Creating Low-Fidelity or High-Fidelity Prototypes, Part 1

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A column by Janet M. Six
July 20, 2020

This month in Ask UXmatters, the UX professionals on our panel of experts begin their discussion of the various factors they consider when deciding whether to create low-fidelity or high-fidelity design deliverables or prototypes. Both levels of fidelity can be useful at different stages of a project, for product teams using different methods of development, and for different audiences and purposes.

In looking at these factors in detail, our experts consider how a prototype’s intended audience, intention, and project constraints all play key roles in determining which type of prototype to create.

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Every month in Ask UXmatters, our panel of UX experts answers readers’ questions about a broad range of user experience matters. To get answers to your own questions about UX strategy, design, user research, or any other topic of interest to UX professionals in an upcoming edition of Ask UXmatters, please send your questions to: [email protected].

The following experts have contributed answers to this month’s edition of Ask UXmatters:

  • Yilmaz Kulahoglu—UX Lead at Saggezza
  • Pabini Gabriel-Petit—Principal Consultant at Strategic UX; Publisher, Editor in Chief, and columnist at UXmatters; Founding Director of Interaction Design Association (IxDA)
  • Janet Six—Product Manager at Tom Sawyer Software; UXmatters columnist

Q: What factors do you consider in choosing whether to provide low-fidelity or high-fidelity design deliverables?—from a UXmatters reader

“The stage of a software-development project and the development method a team is using are typically the key determinants of the types of UX design deliverables I provide,” answers Pabini. “These days, most projects use agile-development methods, so it’s important to create lightweight design deliverables that I can iterate quickly. For early-stage design deliverables, I usually create fairly low-fidelity sketches to convey my design strategy. Often, I go straight from these sketches to creating HTML/CSS prototypes, working collaboratively with a prototyper or the development team. Working in HTML/CSS lets me create very high-fidelity designs, without investing time and effort in polishing deliverables rather than the product itself. The CSS styles that I create become part of the final code, which gives me control over the layout and look of the actual product and lets me avoid the frustration of developers’ implementing code that deviates from my designs.

“Of course, there are other factors you might need to consider as well—such as whether your product-team members are the only audience for your deliverables, or you’ll need to present them to executives—or even show your prototype to customers. The stages at which you’ll be conducting usability testing could also dictate the fidelity of your deliverables, requiring you to create anything from a paper prototype to a fully functional prototype.”

Factors in Choosing Low-Fidelity Versus High Fidelity

“Creating high-fidelity versus low-fidelity UX design deliverables usually depends on whether I’m working on a waterfall or an agile project,” replies Yilmaz. “They form a duality, not a polarity. There shouldn’t be a binary choice between high-fidelity and low-fidelity deliverables. Instead, they should be regarded as complementary to each other. Depending on whether you’re working on a waterfall or an agile project, it’s wise to take an adaptive approach to creating these two types of deliverables. The audience, intention, and constraints are three critical factors to which you may need to adapt in determining a deliverable’s fidelity.

“For the sake of simplicity, I won’t go into the differences between mockups, wireframes, and prototypes, but instead, simply refer to low-fidelity and high-fidelity design deliverables.”

The Audience

“You’ll need to create design deliverables at different phases of your team’s product-development lifecycle—from ideation to implementation,” explains Yilmaz. “Your design deliverables should communicate to different audiences along this journey, for example:

  • product teams—These teams consist of representatives of various disciplines such as business and development. These are the stakeholders that you should include in the design process—early and often. To discover the viability and feasibility of your design ideas in a collaborative manner, you can kick off your conversation with them using low-fidelity deliverables. Fidelity then increases as the product requirements and constraints mature.
  • executives and upper management—If your deliverables land on the desk of an executive or someone in upper management, your designs have most likely already gained some traction. These leaders usually want to see a branded deliverable that closely represents the final product—in terms of the product vision, look and feel, and the user experience. Their time is valuable—so especially for an enterprise user experience—it’s wise to be realistic rather than idealistic.
  • internal UX team—UX professionals need to be able to brainstorm design ideas together by creating sketches or other low-fidelity artifacts. Practicality is the key for this audience.
  • representative users—If your deliverables end up in front of your users, that probably means you want to learn from them. What do you intend to learn?”

