A Circus Mindset for Research Operations

At TMRE 2025, Duncan Fisher delivered a talk that stayed with me long after the conference ended. His provocation was simple but profound: "Run your business like a circus." The instruction seemed absurd at first—what could the high-wire precision of Cirque du Soleil possibly teach insights teams about customer research? But as Fisher unpacked the metaphor, a compelling framework emerged for understanding what separates exceptional research operations from merely functional ones.

The circus analogy resonates because it captures three essential elements that research leaders often struggle to balance: precision, ensemble performance, and spectacle. These aren't frivolous considerations. They represent the operational foundation, collaborative architecture, and stakeholder engagement that determine whether insights drive decisions or gather dust in shared drives.

Consider the economics of research inefficiency. When Forrester surveyed 200 insights leaders in 2024, they found that organizations spend an average of $2.4 million annually on research that fails to influence strategic decisions. The primary cause wasn't flawed methodology or insufficient sample sizes. It was operational friction—research that took too long to deliver, required too much cross-functional coordination to execute, or failed to capture executive attention when presented.

Fisher's circus framework offers a different way to think about these challenges. Not as separate problems requiring separate solutions, but as interconnected performance elements that must work in concert.

Precision: The Invisible Foundation

Watch a trapeze artist prepare for their act and you'll notice something remarkable: most of their work happens before they touch the trapeze. They check equipment tensions, calculate swing trajectories, and run through timing sequences with metronomic repetition. The spectacular catch that audiences applaud represents the culmination of invisible precision work.

Research operations demand similar foundational rigor, yet many organizations treat methodology as bureaucratic overhead rather than performance infrastructure. The consequences compound over time.

Analysis of research project timelines across 50 enterprise organizations reveals a consistent pattern: teams that invest upfront in operational precision complete projects 40% faster than those that rush into execution. More significantly, their insights influence decisions at nearly twice the rate. The correlation isn't coincidental. Precision in research design, sampling methodology, and analysis frameworks creates the conditions for insights to land with impact.

But precision in research operations looks different than in other business functions. It's not about rigid process adherence or standardization for its own sake. Rather, it's about building repeatable excellence into the aspects of research that enable speed and reliability when they matter most.

Consider sample design. In traditional research operations, each new project requires custom sample planning—determining size, composition, recruitment approach, and qualification criteria. This bespoke approach might seem rigorous, but it introduces decision fatigue and variability. Some studies are over-sampled, wasting budget. Others under-sample, undermining confidence. Sample composition varies based on whoever designed that particular study.

Organizations operating with circus-level precision instead develop sample design frameworks that codify best practices while remaining flexible for unique research questions. They establish clear decision rules: for exploratory research, these are the sample parameters; for validation studies, these apply; for tracking research, use these standards. When exceptions are needed, the framework makes the trade-offs explicit rather than intuitive.

The time savings are significant—reducing study design from days to hours—but the real value lies in research quality. When sample design follows proven frameworks rather than improvisation, every study benefits from accumulated learning about what works. Teams can focus creative energy on research questions and conversation design rather than reinventing sampling approaches for each project.

This principle extends across research operations. Interview guide development, analysis frameworks, synthesis methodologies—each represents an opportunity to build precision through deliberate systems rather than relying on individual expertise to recreate quality with each execution.

The psychology research on expert performance supports this approach. Anders Ericsson's work on deliberate practice demonstrates that expertise develops not through general experience but through purposeful repetition of specific skills with systematic feedback. Circus performers embody this principle—they don't simply practice their acts, they isolate individual components and refine them separately before integrating them into performances.

Research operations can adopt the same methodology. Rather than running studies end-to-end and hoping quality emerges, organizations can systematize the specific craft elements that determine research excellence: question sequencing that builds rapport before probing sensitive topics, probing techniques that ladder from surface responses to underlying motivations, synthesis frameworks that surface patterns while honoring individual variation.

When these elements become repeatable practice rather than individual improvisation, research quality becomes systematically achievable rather than occasionally excellent.

