Figma Might Be Making Your Designs Worse — The 2026 Research Says So
There's an assumption that runs quietly through every design team I've encountered: that the tool is neutral. That switching from paper sketches to Figma changed the workflow, not the thinking. That the output quality depends on the designer, and the tool is just the medium.
Two peer-reviewed studies published in 2026 disagree with that assumption — specifically, and with data.
What Tufail et al. Actually Found
Tufail and colleagues, writing in Design Studies in January 2026, compared design output quality and cognitive load across pure-digital workflows (Figma-primary) and hybrid workflows (analog sketching followed by digital execution). They measured cognitive load using established protocols and had independent raters assess design innovation and completeness.
The finding that landed: pure-digital workflows imposed higher extraneous cognitive load — the mental overhead that doesn't contribute to design thinking — than hybrid workflows.
Cognitive load theory distinguishes between intrinsic load (the complexity inherent in the task), germane load (the processing that contributes to learning and design quality), and extraneous load (the overhead imposed by how the task is presented or structured). The goal in any cognitively demanding task is to minimize extraneous load so you have more capacity for the work that actually matters.
Digital tools, it turns out, generate more extraneous load than their designers typically account for. The interface conventions, layer management, component navigation, property panels — all of it consumes working memory that, in an analog workflow, would be available for the design problem itself.
The consequence: designers using pure-digital workflows showed measurably lower design innovation scores than those using hybrid approaches. Not because they were less skilled. Because they had less cognitive capacity available for the creative work.
The EEG Data from 70 Sessions
A parallel study by Holý and colleagues, published in the International Journal of Occupational Analysis in March 2026, came at the same problem from a different angle: wearable EEG and eye-tracking data from 70 design sessions across different tools and times of day.
The headline finding on timing: morning cognitive performance scored 63–67% on their composite measure. Afternoon performance: 25–63%. That's not a small effect. That's a cliff. For the same designers, using the same tools, working on the same types of problems — their afternoon cognitive capacity was sometimes less than half their morning capacity.
The finding on tools: the EEG data showed different patterns of frontal lobe activation depending on whether designers were working in digital tools versus hybrid methods. Pure-digital workflows produced more patterns consistent with extraneous cognitive processing — the brain managing the tool rather than the problem.
What neither paper suggests is that you should abandon Figma. The research conclusion is more specific and more interesting than that: tool choice is not neutral, and most design teams make no systematic decisions about it. They pick the tool that's fastest to produce handoffs, not the tool that produces the best thinking.
The Conversation Design Teams Aren't Having
In most product teams, the design tool decision was made once — either when the team formed or when Figma became industry-standard — and has never been revisited as a strategic decision.
What would it look like to make a deliberate decision? Not "what can we export to engineers most efficiently?" but "what workflow produces the best design thinking per hour of effort?"
The Tufail data suggests a specific answer: for generative phases — ideation, exploration, problem framing — hybrid workflows (sketching first, digital later) produce better outcomes. For refinement phases — component specification, handoff, iteration on an established direction — pure-digital has clear advantages in speed and fidelity.
The mistake most teams make is using Figma for everything, including the phases where it imposes the highest cognitive penalty with the lowest productivity payoff. Early-stage design work in a digital tool is high-extraneous-load work on a problem that hasn't been scoped yet. That's a bad combination.
The practice that emerges from the research isn't complex: rough analog first, digital when you have something to refine. But it requires actively structuring your workflow rather than defaulting to "open Figma."
Why This Doesn't Get Discussed
Design tool discourse is almost entirely vendor-driven. Figma publishes case studies. Tool vendors sponsor design conferences. The publications that reach most designers are sponsored or affiliated with the tools they cover.
Peer-reviewed empirical research on tool choice — specifically research that measures cognitive load with neuroimaging or wearables, rather than self-report surveys — is essentially absent from the design practitioner conversation. Tufail et al. and Holý et al. exist in academic journals that most designers never encounter.
The result is that most design teams make tool decisions based on what they saw other teams doing at conferences, what the Figma blog said last quarter, and what's easiest to justify to engineers. None of those inputs are connected to what actually produces better design thinking.
The Timing Finding Is Immediately Actionable
Even if you're not going to restructure your entire tool workflow, the timing data from the EEG study is immediately actionable.
If your afternoon cognitive capacity is sometimes 25–40% of your morning capacity, the scheduling implication is direct: put your most cognitively demanding design work — the explorative, generative, problem-framing work — in the morning. Put administrative work, meetings, review cycles, and handoffs in the afternoon.
This isn't a novel productivity principle. It's well-established chronobiology. What's new is the 2026 EEG data that quantifies the effect specifically for design work, which is useful because design teams tend to treat cognitive quality as uniform across the day.
Scheduling a major design sprint for a 3pm slot because that's when everyone's calendar is open is making a significant cognitive bet that the Holý data suggests you're likely to lose.
The Neutral Tool Assumption
The assumption that the tool is neutral — that what matters is the designer's skill, and the tool just transmits it — is convenient because it makes every constraint feel like a technical problem with a technical solution.
It's also empirically incorrect. The tool shapes the thinking. The interface constraints become cognitive constraints. The workflow sequence affects what the brain can do with the problem.
The 2026 research doesn't prescribe a specific workflow. It dismantles the assumption that tool choice is a logistics decision rather than a design decision.
If the goal is better design thinking — not just better design exports — then which tool you use, and at what point in the process, and at what time of day, are all questions worth treating as strategic rather than inherited.
Cover photo by Kaboompics via Pexels.