Science-Based Business Plan Development

Scientists studying a complex phenomenon don't start with experiments or even hypotheses. They first build a model. They use this model to run simulations and predict what they think will happen. They then run experiments to test the predictive accuracy of their model. If they get a different result than expected, i.e., the experiment invalidates their model, they update it and try again. This is the essence of the scientific method, which can readily be adapted into an equivalent entrepreneurial method: Model - Prioritize - Test 1. When faced with a new idea, we start with a business model describing how we intend to create, deliver, and capture customer value. 2. We then prioritize the riskiest assumptions in the model and make some predictions, which 3. We then attempt to validate through small and fast experiments. Like scientists, we attempt to learn why our predictions fail. Then use those insights to update our model and try again. Model-Prioritize-Test is how you navigate uncertainty in the new world. The Model-Prioritize-Test flywheel powers #ContinuousInnovation.

Tough pill to swallow as scientist at an early-stage biotech startup: If you don’t make the science work, on time & on budget, the company will die. Here’s a tried & tested framework for dealing with that 👇 Science at early-stage startups is 🧪 Fast-moving 🧪 Ever-changing 🧪 And first and foremost……outcomes-oriented! If you’ve spent your entire career to date in academia, this may feel unsettling at first. Here’s a framework for navigating outcomes-oriented science: 1️⃣ Zoom out. Get clear on the scientific & business outcome the startup needs to get to profitability. Focus on identifying unnecessary assumptions are constraining you - even if it’s an assumption your manager or CEO made! Example: You need a cell-line with particular characteristics to produce antibodies, which you will sell. Assumptions: 🧪We should make this cell line in house (should we make an off-the-shelf purchase instead?) 🧪The antibodies should be produced via cell line (is another system possible?) 2️⃣ Break the problem into its scientific/business parts. Example: What needs to be true about this cell line? It needs to grow quickly, cheaply, scale in some way, and have an optimized ability to produce antibodies. First principles thinking is key here! Biologists can take a lot from the engineering playbook. 3️⃣ Parallelize a few strategies to achieve this outcome. Consider: How can you ensure these strategies fundamentally de-risk each other? How can you try to solve the problem from multiple angles such at least one might yield the necessary outcome on time? Example strategies to parallelize: 🧪Purchase several cell lines which produce antibodies well. 🧪Chose 3 x potential in-house cell lines which are derived from very different sources. Optimize for reduced costs, quicker doubling times, and scale. 🧪Throw a small amount of resources at a long-shot technique which uses a microbial system to produce antibodies 4️⃣ Monitor progress regularly and cull projects as needed. Example: After 1 month, the microbial system is yielding surprisingly good results. 24 hours later, all cell line work is de-prioritized and the system starts again, zoomed in on microbials _________ Personally, I think that the startup model of science is exhilarating - it gets pretty addicting to see how much tangible impact you can make in a matter of months, rather than years!

Change methodology for nature-positive aligned business models 🌎 Transforming a business model to align with nature-positive principles is a significant yet essential undertaking for any organization aiming to contribute meaningfully to environmental goals. A structured approach is critical, moving from a high-level strategy to a transition plan that brings sustainability commitments to life in a measurable and accountable way. A nature strategy outlines broad ambitions and science-based targets, setting a vision for positive impact. However, without concrete operational steps, even the most robust strategy may remain aspirational. This is where a nature transition plan becomes essential, providing a detailed framework to embed sustainability throughout a business model. Using frameworks like the CISL Business Transformation Framework and tools such as the Natural Capital Protocol, transition plans ensure actionable steps toward tangible outcomes. An effective change methodology begins with a commitment to a clear, nature-positive vision. The first step involves assessing current environmental impacts through baseline measurements, such as Life Cycle Assessments. This approach provides insights into dependencies on natural resources, setting a foundation for data-driven decisions that drive nature-positive transformation. Establishing measurable targets aligned with science-based standards is the next critical step. Targets should encompass key areas across the business and value chain, aiming to minimize harm while maximizing positive environmental contributions. For established companies, this process may start with pilot projects that can be tested and refined before being scaled across the organization. For start-ups, integrating nature-positive practices from inception can enhance value propositions and align products and services with sustainable principles from the outset. Regardless of business maturity, fostering a culture of continuous improvement and transparency ensures that sustainability remains at the core of all operations. Long-term success in nature-positive transformation depends on adaptability to shifting environmental landscapes, data-driven monitoring, and strategic partnerships. A well-defined transition plan enables steady progress, ensuring that businesses can meet ambitious goals and contribute effectively to a sustainable future. Source: Cambridge Institute for Sustainability Leadership #sustainability #sustainable #business #esg #climatechange #climateaction #nature

