What Operating Rooms Can Teach Leaders About Team Design

As companies in all industries adopt new technologies to assist teams, they should keep in mind that the experiences of the team’s members working with each other in the past still matter a lot. A study of surgeries at a mid-sized hospital in Madrid, Spain, reinforced that point and generated other insights into how best to staff teams.

Hospitals have spent years investing in digital tools—dashboards, predictive algorithms, and real-time monitoring systems—to optimize their operating rooms. However, inefficiency persists, duration variability remains high, and performance often differs dramatically from one day to the next or from one team to the next. Our research, based on more than 77,000 surgeries conducted from 2016 to 2019 at HLA Moncloa Hospital, an urban general teaching hospital in Madrid, found that a substantial driver of operating room performance is not technology. It is how teams are designed.

After we conducted our research, the hospital, with our assistance, implemented a pilot initiative involving four surgical services, covering 25% of the total cases. It confirmed our finding.

Three factors consistently explain why some operating rooms run smoothly while others experience difficulties: the number of others that people on the surgical team have previously worked with and how many times they had worked together; how the surgical staff is rotated among teams to promote innovation and help others learn new ways of working; and the composition of individual teams, including elements such as rank and gender balance. When these factors are intentionally designed rather than left to chance, performance tends to improve—often quickly and at minimal cost. Conversely, when these aspects are ignored, even the most advanced tools cannot fix coordination issues.

Although our study focused on hospital operating rooms, its implications extend far beyond healthcare. Many professional environments—from consulting and software development to emergency response and other project-based settings—rely on fluid teams that form and reform under pressure. In these contexts, performance depends not only on individual expertise or formal processes but also on how people combine, coordinate, and adapt in real time.

Why Technology Alone Isn’t Solving the OR Problem

Hospitals have been equipped with highly sophisticated technologies that enhance the measurement of a wide diversity of parameters. But delays are not only measurement problems; they are mostly generated by surgical team coordination. And coordination depends less on software than on how teams are structured and staffed.

A good example of breakthrough technology developed to improve surgical centers’ performance is the so-called operating room black boxes (ORBB). These are systems that use synchronized audio, video, and sensor data to record operating room activity. They offer a more granular view of surgical performance, but they also introduce their own challenges.

For example, early studies of comprehensive OR-recording systems illustrate how sensitive clinicians are to perceived surveillance. A recent nationwide survey in France found that while most clinicians recognized the educational value of ORBB recording systems, large majorities also reported concerns about stress, perceived surveillance, medico-legal exposure, and loss of autonomy. Even among supporters, acceptance was conditional on clear governance rules, explicit consent processes, and safeguards against punitive use.

These responses reflect a broader pattern. When clinicians believe data may be used for scrutiny rather than learning, they instinctively protect themselves and change their behavior (i.e., the Hawthorne effect). The lesson is not technological but organizational. Without deliberate trust-building, clear rules for data use and safeguards against individual blame, even well-designed tools can provoke resistance rather than improvement.

This creates a paradox. Hospitals are more data-rich than ever, yet variability in the operating room remains persistent. Technology often shows where disruptions happen, but it doesn’t automatically explain why they occur or how to prevent them. The main cause of surgical inefficiency is the lack of collaboration and coordination under pressure within surgical teams. Fixing this requires redesigning how teams are formed so that the experience flows smoothly among surgeons, nurses, and other surgical staff.

Our multi-year research involving 77,482 surgeries helps explain why clinical factors account for only part of daily variation. Procedure type, case complexity, diagnosis, patient characteristics, and timing factors, such as the day of the week, all influence outcomes, but they don’t fully explain why some surgeries start and end on time while others don’t.

For this reason, we built a predictive model to forecast surgery duration, incorporating both these predictors and human-factor variables such as team familiarity (the extent to which members of a surgical team have worked together in the past), partner-exposure diversity (the extent to which team members have collaborated with a broad range of colleagues across prior surgeries), gender composition, and cumulative surgeon experience. The accuracy of the model improved significantly with these additions. Conversely, removing these variables greatly reduced accuracy, indicating that the proper drivers of OR performance are team dynamics rather than case clinical labels—standardized categories or tags applied to surgical cases to classify procedures, diagnoses, specialties, risks, and outcomes for operational, billing, research, or analytics purposes.

In short, who works together often matters as much as what they do. This insight has significant implications for hospital leadership: Many organizations are trying to solve a human-coordination problem using the wrong tools: those for measuring processes.

The Limits of Data Without Design

Many hospitals now collect enormous amounts of information on all the stages of surgeries: the preoperative stage (before the surgery), the intraoperative stage (during the surgery), and postoperative stage (after the surgery). It includes timestamps for every step, visual dashboards showing case progress, and analytics platforms that promise to flag inefficiencies. These tools can help diagnose obvious bottlenecks or missed compliance steps. Yet they seldom capture the behavioral drivers that most affect performance: how teams coordinate, anticipate problems, and respond when pressure mounts.