Ensemble Performance: Research as Collaborative Act

The soloist might capture headlines, but circus performances succeed through ensemble coordination. The aerialist's spectacular catch depends on the catcher's precise timing, which depends on the ground crew's equipment preparation, which depends on the lighting designer's visibility planning. Each performer must master their individual craft while synchronizing with the broader production.

Research organizations struggle with this collaborative architecture. Despite everyone agreeing that cross-functional insight development produces better outcomes, most research still operates through a relay model: researchers conduct interviews, analysts synthesize findings, strategists develop recommendations, designers create presentations. Each function executes their portion sequentially, passing work forward with limited feedback loops.

The inefficiency is measurable. Gartner's analysis of insight development workflows found that sequential handoffs increase time-to-insight by an average of 65% compared to concurrent collaboration models. Quality suffers too—each handoff introduces interpretation drift as findings get translated through different functional lenses without the context that informed earlier work.

But the deeper problem is opportunity cost. Sequential research operations optimize for functional clarity at the expense of emergent insight. When researchers interview customers without product context, they miss opportunities to probe on technical trade-offs that would inform development decisions. When strategists synthesize findings without having heard raw customer conversations, they may miss nuance that would reshape recommendations. When designers create presentations without understanding the stakeholder dynamics the research needs to address, they optimize for aesthetics rather than persuasion.

Circus ensembles avoid this fragmentation through carefully choreographed collaboration. Performers don't simply execute individual components in sequence—they train together, develop shared timing intuition, and adjust dynamically based on real-time cues from other ensemble members.

Research operations can adopt similar collaborative architectures. Rather than researchers owning interview execution while other functions wait for synthesized findings, cross-functional teams can engage throughout the research cycle.

This doesn't mean everyone attends every interview—that creates coordination overhead without value. Instead, it means building collaboration points where functional perspectives can shape research in real-time:

Product managers participate in conversation guide development, ensuring research explores the technical and market context that informs their decisions. This upfront involvement might add two hours to study design, but it saves weeks of iteration when findings need additional validation to answer the questions that really mattered.

Data analysts review early interview transcripts before synthesis begins, identifying patterns that warrant quantitative follow-up or suggesting analytical frameworks that would maximize insight extraction. Their early engagement prevents the common pattern where qualitative research surfaces intriguing patterns that can't be validated because the necessary quantitative data wasn't collected.

Designers join synthesis sessions rather than receiving finished findings, enabling them to observe how insights emerged and understand the confidence levels behind different conclusions. This participation creates presentations that emphasize the insights with the strongest evidence rather than treating all findings as equally valid.

The MIT Sloan research on team performance provides useful framing here. Their work on collective intelligence demonstrates that team performance depends less on individual member capabilities and more on communication patterns and collaborative turn-taking. High-performing teams show distinctive interaction patterns: frequent short contributions rather than long monologues, even distribution of speaking time, and high social sensitivity to other members' reactions.

Research ensembles can deliberately cultivate these patterns. Rather than one-hour synthesis meetings where researchers present findings while other functions listen, collaborative research operations create working sessions where different perspectives contribute actively. The researcher might start by highlighting key interview moments, but product managers chime in with market context that reframes the significance, while strategists connect patterns to broader business dynamics.

This ensemble approach requires letting go of functional ownership in ways that make many research leaders uncomfortable. When synthesis becomes collaborative, researchers can't control the narrative as tightly. Findings might get challenged or reinterpreted through different functional lenses. The clean story researchers might prefer becomes messier through multiple perspectives.

But this productive messiness is precisely what creates insights that drive decisions. When cross-functional teams shape research interpretation together, they develop shared ownership of conclusions and collective commitment to implications. The research doesn't need to persuade skeptical stakeholders later—they were part of developing the insights from the start.

Spectacle: Making Insights Unmissable

The most common complaint from insights professionals isn't about methodology or analysis—it's about impact. "We deliver great research that doesn't get used." The frustration is palpable and justified. Organizations invest significant resources in understanding customers, then make strategic decisions based on executive intuition or internal consensus rather than research findings.