The Intention

“Too many UX professionals tend to skip the crucial question: What do I intend to communicate or learn through my deliverables?” continues Yilmaz. “For instance, your intention could be to learn about the technical feasibility of a particular workflow from a technical audience. In this case, you wouldn’t want to put a high-fidelity design in front of your audience because they might get hung up on visual or content details.

“Conversely, your intention could be to find out whether your users understand the content you’ve presented in a user interface by having them complete a realistic task scenario. In such a situation, placing lorem ipsum text in your design deliverable would defeat your purpose.

Especially when you’re deciding on the fidelity of a design for testing, you should always differentiate between these two research questions:

  1. Is it useful?
  2. Is it usable?

“Understanding your audience’s expectations is also essential when you’re thinking about your intent in creating design deliverables. To understand their expectations, you’ll need to ask the right questions, then let your audience speak.”

The Constraints

“In the software industry, common constraints include resources, time, and budget,” says Yilmaz. “A big part of any UX professional’s job is understanding and solving design problems within these constraints.

“The greatest value that UX designers provide lies in their ability to put together a realistic representation of a product so they can test their design ideas with target users. In their book Lean UX, Jeff Gothelf and Josh Seiden describe these deliverables as an ‘approximation of the end experience.’

“Testing our design deliverables with users lets us validate and iterate our design ideas based on our learnings, before scaling our designs. Learning through UX research costs much less in time, resources, and money than shipping a product that fails in the marketplace. Nevertheless, we must consider the time and effort it takes to build a fully interactive, high-fidelity design prototype. It requires a considerable amount of time and effort from what might be the scarcest resource on a team or in a company: the UX designer, whose time may be spread thin over multiple projects. It’s important to balance the actual value the prototype creates with the potential waste that can result from the production of high-fidelity design prototypes.

Prototyping a Minimum Viable Product

“To adapt our UX design deliverables to the needs of our audience, we need to be able to utilize all the different methods in our toolbox and continually analyze their cost versus the benefits they provide,” advises Yilmaz.

“In 2011, Eric Ries described a minimum viable product (MVP) as ‘the smallest thing we could do/make to test a product hypothesis.’ Depending on your team’s acceptance of risk and your confidence in a design solution, this smallest thing could fall anywhere on a spectrum between cheap and fast versus costly and time consuming. As UX professionals, we all know that we cannot produce design deliverables at the drop of a hat—especially high-fidelity prototypes. Unfortunately, most of the people we work with tend to believe the opposite. Therefore, we should base our decisions about whether to deliver low-fidelity versus high-fidelity prototypes on the important constraints I’ve just described.”

We also need to consider who will use these prototypes, as well as benefit from the results of our UX research. To whom will you send your MVP prototypes? To

  • Engineering—so they can build the product
  • Marketing—so they can develop a marketing plan
  • executive management—so they can understand where the product fits into the company’s overall strategy

Make sure that you create an MVP prototype that fulfills the purpose of a minimum viable product for both its direct and indirect recipients.

Next month, in Part 2 of this series, the UX professionals on our panel of experts will continue their discussion of the factors that determine the appropriate level of fidelity for UX design deliverables and prototypes. 

Product Manager at Tom Sawyer Software

Dallas/Fort Worth, Texas, USA

Janet M. SixDr. Janet M. Six helps companies design easier-to-use products within their financial, time, and technical constraints. For her research in information visualization, Janet was awarded the University of Texas at Dallas Jonsson School of Engineering Computer Science Dissertation of the Year Award. She was also awarded the prestigious IEEE Dallas Section 2003 Outstanding Young Engineer Award. Her work has appeared in the Journal of Graph Algorithms and Applications and the Kluwer International Series in Engineering and Computer Science. The proceedings of conferences on Graph Drawing, Information Visualization, and Algorithm Engineering and Experiments have also included the results of her research.  Read More

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