Table of Contents
- 1. Why UX Research Often Fails to Influence Real Decisions
- 2. What Is the Elito Method, Really?
- 3. The 5 Layers of the Elito Method (From Fact to Meaning)
- 5. When the Elito Method Works Best (And When It Doesn’t)
- 6. Elito Method as a Sense-Making Tool
1. Why UX Research Often Fails to Influence Real Decisions
UX research rarely fails because teams did not collect enough data. More often, it fails because the data never becomes meaning.
Many teams recognize this feeling:
- Research decks are well-crafted, but decisions stay the same.
- Insights sound interesting, but no one is confident about what to do next.
- Teams say, “We learned a lot,” followed by silence.
The problem usually sits between three stages that are treated as separate activities:
| Stage | What Happens | Where It Breaks |
|---|---|---|
| Observation | Teams gather quotes, behaviors, artifacts | Too much raw detail |
| Insight | Patterns are discussed and labeled | Meaning stays abstract |
| Decision | Product or design choices are expected | No clear direction |
This gap is not about effort. It is about translation.
1) When Observations Stay as Observations
Teams are often good at capturing what happened.
- “Three participants abandoned the form halfway.”
- “Users switched tabs frequently during setup.”
- “Someone paused for a long time before clicking submit.”
These are valuable facts. But facts alone do not tell a team what matters most.
Without a structured way to interpret them, observations pile up. They feel important, but they do not compete with roadmap pressure, stakeholder opinions, or technical constraints.
2) The Hidden Cost of Unstructured Complexity
Research outputs often suffer from what can be called unstructured complexity.
This happens when:
- There are many signals, but no hierarchy.
- Insights are phrased as themes, not decisions.
- Everyone agrees something is “interesting,” but no one agrees on priority.
As a result, insights stop at the slide level. They inform conversations, but they do not anchor choices.
3) “We Saw a Lot, But What Should We Do?”
This is the most honest sentence teams say after research.
It is also the clearest signal that synthesis did not go far enough.
The real challenge is not finding patterns. It is answering two harder questions:
- Why does this observation matter?
- What kind of design or product direction does it imply?
This is the space where many UX research methods become vague. And this is exactly the space the Elito Method was designed to make explicit.
2. What Is the Elito Method, Really?
The Elito Method is often described as a UX synthesis template.
A more useful way to think about Elito is this:
Elito is a sense-making framework that helps teams turn research observations into actionable design principles.
It is not meant to produce a prettier research summary. It is meant to make the difficult middle step visible: the step where teams move from “what happened” to “what it means” to “what we should do next.”
1) Why This Middle Step Is So Hard
In most teams, there is a silent expectation that research will naturally lead to product direction.
But in reality, research produces inputs, not decisions.
Between inputs and decisions, teams need to do work that is often fuzzy:
- deciding which signals are meaningful
- interpreting why behavior happened
- extracting values and motivations
- translating those into design direction that a team can align on
When this step is not explicit, it still happens. It just happens informally:
- the loudest opinion wins
- teams default to what is easiest to build
- stakeholders interpret the data through their own narrative
- research becomes “supporting evidence” rather than a decision tool
Elito tries to prevent that drift by forcing teams to externalize the reasoning.
2) Analysis vs. Synthesis in Plain Terms
A lot of confusion comes from using “analysis” and “synthesis” as if they are the same thing.
Here is a simple distinction that tends to hold up in practice:
| Mode | What You Are Doing | Common Output |
|---|---|---|
| Analysis | Breaking information into parts | Notes, tags, clusters, themes |
| Synthesis | Recombining parts into meaning and direction | Principles, concepts, priorities |
Analysis helps you understand. Synthesis helps you decide.
Many teams stop at analysis because it feels objective. Clustering notes, labeling themes, and counting mentions all look rigorous.
But synthesis requires interpretation. That can feel risky because interpretation introduces judgment.
Elito is useful because it acknowledges something important:
- you cannot reach decisions without interpretation
- the goal is not to avoid judgment
- the goal is to make judgment more reasoned, transparent, and shared
3) The Real Question Elito Helps You Answer
Teams often jump from observation to solution:
- “Users abandoned onboarding, so let’s add tooltips.”
- “People struggled with filters, so let’s redesign the UI.”
- “Customers asked for exports, so we should build export.”
Sometimes those fixes work. Sometimes they are surface-level patches that miss the real motivation.
Instead, Elito is built around a simple question:
“Why is this observation important, and what should we do because of it?”