The standard explanation blames organizational culture or stakeholder sophistication. If only executives valued data more, if only product teams were more customer-centric, if only there was more budget for research... these cultural critiques may be true, but they're not actionable. Insights teams can't transform company culture. They can, however, make their findings impossible to ignore.

This is where Fisher's circus framework becomes most provocative. Spectacle isn't frivolous or manipulative—it's essential craft. Circus performances don't rely on audiences' intrinsic interest in acrobatics. They engineer attention through staging, timing, and dramatic tension. The research equivalent isn't flashy slides or entertaining anecdotes. It's deliberately designing insight delivery for maximum stakeholder impact.

Consider how research findings typically get presented. After weeks of interviewing and analysis, insights teams schedule presentation meetings with stakeholders. They create slide decks summarizing key findings, supported by representative quotes and thematic analysis. The presentation walks through research objectives, methodology, findings, and recommendations. Stakeholders nod politely, ask a few questions, thank the research team, and... nothing changes.

The problem isn't content quality—the insights are often solid. The problem is delivery architecture. Research presentations compete with every other meeting, email, and priority demanding stakeholder attention. Without deliberate spectacle, insights blend into the background noise of organizational communication.

Circus performances offer a different model. They don't present acts sequentially with equal weight. Instead, they architect the entire experience around peak moments—the most spectacular tricks, the highest tension points, the most surprising reveals. Supporting acts build toward these peaks, creating narrative momentum that carries audiences through the full performance.

Research insight delivery can adopt similar architecture. Rather than presenting findings with academic evenhandedness, insights teams can identify the single most surprising, challenging, or opportunity-rich finding and structure the entire narrative around that peak moment.

This requires discipline that feels counterintuitive to researchers trained in balanced reporting. The instinct is to present all findings comprehensively, giving stakeholders the full picture to draw their own conclusions. But comprehensive presentations diffuse impact. When everything matters equally, nothing matters particularly.

Research from the Heath brothers' work on idea stickiness provides useful guidance here. Their analysis of memorable communications identified six principles: simplicity, unexpectedness, concreteness, credibility, emotion, and stories. Research presentations typically excel at credibility—methodology is sound, sample sizes are appropriate, analysis is rigorous. But they often fail the other five principles by prioritizing comprehensiveness over impact.

Spectacle-minded research delivery inverts these priorities. It identifies the single most unexpected finding—the insight that challenges stakeholder assumptions or reveals hidden opportunity. It makes that finding concrete through specific customer stories and vivid details rather than thematic summaries. It connects findings to emotional stakes—the frustrated customers about to churn, the delighted users becoming evangelists. And it structures insights as narrative rather than categorical findings.

This approach doesn't mean sacrificing rigor or manipulating findings. It means recognizing that insight impact depends on stakeholder attention, and attention depends on deliberate delivery design.

Some research leaders resist this framing as pandering or "dumbing down" sophisticated analysis. The circus metaphor helps reframe the concern. When Cirque du Soleil designs a performance, they don't simplify acrobatic technique—they showcase elite athleticism through staging that makes the difficulty visible and the achievement undeniable. The spectacle serves the craft rather than replacing it.

Research spectacle operates similarly. The goal isn't to hide complexity or oversimplify findings—it's to make rigorous insights impossible for stakeholders to dismiss or forget. This might mean leading with a provocative customer quote that encapsulates a key finding, then unpacking the broader pattern it represents. Or structuring presentations around a customer journey that surfaces friction points and opportunity moments with dramatic specificity. Or creating video highlight reels that show actual customer reactions rather than summarizing sentiment in bullet points.

The economics of attention support this approach. Herbert Simon observed that in information-rich environments, attention becomes the scarce resource. Organizations don't lack insights—they lack the attentional capacity to process and act on all available information. Research that fails to compete for attention effectively doesn't fail because the insights lack value. It fails because it's optimized for comprehensiveness rather than impact.

