The Problem: You Organized the Information Wrong
You spent two hours organizing your competitive analysis. You filed every competitor under category: CRM tools, marketing platforms, analytics tools. The CEO asks: "Who are the three players with the biggest funding this year?" You have no idea — you organized by product type, not by funding, time, or hierarchy. The information is there; it's just organized the wrong way for the question.
This is the organizing mismatch: information organized for one type of question doesn't answer a different type of question well. A phone book alphabetized by name is useless if you need all the dentists in your zip code. A calendar organized by chronology is useless if you need all the meetings with a specific person.
The LATCH information framework gives product managers, strategists, and knowledge workers a vocabulary for choosing how to organize information — five distinct schemes, each optimal for a different type of question. Understanding LATCH helps you organize information the right way the first time, and recognize when a re-organization would make a dataset dramatically more useful.
Where LATCH Comes From
LATCH was developed by Richard Saul Wurman, an architect, graphic designer, and information architect who coined the term "information architecture" (IA) in the 1970s. Wurman published LATCH in his 1996 book Information Architects and again in Information Anxiety 2 (2000).
Wurman's core argument: all information in the world can be organized in only five ways. Not because he chose five arbitrary categories, but because these five exhaust the logical possibilities for how humans relate to information:
- Where it is (Location)
- What it's called (Alphabet)
- When it happened (Time)
- What kind it is (Category)
- How important it is (Hierarchy)
This claim is genuinely useful for information workers: if you can identify which of the five organizational schemes you need for a specific question, you can organize your data accordingly — rather than organizing by habit or by what's easy.
LATCH has been influential in information architecture, UX design, and instructional design. It's also applied in data visualization (choosing chart type by the organizational relationship you want to show) and knowledge management.
The LATCH Framework, Applied Step by Step
L — Location
What it is: Organizing information by where things are — geographic location, physical position, spatial relationship.
Best for answering: Where is X? What's near Y? How does distribution vary by region?
Examples:
- A world map of sales by country (organized by geographic location)
- An office seating chart (organized by physical position)
- A user research report organized by market (US vs. EU vs. APAC)
- A logistics report organized by distribution center location
When to choose Location: When the "where" question is central to the analysis or decision. Geographic variation in user behavior, market penetration by region, physical layout of resources, supply chain by geography.
When NOT to choose Location: When location is irrelevant and the question is about time, type, or priority. Don't organize competitor profiles by country of headquarters unless geography is the relevant differentiator.
A — Alphabet
What it is: Organizing information alphabetically — by name, title, keyword, or any other alphabetized label.
Best for answering: Is X in the list? Give me the item named Y.
Examples:
- A phone directory (organized by last name)
- A glossary or dictionary
- An A-Z index in a book
- A dropdown menu of options in a software interface
When to choose Alphabet: When users need to look up specific known items by name and the collection is large enough that browsing is impractical. The phone book is alphabetical because people know the name of who they're looking for.
When NOT to choose Alphabet: When the relationship between items matters more than the ability to look up specific items. Alphabetical organization destroys chronological, hierarchical, and category-based relationships. If you don't know what you're looking for (discovery), alphabetical is almost always wrong.
T — Time
What it is: Organizing information chronologically — by when things happened, when they will happen, or in what sequence they occurred.
Best for answering: When did X happen? What comes before/after Y? How did this evolve over time?
Examples:
- A project timeline or Gantt chart
- A changelog or version history
- A news feed or social media timeline
- An investigation into a product's development history
- A customer journey map (organized by the sequence of touchpoints)
When to choose Time: When sequence or chronology is the meaningful relationship — process documentation, historical analysis, product roadmaps, event timelines.
When NOT to choose Time: When time is incidental and the category, priority, or location is what matters. A list of competitors organized chronologically by founding date doesn't help you understand the competitive landscape.
C — Category
What it is: Organizing information by type, kind, or characteristic — grouping similar things together.
Best for answering: What kind of X do we have? How many X fall into each type?
