Team Health as a Performance System, Not a Wellness Program

01 /The Concept

Quan's premise is simple: company performance is a function of team health. When teams feel cohesive, motivated, and not burned out, performance follows. When they don't, it doesn't.

"Team health" has traditionally been treated as a psychological problem – addressed with therapists, meditation apps, motivational workshops, and reflection exercises. Quan argues that's only half the picture. If a company wants to improve performance, it needs to actually work on performance – which means setting sensible quarterly goals and establishing working procedures that help teams hit them.

The conventional fix for underperforming teams is more management: more oversight, more check-ins, more people monitoring team "health." Quan rejects this. Teams, it argues, can self-optimize without external supervision – provided they have the right platform to do it with.

Quan's core idea: the most reliable route to team effectiveness is building healthy habits – or, as the company calls them, "rituals." These are structured work practices that teams adopt deliberately at first, and eventually follow automatically.

The platform runs quarterly surveys across all team members, gathering input across five dimensions: emotional state, physical wellbeing, quality of connections with colleagues, sense of purpose in the work, and feeling of personal fulfillment.

Based on results, the platform surfaces recommendations about which aspects of collaboration the team should focus on. Survey results are fully confidential – no individual answers are visible to managers or teammates, only anonymized and aggregated data. That makes it possible for employees to respond honestly.

The surveys themselves are light: once a quarter, ten minutes per person.

In addition to individual recommendations, each team receives a suggested set of rituals from Quan's catalog – a library of best-practice collaboration patterns assembled from across the platform's user base. Which rituals get recommended depends on what the team's survey data reveals.

One client, for instance, used the platform to navigate a smooth transition to hybrid work – balancing remote days with periodic in-office time – without the friction that typically accompanies such shifts.

Quan is based in the Netherlands. It launched its beta in spring 2021, went through Y Combinator in winter 2022, and graduated with $1.2M in funding and its first 12 enterprise clients. It has now raised a new $2.82M round.

02 /Why It Matters

In modern organizations, performance is increasingly determined at the team level, not the individual level. Yet most companies still run individual performance reviews as their primary evaluation mechanism – a holdover from a model that's no longer how knowledge work actually functions.

Confirm, which has raised $11.4M and was [covered here](/review/rezultat-prinosit-ne-sotrudnik-a-komanda) in fall 2023, addresses exactly this gap. Rather than relying solely on formal org chart teams, Confirm's platform maps the informal network of actual working relationships – who collaborates with whom, how often, and how effectively – then surveys along those real connections instead of the org chart ones.

This echoes the central insight of *Moneyball*: that team outcomes can be optimized through data and smart process design rather than by assembling star talent. The Oakland A's built a winning team not by acquiring the best individual players, but by understanding the system well enough to deploy average players in the right positions.

Both Confirm and Quan operate in that spirit – treating the team as the unit of analysis, not the individual.

Quan's specific bet within that frame is that the most durable path to better team performance is habit formation. Once a practice becomes routine, it stops requiring motivation or self-discipline – it just happens. Consider fitness: the people who exercise consistently aren't usually the most motivated, they're the ones who scheduled the gym into their lives until it became automatic. Motivation fades; habits don't.

Rhythms, [covered in December](/review/a-v-takom-ritme-mozhno-bolshe-zarabotat), is building along similar lines – and raised $26M even before launching its product. Its framing is the "rhythm" of how a team works: its AI analyzes patterns of high-performing teams, identifies what distinguishes their working cadence, and recommends those patterns to other teams that are underperforming.

The difference: Quan relies on a curated library of rituals, while Rhythms aims to discover effective patterns automatically from behavioral data. But the underlying thesis – that team effectiveness is a function of repeatable, internalized practices – is the same.

03 /Opportunities

Two distinct product opportunities emerge from this space.

Team-level performance analysis is the less-explored ground. Almost every tool in the market is still built around individual reviews. Building for the team as the unit of analysis is a largely open field with real demand from both companies and investors.

Adjacent to that is the ritual and cadence layer – platforms for identifying and embedding productive working practices at the team level. Call them rituals, habits, or rhythms; the underlying mechanism is the same.

Both areas are early enough that there's genuine room for experimentation and differentiation. The category is attracting interest on both the enterprise and investor side, which means the ground is being broken but the space isn't yet crowded. The entry angle with the clearest moat is proprietary behavioral data: the platform that accumulates the most evidence about which team practices actually correlate with performance outcomes will be hard to replicate.