This realization requires research leaders to develop new skills beyond traditional methodology and analysis capabilities. Insight teams need to understand narrative structure, visual storytelling, and persuasive presentation in the same way circus producers understand theatrical staging. These aren't peripheral communication skills—they're core capabilities that determine whether research influences decisions or disappears into documentation archives.

Integration: When the Elements Come Together

The circus mindset's real power emerges when precision, ensemble performance, and spectacle work in concert. Each element reinforces the others, creating research operations that deliver insights with speed, quality, and impact that would be impossible through any single focus.

Consider how these elements interact in practice:

Operational precision creates the foundation for ensemble performance. When research processes are systematized and repeatable, cross-functional collaborators can engage confidently without worrying that their participation will break fragile methodology. Product managers can contribute to study design knowing that research fundamentals are handled. Analysts can suggest alternative synthesis approaches confident that the underlying data collection was rigorous.

Ensemble performance enhances spectacle by ensuring insights address stakeholder questions directly. When cross-functional teams shape research from the start, findings naturally connect to the decisions they need to inform. The research doesn't need to persuade skeptical audiences because the audiences helped generate the insights. The spectacle becomes authentic surprise and discovery rather than persuasive argumentation.

Spectacle creates demand that justifies investing in precision and ensemble coordination. When insights consistently influence decisions and drive business impact, organizations prioritize research operations investment. Leaders approve the time required for rigorous methodology and cross-functional collaboration because they've seen the results. The virtuous cycle compounds.

Research organizations that master this integration don't just deliver insights faster or more efficiently. They fundamentally change how their organizations use customer understanding. Research transforms from a periodic input into strategic planning to a continuous capability that informs daily decisions across functions.

The operational characteristics of these high-performing research functions share consistent patterns:

They maintain systematic research infrastructure that enables speed without sacrificing quality. Conversation guides follow proven frameworks. Sample designs apply established best practices. Analysis uses standardized coding schemes that still allow emergent insight discovery.

They operate through cross-functional pods rather than sequential handoffs. Research teams include standing members from product, marketing, and strategy who engage throughout research cycles rather than at discrete presentation moments.

They optimize insight delivery for stakeholder impact, not researcher preferences. Presentations lead with surprise, use video and concrete stories, and structure narratives around decision implications rather than thematic categories.

And critically, they measure success by decision influence rather than research volume. The question isn't how many studies were conducted or how many customers were interviewed. It's whether the insights shaped product roadmaps, informed marketing strategy, or influenced resource allocation.

The Practice of Research Excellence

Fisher's circus provocation ultimately offers a framework for thinking about research operations as performance craft. Just as circus acts require relentless practice, technical precision, and collaborative coordination to achieve moments of apparent effortlessness, research operations require systematic attention to craft elements that most organizations treat as administrative overhead.

The transformation isn't quick or easy. Building precision into research processes requires confronting comfortable inefficiencies. Shifting to ensemble collaboration means relinquishing functional control and accepting messier synthesis processes. Developing spectacle capabilities requires researchers to master storytelling and presentation skills that weren't part of their training.

But organizations that make these investments don't just improve research efficiency or stakeholder engagement. They build systematic capability for customer understanding that compounds over time. Each research cycle strengthens operational systems, deepens collaborative relationships, and refines insight delivery approaches. The organization doesn't just learn from customer conversations—it learns how to learn from customers more effectively.

This is what Fisher meant by running your business like a circus. Not adopting circus aesthetics or organizational structures, but embracing the circus mindset: relentless attention to craft, ensemble coordination where individual excellence serves collective performance, and deliberate spectacle that makes your work impossible to ignore.

For insights leaders emerging from TMRE 2025, the challenge isn't implementing a new methodology or adopting a new technology platform. It's examining their research operations through this circus lens and asking: Where does our precision fail? Where do handoffs create friction that ensemble collaboration would eliminate? Where do our insights disappear into documentation because we haven't engineered spectacle?

The answers to these questions illuminate the path toward research operations that don't just generate insights—they create organizational conditions where customer understanding drives every decision that matters.

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