Examples:
- A product catalog organized by product line (Electronics, Clothing, Books)
- A user research report organized by persona
- A budget organized by expense category (Salaries, Marketing, Infrastructure)
- A knowledge base organized by topic (Security, Billing, Getting Started)
When to choose Category: When the type or kind of thing is the relevant organizing dimension. Category organization is most natural when items have a clear taxonomy and the question is about groups, not individuals.
When NOT to choose Category: When categories are ambiguous, overlapping, or when the question is about individual items rather than types. If you're asking "is X bigger than Y?" (hierarchy), category doesn't help.
H — Hierarchy
What it is: Organizing information by magnitude, importance, rank, or size — from most to least (or least to most) of some dimension.
Best for answering: What's the most/least X? How does this rank? Where is the threshold?
Examples:
- A competitive analysis ranked by market share
- A bug prioritization list ranked by severity
- A list of customers ranked by annual contract value
- A Pareto chart (top 80% of effects from 20% of causes)
- A performance review ranking team members by output metrics
When to choose Hierarchy: When importance, priority, quantity, or magnitude is the meaningful dimension. Decision-makers almost always want to know "what matters most" — which is inherently hierarchical.
When NOT to choose Hierarchy: When rank doesn't exist or when the question is about relationships rather than magnitude. Organizing a feature roadmap purely by importance can obscure time dependencies (some features must come before others regardless of importance).
A Worked Example
A product manager at a SaaS company needs to organize a competitive landscape analysis of 25 competitors for a strategic planning session.
The wrong question: "How should I organize this?"
The right question: "What questions do our stakeholders need to answer from this analysis?"
Question 1: "Who are the market leaders we need to take most seriously?" → Hierarchy (organize by market share, customer count, or funding)
Question 2: "Are there geographic gaps in the competitive landscape where we might have room?" → Location (organize by primary market served: North America, Europe, APAC)
Question 3: "What types of competitors exist?" → Category (organize by product type: full-suite CRMs, point solutions, industry verticals)
Question 4: "Which competitors entered the market recently that we might have missed?" → Time (organize by founding or funding date)
The LATCH insight: One dataset, four valid organizations, each answering a different question. The PM creates four views of the same competitor data — a hierarchy table for the executive summary, a category breakdown for the product team, a timeline for the market trends analysis, and a geographic heat map for the market entry discussion.
Where LATCH Shines
For information architecture decisions: When designing navigation for a website, app, or knowledge base, LATCH provides a framework for evaluating organizational choices. "Should this knowledge base be organized alphabetically (by feature name) or by category (by user goal)?" LATCH surfaces the tradeoff.
For report and dashboard design: Before organizing a report, ask: what questions will readers be trying to answer? Match the organizational scheme to the question.
For communicating complex data: Choosing the right LATCH scheme for a visualization makes data self-explanatory. A time series chart (T) communicates trend. A ranked bar chart (H) communicates priority. A geographic heat map (L) communicates spatial distribution. Using the wrong scheme forces readers to mentally re-organize the data to answer their question.
Where LATCH Breaks Down
Many datasets need multiple schemes: A competitive analysis needs both Hierarchy (who's biggest) and Category (what types). LATCH doesn't tell you which single scheme to use — it helps you name which schemes serve which questions. Real analysis often requires multiple views.
The schemes aren't always cleanly distinct: Is "chronological by adoption rate" Time or Hierarchy? Is "by product category" Category or Hierarchy if some categories are more important? The framework is conceptual; edge cases require judgment.
LATCH is a vocabulary, not a formula: Knowing the five schemes doesn't tell you which to use in your specific situation — that requires understanding what questions your audience is trying to answer. The framework helps name and compare; it doesn't eliminate the judgment.
