How well do you know your own biotech company?

Running a biotech means managing a complex engine of people and IP. Despite this complexity, the most successful industry leaders we've met have a sharp understanding of how that engine is operating – people, teams, costs, and investments worth making. As always, if anything here resonates, please reach out!

A couple of weeks ago, we sat down with Carina on the Building Biotechs podcast (link here if you want to listen!) to talk about building lean biotech companies. One theme kept popping up: operational inefficiencies. In many ways, they’re the silent killers of companies that should’ve had a shot. We spend a lot of time worrying about failed experiments or dried-up funding, but we don’t talk enough about operational bloat, which is just as dangerous.

In business, every dollar spent should be a calculated investment. Within the biopharma space, we’ve lost count of how many times we’ve seen companies hemorrhage resources on redundant processes, poorly managed outsourcing, or experiments that drag on without clear endpoints. More often than not, this happens when there’s a lack of detailed knowledge at the top of the company. 

Take financial knowledge, for example. The sharpest people we’ve met – whether they’re CEOs, COOs, SVPs – have an almost preternatural ability to map out costs in real-time. Effective leaders can quantify every aspect of their operations and can run simulations, like how much it costs to hire a new employee, run 1.5 months of R&D, or train a new hire. They’re really good at turning these moving parts into concrete numbers and can simulate the impact of different decisions on their future operations.

We recently talked with a biotech executive who broke down what would happen if his team got to the clinic six months faster: “That would give us six more months of patent life, which means six more months of exclusive sales once the drug hits the market—about $X00M in additional revenue in our market.” He could take a potential scenario from early stage R&D, that came up off-the-cuff, and map the savings from it today to a precise bump in revenue tomorrow, on the spot.

We’re discovering that this level of knowledge is the difference between companies that shoot in the dark and companies that take calculated moonshots. When you know exactly how much each experiment costs, how long it should take, and what outcomes justify continued investment, you create an environment where risks can be taken intelligently. 

Financial knowledge is just one piece of the puzzle here. One of the most pernicious forms of operational inefficiency in biotech is what we call "data drift." It's the slow, almost imperceptible loss of critical information that occurs when experiments are poorly documented, when communication between teams breaks down, or when key insights get buried in a sea of noise. In a well-run biotech, data drift shouldn’t happen. Simply put, you can’t afford to have experiments running and not know about their status, or not know whether your CRO is hitting their deliverables on time (or even sending you the data you asked for, to the specifications you wanted). We’ve even met companies that have been running multiple experiments, unaware they already have enough data to prioritize one of their candidates and focus resources accordingly.

To be fair, as Carina pointed out in our conversation, there’s a lot going on in biotech companies. There is so much data being generated across multiple experiments on several drug candidates, that it’s not easy to build a detailed knowledge base when the data that knowledge is based on feels like it’s always changing. Add in the pressure to hit milestones and “de-risk” your company, and it’s tempting to just push forward.

This pressure to move quickly can lead to a flurry of action without proper coordination or direction. Teams launch experiments without clear oversight, data gets lost in the shuffle, and timelines slip through the cracks. One team misses a handoff, another delays an experiment because the CRO wasn’t looped in on new data.. This chaotic motion creates an illusion of speed, but in reality, it's more like running on a treadmill—lots of energy expended, but no real movement forward. By the time leadership realizes the disconnect, valuable time and resources have already disappeared. 

The good news is, if you’re in an executive or leadership position, you don’t need to know every little detail. What you do need are guardrails to make sure you have the right knowledge to keep your company moving forward in confidence. For example, the way we tackle this in Kaleidoscope is through dashboards that let users set up stage gates for each program. We make it really easy to encode rules where possible, allowing you to easily specify which experiments matter for each stage gate and what values are important within those experiments. When data comes in for an asset and meets the defined criteria, you'll see it clearly on the dashboard and receive a notification, before next steps are automatically triggered (e.g. kicking off the next experiment). This makes it simple to visually track progress and stay informed about assets meeting key milestones, without getting bogged down in unnecessary details.

Ultimately, knowledge is the best weapon you have against inefficiencies. You can’t fix what you don’t see, and inefficiencies have a way of quietly adding up. What starts as a few extra hours here and there turns into months of lost time over the course of a year, and years over the course of an end-to-end R&D project. Leaders who understand the full scope of their operations can spot inefficiencies early and make smarter decisions daily. The compounding effect of those small, informed choices isn’t just about saving time or money—it’s about building a company that runs lean and fast enough to keep pace with its ambitions.

If you want to chat more about anything we wrote, or you’re interested in finding a way to work together, let us know!