That question sounds obvious, but it is rarely answered in a structured way.
Elito slows that jump down, but only enough to reveal the reasoning:
- What did we actually see?
- Why might it matter?
- What value is underneath that behavior?
- What concept or principle should guide our design response?
- What memorable framing helps the team stay aligned?
That sequence is what makes Elito feel different from many other synthesis tools.
4) Where the Name Comes From
The method is named after “Eli Toolbox,” associated with work led by Eli Blevis in academic HCI contexts, and later developed through early-2000s design research projects by collaborators such as Trysh Wahlig, Margaret Alrutz, and Ben Singer.
Elito was created because teams needed a reliable way to connect research to design direction, especially when data was messy and qualitative.
5) What You Get When You Use Elito Well
A strong Elito output usually creates two things:
- design direction that can be applied across features, not just a one-off fix
- a shared language that makes tradeoffs easier
Instead of ending with “users want X,” you end with statements closer to:
- “Users need to feel in control during setup, so we should prioritize reversible actions and clear progress signals.”
- “People interpret delays as uncertainty, so we should design for visible system status even when work is happening in the background.”
Those are not UI mockups, but are decision anchors.
3. The 5 Layers of the Elito Method (From Fact to Meaning)
The Elito Method breaks synthesis into five distinct layers. Each layer answers a different question, and each one slightly raises the level of abstraction.
What makes Elito powerful is not the layers themselves, but the discipline of not skipping any of them.
Below, we will walk through each layer using a simple, non-UI-specific example: a team researching how people manage recurring personal tasks across different tools.
| Layer | Core Question | Output Type |
|---|---|---|
| Observation | What happened? | Factual statements |
| Judgement | Why does it matter? | Interpreted meaning |
| Value | What motivates the user? | Human drivers |
| Concept / Sketch | How should we respond? | Design direction |
| Key Metaphor | How do we remember this? | Shared language |
1) Observation: What Did You Actually See?
An observation should describe only what was seen, heard, or recorded, without interpretation or explanation.
| Good Observation | Slips into Interpretation |
|---|---|
| “The participant rewrote the same task title in two different apps.” | “The participant was confused by the system.” |
| “Three users paused before confirming deletion.” | “Users were anxious about deleting items.” |
| “People checked their calendar after adding a task.” | “They did not trust the task list.” |
The difference may feel subtle, but it matters.
Once interpretation sneaks in, later layers become biased. Teams start treating assumptions as facts.
If you can prepend “I saw that…” or “I heard that…” and the sentence still makes sense, it is probably a valid observation.
2) Judgement: What do you think makes users behave that way?
Judgement is the first place where interpretation is allowed, and encouraged.
Here, the question shifts from what happened to why this might be important.
This is not personal opinion. It is reasoned interpretation, grounded in the observation.
Example:
| Observation | Judgement |
|---|---|
| “Users rewrote the same task title in two apps.” | “Tasks are being mentally reframed depending on context, which suggests people do not think of tasks as static objects.” |
| “Participants paused before deleting.” | “Deletion feels risky, likely because recovery is unclear or irreversible.” |
A useful check at this stage is asking:
- If this is true, what does it imply about how people think or behave?
- What assumption about the user does this challenge?
Judgement statements should feel debatable, but defensible.
- If no one can disagree with a judgement, it is probably too shallow.
- If everyone disagrees, it may be under-supported.
3) Value: What Truly Motivates the User?
This layer moves away from features and workflows, and toward human motivation.
Value is not what the product offers. It is what the person cares about.
Common traps at this stage include:
- describing functional needs as values
- confusing “nice to have” with “emotionally sticky”
Compare these:
| Not Quite Value | Clear Value (Context-Aware) |
|---|---|
| “Users want faster task creation.” | “A marketing manager juggling multiple live campaigns wants to unload tasks quickly before they become another source of mental stress.” |
| “People want fewer steps.” | “A remote worker switching between meetings wants to conserve mental energy for actual work, not for managing tools.” |
| “Users need better organization.” | “A junior consultant wants reassurance that nothing important is being forgotten, especially when deadlines depend on others.” |
Value statements explain why a behavior exists, not just what happened.
What changes on the right side is not wording, but perspective.
- The subject is no longer a generic “user”
- The value is tied to a situation, pressure, or risk
- The motivation explains why the behavior exists
4) Concept or Sketch: Turning Meaning into Direction
At this stage, teams often expect screens or flows, which limits the usefulness of this layer.
