The Accidental Operator

Last month, we wrote about why operational roles matter more in biotech than people think. The response was fantastic – it clearly struck a chord within the bio community. So we wanted to dig deeper into how biotechs can nurture these critical roles. But to do that, we need to first understand how these roles are typically being filled today.

Scientist turned operator/PM

We’ve seen repeatedly that many of the most capable operations leaders in biotech didn't start in operations. They were scientists, research associates, or analysts who happened to be organized, showed initiative, and filled gaps that nobody else noticed (or cared to address). These were the people who created the first project tracker when timelines got confusing. Who stepped up to manage the CRO when the relationship was faltering. Who built the first budget template when spending started to accelerate. We’ve even come across people who optimized the placement and layout of lab equipment to help with smooth flow and more efficient scientific operations.

They weren't hired for "ops." They didn't have operations-focused titles. But without them, their companies would have stalled.

We call these people "accidental operators" – and biotech is full of them. The problem is that too many companies stumble into this talent instead of intentionally developing it (especially scientific PMs, which we made a strong case for the other week). This oversight costs precious time, runway, and momentum at the stages when biotechs can least afford it.

Look around and you’ll find them

The pattern typically unfolds like this: someone starts in a technical role, and because they're organized, proactive, and team-oriented, they begin picking up operational responsibilities. Before long, they're coordinating timelines, facilitating decisions across teams, managing vendor relationships, and tracking budgets.

Over time, they're essentially doing the work of a program manager – but without the formal recognition, mentorship, or tools. They've become indispensable, solving problems that nobody else is tackling. Yet they often operate in a strange limbo – performing critical functions without official mandate or support.

Look around any biotech, and you'll find them. The research associate who created the vendor management system that everyone now relies on. The scientist who somehow ended up coordinating three cross-functional projects. The analyst who built the company's first milestone tracking Excel.

These accidental operators are critical, but many feel invisible or unsupported. Their career paths are unclear. Their impact is felt but rarely measured. And they're often pulled between their 'real job' and the operational work that has become increasingly vital to the company.

“Science first, sanity later” 

The root of this issue is straightforward: early-stage biotechs prioritize scientific talent. When resources are limited, founders naturally focus on the core science – the technology, platform, or therapeutic approach that represents the company's value proposition. Operations is viewed as overhead, something to add "later" when the team is larger.

There's also a subtle cultural bias at work. In an industry built on scientific innovation, operational roles are often seen as "non-core" – despite the fact that they directly determine how efficiently a company uses its runway and how quickly it reaches critical milestones (or whether it even lives long enough to do so).

Many founders simply don't know what good operations leadership looks like early on. They might assume it's too soon to bring in dedicated operational talent, or they don't understand how these roles should evolve as the company grows, or how to best support them once they exist.

Because of these factors, operational talent is often grown accidentally rather than intentionally – emerging organically from within rather than being deliberately cultivated.

The cost of waiting

When biotechs wait too long to formalize operational roles, they fall into predictable traps. Scientists end up burning out as they try to juggle bench work and coordination responsibilities. Project timelines become fuzzy, and decision-making processes remain undocumented and existentially slow. The people doing essential operational work aren't properly empowered or supported, leading to inconsistent execution or even departure of valuable talent.

The result is a dangerous mix of inefficiency, preventable delays, and poor communication – precisely when precision and speed matter most. A company might have brilliant science but struggle to translate it into consistent progress because the operational muscle hasn't been developed.

What's particularly frustrating is that these problems compound. Early operational inefficiencies create technical debt that becomes increasingly difficult to address as the organization grows. Patterns set in the first year or two often persist long after they should have been replaced with more robust approaches.

What to do instead

Biotechs can take a more intentional approach to operations from the beginning. Here are practical steps that even the earliest-stage companies can implement:

Look internally: Identify people already performing informal operational work and offer them training, mentorship, or a path to formal leadership. These accidental operators have already demonstrated both aptitude and interest – they just need support to grow.

• Tip: While it may be tempting to post an external role or bring on an external consultant for a project, it’s worth first looking internally. If there’s someone with a good fit already within your team, that means they already have a lot of critical context. 

Don't wait for scale: Even a 10-person company needs someone thinking about timelines, budgets, and vendor coordination. These functions don't magically appear when you hit 50 people – they need to be built incrementally from the start.

• Tip: If you’re already larger than this, avoid sunk cost fallacy. Remember: the best time to plant a tree was 20 years ago; the second best time is now.

Create pathways: Build internal programs for transitioning high-potential scientists or team leads into program management roles. This might include training, mentorship from advisors with operational experience, or partial role transitions that allow people to test their fit.

• Tip: If there's a strong fit, consider decisively changing their title/role so that they can allocate proper bandwidth to solving operational challenges. PMing complex R&D projects is not a part time job.

Equip for success: Allocate appropriate budget for the tools that these leaders need to excel, and support them in implementing the processes to properly leverage these tools. Couple this by giving them enough decision-making authority to show trust and remove unnecessary blockers.

• Tip: It can be very damaging (both for the person and for the org) when the scientific PM has identified a solution they strongly believe will help, and they’re met with "No’s" or a lack of proper consideration. PMing is more than just doing busy work – it’s about being thoughtful about what you pick and how you implement change.

Signal value: Treat operations as a strategic function – not just support. Celebrate executional wins as much as scientific milestones. Make operational excellence part of your company's identity from day one, and, when you find your superstars, create opportunities for advancement and promotion in the org.

• Tip: In all-hands meetings, make it a habit to shout out operational wins, or even operational challenges being worked through. This helps normalize Ops as a core part of progress, not just behind-the-scenes support. Over time, it shifts the team’s culture to value the how, not just the what.

Companies that build their operational culture early - by intentionally identifying and developing talent - gain a competitive advantage that compounds over time. They make faster, more informed decisions. They execute with more discipline. They scale without the chaos that often accompanies rapid growth.

Most importantly, they send a powerful message: in this company, execution matters just as much as innovation. And without the former, the latter will not reach the patients who need the innovation the most.

Kaleidoscope is a software platform for biotechs to robustly manage their R&D operations. With Kaleidoscope, teams can plan, monitor, and de-risk their programs with confidence, ensuring that they hit key milestones on time and on budget. By connecting projects, critical decisions, and underlying data in one spot, Kaleidoscope enables biotech start-ups to save months each year in their path to market.