Tools That Support LATCH-Based Organization
| Tool | LATCH support | Notes |
|---|
| Airtable / Notion databases | All five (filter, sort, group by any field) | Ideal — one dataset, multiple views |
| Excel / Google Sheets | All five (sort, filter, pivot) | Standard; less visual than databases |
| Tableau / Power BI | Location, Time, Hierarchy especially | Strong for visualization by LATCH scheme |
| Miro / FigJam | Category (affinity grouping), Hierarchy (priority matrix) | Good for workshop-based organization |
| Obsidian | Category (folders/tags), Hierarchy (MOCs), Alphabet (file names) | PKM application of LATCH |
| WebSnips | Category (collections by topic), Hierarchy (starred/priority) | Web clips organized by LATCH principles |
WebSnips and LATCH: Organizing web clips and research into collections applies Category (by topic, project, or type) as the primary LATCH scheme. For time-sensitive research (competitive intelligence, news monitoring), organizing by Time (when the content was published) is relevant. LATCH provides a vocabulary for intentionally choosing how to organize collected content.
Common LATCH Mistakes
Mistake 1: Organizing by habit rather than by question.
Most people alphabetize or categorize by default, regardless of what questions their audience will ask. Before organizing anything, ask: what does the audience need to find or understand? Then choose the LATCH scheme that serves that question.
Mistake 2: Using one scheme when multiple are needed.
A product roadmap needs both Time (when will each feature ship?) and Hierarchy (what's the priority when there are conflicts?). A single LATCH scheme often isn't enough; the question is which scheme serves each layer of the analysis.
Mistake 3: Alphabetical as a default fallback.
Alphabet is the right scheme for lookup (find a specific known item). It's almost never the right scheme for analysis (understand patterns, find important items, explore relationships). Defaulting to alphabetical in a business context is usually wrong.
Mistake 4: Choosing a LATCH scheme that doesn't match the question.
If the question is "where are our customers?" and you organize by revenue (Hierarchy), the audience has to mentally re-sort the data. Match organization to question.
Frequently Asked Questions
What if my information doesn't fit neatly into one LATCH scheme?
Most real datasets don't fit neatly into one — they need multiple views for different questions. Create multiple versions (or views in a database tool) organized by different LATCH schemes. The question is always "what question does this view need to answer?"
Is LATCH relevant for personal knowledge management, not just professional work?
Yes. Your reading list might be organized by Topic (Category), by Date Added (Time), by Importance (Hierarchy), or by Author's Last Name (Alphabet) — the LATCH framework helps you notice which organization serves your actual retrieval patterns.
How does LATCH relate to data visualization chart types?
Closely. Bar charts and ranked lists visualize Hierarchy. Line charts visualize Time. Maps visualize Location. Category breakdowns visualize Category. Hierarchical trees and org charts visualize... Hierarchy. Choosing the right chart type is often equivalent to choosing the right LATCH scheme.
Key Takeaways
- LATCH information framework is Richard Saul Wurman's five-scheme taxonomy for organizing any information: Location, Alphabet, Time, Category, Hierarchy — all information can be organized in one (or more) of these five ways.
- Developed by Wurman in Information Architects (1996) as a foundational concept in information architecture.
- Match scheme to question: the right LATCH scheme is the one that answers the questions your audience will actually ask, not the one that's easiest to create.
- Alphabet is for lookup, not analysis: alphabetical organization is appropriate when users know what they're searching for; it's almost never appropriate for analytical or discovery contexts.
- Most analyses need multiple LATCH views — create separate views (or database filters) for different organizational needs.
- Hierarchy is the most underused: ranking by magnitude, importance, or impact is often the most decision-relevant organization but requires defining the ranking dimension.
Conclusion
LATCH is one of those frameworks that, once learned, is impossible to forget — because once you see that all organization is one of five schemes, you can't un-see it. The phone book is Alphabetical. The calendar is Time. The org chart is Hierarchy. The product catalog is Category. The city map is Location. Recognizing which scheme is in use (and whether it matches the question) is a core information literacy skill. For product managers, strategists, and knowledge workers who regularly organize, present, and use information to make decisions, LATCH provides the vocabulary to make deliberate organizational choices rather than defaulting to whatever feels natural.
Try WebSnips free — organize your research and web clips into collections that match the LATCH scheme most useful for your projects: by topic (Category), by priority (Hierarchy), or by date saved (Time).