Our own analysis showed that, during the intraoperative phase, two clinically similar procedures can differ by 20 to 40 minutes solely because of the team in the room. Predictive models that ignore team dynamics miss this signal entirely.

What We Learned from a Pilot

HLA Moncloa partnered with us to test a different approach: a team-based redesign grounded in behavioral insights rather than new technology. The aim was simple: improve efficiency without collecting new data or employing new sophisticated technology.

Over six months, the hospital implemented a low-cost redesign of surgical team staffing that produced substantial improvements in OR performance. Led by the hospital’s surgical center management team, the initiative translated our research on team familiarity, partner-exposure diversity, and cumulative surgeon experience into day-to-day staffing decisions, with operational results that closely mirrored the patterns identified in our study.

The results were notable. Turnover time fell from 18 to 12 minutes. On-time starts improved from 85% to 96%. Readmissions declined from 12 to five per 1,000 procedures, and near misses (incidents in which a mistake or unsafe condition occurs during the surgical process but is detected in time to prevent injury to the patient) dropped from two to one per 1,000. These improvements were obtained without purchasing new equipment, increasing overtime, or expanding staffing. The hospital changed how people were paired and scheduled, not the tools they used.

As an example, thanks to the low-cost operational redesign based on our study findings, robotic surgical times, as reported by the robot manufacturer, have been reduced by half in prostate surgery, nephrectomy (the removal or all or part of a kidney, and other procedures.

For an OR, these are not marginal gains. They translate into fewer delays for patients, more predictable days for staff, and better use of existing capacity. And they came from treating the design of the teams as a core operational lever.

From the perspective of Dr. Carlos Zarco, the hospital’s general manager, what mattered most about this initiative was not the sophistication of the analysis but its practicality. The hospital did not need to introduce new technology, hire additional staff, or redesign clinical pathways. It simply changed how teams were formed and how collaboration was structured.

Initially, there was understandable skepticism: Surgeons and nurses worried about losing flexibility or autonomy. But as the weeks passed, the effects became visible on the ground: smoother daily schedules, fewer last-minute disruptions, and a noticeable reduction in stress during complex cases. What impressed Zarco was that performance improved without trade-offs. Patients experienced fewer delays, professionals felt more supported, and the organization gained reliability. “This reinforced a core lesson for me as a leader,” Zarco said. “Many operational problems we label as ‘capacity’ or ‘technology’ issues are design problems—and thoughtful team design is one of the most powerful, yet underused, tools we have.”

Here are some specific takeaways from our project.

1. Design for team familiarity.

Team familiarity—the degree to which team members have shared experience working together—has consistently emerged as one of the strongest predictors of variability in surgery duration in our models. Familiar teams communicate more effectively, anticipate one another’s needs, and maintain flow when confronted with unexpected events such as complex anatomy or equipment glitches.

In the pilot, people were assigned to specific surgeries in a thoughtful, deliberate manner, especially for the most difficult and unpredictable cases. In effect, the hospital started treating familiarity among teammates as valuable and using it where it would have the greatest impact. That said, the staffing approach did not eliminate flexibility. Individual team members, including surgeons, anesthesiologists, and nurses, could still request changes for scheduling conflicts, workload balance, training needs, unexpected absences, or personal circumstances. These requests were handled on a case-by-case basis and did not override the pilot’s core principle of prioritizing team familiarity for the most complex surgeries.

2. Balance experience and exposure diversity.

If familiarity is helpful, why not keep the same teams together all the time? Because excessive stability can limit learning. Periodic exposure to colleagues from different teams allows surgical staff to observe alternative techniques, communication styles, and coordination routines that can improve performance across teams. The goal should not be to create permanent teams but a balance between continuity and selective rotation.

We measured exposure diversity—how much of someone’s work over time was performed with each teammate—by using the Herfindahl–Hirschman Index, a methodology originally developed to quantify market concentration. It helped us assess whether someone’s experience was concentrated with a few teammates or distributed across many. The working relationships of staff whose experience was overly limited to a small set of colleagues were gradually broadened, while those who had been working with too many different teammates were given more continuity. The idea was to build stable cores with flexible peripheries: The surgeon and a few key staff remained consistent, while other roles rotated through a wider set of partnerships.

This calibrated structure allowed teams to develop a shared understanding of how the procedure in question unfolds, each person’s role in it, and how to anticipate potential complications without sacrificing operational flexibility—the ability to adjust schedules and staffing when conditions change. In general surgery, applying this method reduced turnover time by 22%, illustrating how a more intentional rotation policy can improve teams’ ability to adapt and increase efficiency. Instead of relying on exposure diversity, it provides a clearer, more principled basis for staffing decisions than informal preferences and ad hoc swaps.