Techno-Economic Analyses for Dummies I mean, I wish there was a book like this. The threat of tariffs is shaking up how we approach techno-economic analyses (TEAs) these days. From CAPEX, OPEX, and supply chains, businesses are scrambling to adjust assumptions and asking me how. It's hard to answer as global supply chains are messier and forcing companies to choose between local production and other resilience strategies. Regardless, I've found that if your tech is game-changing, your TEA should prove it, and make it easy for others to believe it too. Here are some tips I've found over the years: 🔧 Manufacturing diagram comparison Please include side-by-side process flow diagrams: one showing your tech, the other a standard process. Highlight where your approach wins—on cost, labor, IP, or efficiency. 📌 Annotate your diagrams and Excel cells Add short, clear descriptions for each process step or component. Don't assume your audience knows the jargon, acronyms, or process steps—make your innovation digestible. 🤲🏼 Source transparency List the source of every key input—is it from internal R&D results? academic papers? industry benchmarks? recent RFPs provided by a supplier? The more transparent the model = the more credible the model. Recommended Guides & Templates ⤵️ 📘 Zero Carbon Capital's Guide to TEA: Quick-start guide for founders to understand TEAs and how to structure them effectively. 📘 U.S. Department of Energy (DOE) TEA Series: Tutorials, videos, and spreadsheet tools like TECHTEST, which provide a solid grounding for building a full TEA. 📘 Activate’s "Techonomics" Series: Videos and templates that simplify TEA for science-based startups. Includes a whitepaper to help integrate TEA into strategy. 🎧 Catalyst Podcast: TEA Pitfalls -> Great breakdown of what not to do in a TEA—bad assumptions, irrelevant metrics, modeling theater. 📘 Planet A Ventures’s TEA Best Practices: I love their step-by-step guide for getting your TEA investor-ready. Includes cost levers, price parity planning, and modeling advice. Data Tools 🗃️ AssessCCUS Equipment Cost Database: A vetted CAPEX cost library—use it to build realistic projections without reinventing the wheel. 📈 NREL LCOE Calculator & CREST Tools: Use these free tools to sanity-check your cost assumptions and simulate energy project cash flows. Companies That Can Help You Build or Review a TEA 🧪 BioRaptor: AI-powered bioprocess data engine that helps optimize experiments and generate better TEA inputs. 🧪 LEC Partners: Global network of bioeconomy experts—great teams for building everything from SAF, fermentation, plant cell culture, and molecular farming TEAs to full commercial and feasibility studies. 🧪 Synonym: Makers of Scaler, a free tool to model fermentation production at scale. They also offer custom TEA services for startups and investors. 🙋♀️ Oh ya, and then there's me. Feel free to have me check over your TEA before sending it off.

Most entrepreneurs are still stuck in the old way of thinking: 1. Come up with an idea 2. Build a product 3. Spend a ton on marketing 4. Hope it works out News flash: it usually doesn’t work - Enter: Scientific Entrepreneurship. Here's the 3-step process: 1. Evaluate: Rank your ideas based on impact, cost, time, and ease of testing. 2. Experiment: Run quick, cheap tests to validate your concepts. 3. Elevate: Implement winning strategies and repeat the process. Why it works: • Minimizes risk • Saves time and money • Provides clear direction Real-world example: My friend spent 2.5 years and $180K testing products. I used scientific entrepreneurship and achieved better results in 4 months, actually MAKING money. Don't be a statistic. Be scientific.