THEMES ACROSS CASE STUDIES

Spot the patterns that repeat across many case studies

One case study tells you what happened to one organization; a set of them can show what keeps happening. Upload the cases to one Search+ workspace, ask which causes, decisions and outcomes recur across them, and open the citations to check that each pattern really appears in each case rather than in only one vivid example.

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Last updated October 2026

How to find patterns across case studies

  1. Collect the cases on one topic

    Upload the case studies you want to compare, for example a dozen product launches or a set of public health interventions, up to 10 files at a time. PDFs, Word files and scanned copies can sit in the same workspace.

  2. Write the lens as standing instructions

    In Workspace Context, state what counts as a pattern for you, such as "Look for causes of failure that appear in at least two cases, and keep the context of each case". It applies to every question.

  3. Ask for patterns, then check each case

    Ask which factors recur, then ask about each factor case by case. Open the citations so a pattern you report is backed by passages from more than one case.

Cross-case questions

Success factors

Which factors do the successful cases have in common that the unsuccessful ones lack?

Repeated failures

In how many of these cases does the failure trace back to underestimating costs, and where is it described?

Decision points

At what kind of moment do the protagonists usually make the decisive choice?

Context

Do the same patterns hold for the small organizations as for the large ones in this set?

Outliers

Which case contradicts the pattern the others show, and why does the case say it turned out differently?

What to look for across a set of cases

Comparable cases

Patterns are only meaningful across cases that are similar enough to compare. Check each case's setting, size and period before treating a factor as common to them.

Selection effects

Case collections are often chosen because the cases are dramatic or successful. Ask what the cases leave out, and be careful about general claims from a hand-picked set.

Outcome bias

Knowing how a case ended makes earlier choices look obviously right or wrong. Ask what the people in the case knew at the time of the decision.

Counter-examples

A single case that breaks a pattern can be the most instructive. Ask which cases do not fit before writing up the pattern.

Questions across the whole set

Ask across every case in the workspace or about one case alone, and each answer cites the case passages it relied on.

Patterns traced to passages

Search+ finds repeated claims and themes across documents in chat, and you can trace each one back to its supporting text.

Pattern types across case studies

Pattern typeAn exampleA question to ask Search+
Common causeThe same root cause behind several failuresWhich cases name poor communication as a cause?
Common responseOrganizations reacting the same wayHow did each company respond to the first sign of trouble?
Contrasting outcomesSimilar choices, different resultsWhich cases made the same choice but got different outcomes?
TimingWhen in the story the turning point comesAt what stage does each case reach its turning point?
Stakeholder conflictThe same groups clashing in different casesWhere do finance and operations disagree across these cases?

What is pattern-finding across case studies in Search+?

Pattern-finding across case studies in Search+ means asking questions across a set of cases in one workspace and receiving written answers that name recurring causes, decisions and outcomes, each with citations to the cases that show them. Deep Analysis (beta) is another way to ask Search+ to synthesize across the whole set, again with cited answers.

It is not a coded qualitative dataset or a cross-case coding sheet. You get cited answers in chat, which you can question further and check against each case.

Questions about patterns across case studies

Can Search+ do a cross-case analysis?
It supports one. You ask which factors recur and how each case handles them, and the answers cite the cases. Building the final analysis and its conclusions is your work.
How does it show which cases support a pattern?
Each answer cites the passages it used, case by case. If a pattern rests on one case only, the citations make that visible.
Can it find cases that break the pattern?
Ask directly which cases do not fit the pattern, then open their citations to see how they differ.
Can I keep adding cases later?
Yes. The workspace persists, so you can add cases as you find them and ask the same questions again across the larger set.
Can scanned cases be part of the set?
Yes. Scanned cases are read with OCR and join the pattern answers alongside the digital ones. A blurred exhibit in an old scan is the place to slow down: open the citation and check it against the original page.
Are the patterns guaranteed to be complete?
No. An AI answer may miss a case or a nuance, so confirm important patterns by asking about each case directly.

Learn what the cases teach together

Start a workspace, upload the cases, and ask which lessons keep coming back.

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