For leaders, the message is clear: Rotational policies should aim to build resilient, experienced teams capable of functioning smoothly in various conditions, not just to distribute the burden of undesirable shifts or challenging surgical cases.

3. Gender diversity matters.

While hospitals routinely track clinical and scheduling variables, team composition factors such as gender mix are rarely incorporated into performance models. But observational studies analyzing real-time team interactions in the operating room found that gender-balanced teams exhibit fewer conflict-driven behaviors, more affiliative exchanges, and more consistent cooperation. Conflicts are disproportionately initiated within same-gender groups, especially among men, where status dynamics and intrasexual competition can intensify disruptions and undermine teaching.

Mixed-gender teams, particularly those balanced across hierarchical levels, demonstrate smoother teaching interactions and more effective cross-role communication. Senior surgeons receive more questions rather than silent compliance, junior staff speak up earlier, and disagreements are less likely to escalate into open conflict. These patterns directly shape how quickly a team can resolve ambiguity, reconfigure when something goes wrong, or adopt a safer alternative mid-procedure.

In our own work, even small adjustments produced operational benefits. In ophthalmology, for instance, improving gender balance in scrub-nurse assignments reduced the duration of cataract procedures by 9% within eight weeks.

For hospital leaders, this means that diversity efforts should explicitly include the composition of surgical teams. When building OR schedules, gender mix is not just a compliance variable; it is a contributor to performance.

Managing Resistance

As with any operational redesign, resistance emerges. At HLA Moncloa, surgeons feared losing autonomy over who supported them in the OR; they were concerned that a familiarity-based template might limit their influence over staffing decisions. Other staff worried that a more structured model would restrict their ability to swap shifts, making it harder to accommodate their personal needs.

These are legitimate concerns. They touch on control, identity, and work-life balance—all sensitive issues in a high-stress environment like the OR.

The hospital addressed them through three practices:

Make staffing criteria transparent.

People should understand how decisions are made and see that the rules are applied consistently.

Place caps on consecutive assignments.

Set a limit on how many times the same individuals or the same team can be scheduled to work together in succession. The purpose is to avoid the perception of favoritism or “closed circles.”

Redesign surgical teams’ staffing through collaborative cycles.

Clinicians should be given opportunities to propose adjustments, which should then be tested and incorporated if they improve both performance and perceived fairness.

HLA Moncloa’s leaders observed that as surgical schedules became more predictable across days, staff concerns diminished, and confidence in the new team assignment approach increased. The benefits of the new model soon became clear. Surgeons noticed that operations started on time more consistently and that the daily sequence of surgeries ran with fewer delays and interruptions, making it easier to complete the procedures they had planned for the day. Nurses noticed that the new approach reduced the number of crises and the severity or complexity of cases, making their days less tiring.

The lesson is like what other systems have found when implementing checklists or standardized protocols: Resistance is highest when changes are perceived as externally imposed and non-negotiable. It declines when frontline professionals can see both the logic and the benefits of the new design.

Where This Model Works and Where It Doesn’t

A human-factor-centered model is most effective in medium and large hospitals with predominantly elective caseloads and stable rosters. These environments provide the continuity necessary for familiarity and balanced exposure, and they offer enough volume to realize the benefits of better team design. Subspecialty units with high volumes of similar procedures are particularly strong candidates.

The model is less effective in places where staffing constraints make it hard to keep people working with the same teammates. They include small hospitals with limited staffing depth, trauma-heavy services where unpredictability prevents consistent pairing of clinical staff, and units that rely heavily on temporary personnel.

A Practical Playbook

Implementing this approach requires at least one year of staffing data, a designated operating-room-governance lead such as a clinical or operations leader responsible for overseeing OR scheduling policies and coordinating decisions across surgical departments, and leaders willing to maintain stable team assignments while retaining the ability to make staffing decisions when necessary. Without these minimum prerequisites, attempts to redesign teams may falter or provoke more resistance than improvement.

A practical starting point is to use existing data on staffing and cases to map patterns of team familiarity and exposure diversity and highlight where collaboration is either overly stable or excessively fragmented. A set of metrics that we developed and tested can help perform this task.

With this baseline established, leaders can reorganize rosters to stabilize core teams for complex procedures and expand supporting staff’s experience by fostering collaboration. As new patterns emerge, you can include gender-balance considerations and implement measures to create a psychologically safe OR environment—where everyone feels comfortable speaking up and sharing concerns.

. . .

Many hospitals attempt to solve coordination challenges with increasingly sophisticated technology. Our research and field experience suggest that team structure, not technology, is the most powerful lever for improving OR performance. By redesigning how people collaborate, hospitals can achieve meaningful improvements quickly and at minimal cost. Technology can and should support progress. But thoughtful team design is what drives it.

Copyright 2026 Harvard Business School Publishing Corporation. Distributed by The New York Times Syndicate.

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