late-binding, etc.) allows us to not more easily design workflows for hooking up a data pipeline and how to divide tasks between the data engineer and data scientist user personas.

In the month ahead we’ll be diving deeper into each of these realms in a series of posts, and looking at how the role of design in the enterprise is evolving in ways you may not always expect.