In the Elito Method, a concept is not a UI idea. It is a design stance that constrains future decisions.
A strong concept should feel uncomfortable in a good way. It should rule out certain solutions.
Example: The “Why Does This Feel Like My Fault?” Moment
Context
- Role: Freelance designer
- Environment: Client-dependent work
- Situation: Waiting for feedback before proceeding
Observation
- Tasks remain scheduled for “today” for several days.
- The user reschedules them repeatedly.
- The interface marks them as “overdue.”
What Is Actually Happening
- “I can’t move forward without feedback.”
- “But the app makes it look like I failed.”
- “Seeing this makes me avoid opening the list.”
Underlying Value
This user wants the system to distinguish between personal inaction and external dependency.
Concept (Design Direction)
“Do not frame uncontrollable delays as personal failure.”
This concept shapes:
- how time is represented
- which language is used for delays
- whether status communicates blame or context
It does not say how to implement it. It says what the system should not imply.
Any solution that forces early precision would violate this concept.
5) Key Metaphor. A Sentence the Team Remembers
The final layer translates direction into shared memory.
Principles are precise, but they are not sticky.
Metaphors are sticky because they compress meaning into something teams can feel.
A good key metaphor is not clever. It is diagnostic.
It helps teams ask, “Are we violating this?”
A key metaphor is a short, vivid phrase that captures the intended experience.
Example: The “Why Does This Feel Like My Fault?” Moment
Concept
Do not frame uncontrollable delays as personal failure.
Key Metaphor
“Waiting is not procrastinating.”
Used in practice:
- “This label makes waiting look like procrastination.”
- “Are we blaming the user for something they can’t control?”
5. When the Elito Method Works Best (And When It Doesn’t)
Like most synthesis tools, the Elito Method is powerful in the right context and frustrating in the wrong one.
Understanding when to use it is just as important as knowing how to use it.
1) Research Is Abundant, but Alignment Is Weak
This often happens after:
- generative user research
- diary studies or longitudinal research
- open-ended interviews
- exploratory field studies
In these cases, teams usually have:
- dozens of quotes
- many observations
- multiple, equally plausible interpretations
Elito helps by forcing the team to converge on meaning.
Instead of debating which insight is “right,” teams discuss:
- which judgments are better supported
- which values feel most central
- which concepts are worth designing around
The result is not consensus by volume, but alignment through reasoning.
2) You Need Design Principles, Not Just Features
There are moments when teams need something more durable than a feature decision.
For example:
- entering a new problem space
- redefining an existing experience
- unifying design across multiple teams or surfaces
Elito outputs work well here because they produce:
- principles that can guide future decisions
- concepts that scale beyond one screen
- metaphors that help teams self-correct over time
Instead of asking, “Should we add this feature?”, teams start asking, “Does this align with our core direction?”
3) Early-Stage or Reframing Phases
Elito is especially useful when the problem itself is still fluid.
This includes:
- new products or services
- major shifts in user behavior
- rethinking a legacy experience
At this stage, premature solutions can lock teams into the wrong assumptions.
Elito slows teams down just enough to clarify what actually matters before committing.
6. Elito Method as a Sense-Making Tool
At a certain point in your work, the challenge shifts. It is no longer about knowing more methods. It is about making better sense of complexity, faster, and with others.
This is where the Elito Method starts to feel less like a UX framework and more like a thinking skill.
Most teams are not short on information. They are short on shared meaning.
Elito helps because it externalizes thinking that usually stays implicit:
- why one observation matters more than another
- how interpretation leads to direction
- where values sit underneath behaviors
By naming these steps, teams can discuss them explicitly instead of talking past each other.
Conversations change from:
- “I think this is important.”
- “That’s just one user.”
to:
- “Which judgement is better supported?”
- “What value does this point to?”
- “If we believe this metaphor, what does it rule out?”
That shift alone improves the quality of collaboration.
It is tempting to judge good work by its artifacts: screens, flows, documents, or frameworks.
But artifacts are outputs. Meaning is what actually shapes decisions.
Good practitioners are not the ones who generate the most insights. They are the ones who connect observations to values, values to concepts, and concepts to choices.
The Elito Method is useful because it respects that reality.
It does not try to eliminate ambiguity. It helps teams work with it, responsibly.
If there is a single idea worth carrying forward, it is this:
Good design is not about collecting more insights. It is about connecting them well enough that people can act.
That is the real value of Elito, and why it remains relevant well beyond UX research itself.