A Simple Founder’s Guide to TEAs
Understanding cost competitiveness is vital for early-stage founders working on climate solutions. Techno-Economic Assessment (TEA) provides the necessary toolbox to evaluate the economic potential of a new technology. Yet many founders and investors new to the field struggle with it. In this article, we provide some initial guidance and basic TEA best practices that we like to see when evaluating early-stage climate technologies.
Like every SaaS founder should know their metrics such as unit economics and LTV/CAC ratios, every climate founder building physical products should know their techno-economics 🤓. Doing a Techno-Economic Analysis (TEA) should be a basic exercise done early on and refined at every development stage.
In a nutshell, TEAs are a way to understand a product’s potential economic competitiveness by looking at technological and economic variables which influence cost levels and thus prices. It is very similar to a Life Cycle Assessment (LCA), a framework to assess impact, which we use as part of our investment process at Planet A (see our methodology here). But instead of environmental impact, this method focuses on the costs involved.
WHY EVERYONE SHOULD DO A TEA
In general, TEAs are a strategic tool that can help founders understand the potential economic competitiveness of their technology. In the climate tech context, this is useful when assessing whether a technology can be economically viable and/or achieve price parity with incumbent approaches. This is particularly important for commodity markets such as energy, chemicals, or CO2. By identifying key cost drivers and levers, you can not only show the economic potential of your process but also sketch a roadmap to get there once operating at scale.
In short: it’s a must-do exercise even at early stages. Your TEA shows investors how you think and serves as a basis for assessing your technology.
HOW TO PERFORM A BASIC TEA
I. Look at your technological variables
The first step is to get operational data on process parameters like resources, material flows, and energy requirements and build a simple process model. Estimates or assumptions for some inputs may be required but should be improved with time. The outcome of that model should include material and energy balances. Together with reaction kinetics, conversion rates and other process-related information, it is used to size your equipment.
II. Estimate operating expenditure
Based on your process model, you can estimate fixed and variable operating costs by combining required material, labor, energy, maintenance, and other data with corresponding market prices. You may want to include cost projections in the model, particularly if the success of the technology is fundamentally dependent on something such as declining low-carbon energy costs.
III. Estimate Capital Expenditure
By compiling an equipment list and getting prices from the literature or supplier quotes, you can estimate the Capex needed for your plant or machine. Be sure to include factors for other important categories such as equipment installation, piping, electrical systems, instrumentation, and so on, which can lead to capital expenditures that are up to four to six times as high as the costs for the primary equipment alone. To be on the safe side, add contingencies on top.
IV. Break down to production unit
After taking the costs together you can express it in a functional unit to normalize input and output data (e.g., cost per gross ton of carbon dioxide captured from the atmosphere).
V. Express in the right financial metric
Finally, express the output in a suitable economic metric. In many cases, unit costs are enough to get started, but you could also gather other KPIs such as IRR, ROI etc. using a more advanced financial projection and get market data on prices to derive margins.
DO’S AND DON’TS
We see numerous TEA calculations every week and put together some simple best practices that you can follow:
Realistic Assumptions: Be open about your assumptions, state your sources, and choose realistic, industry-specific values for current and future key parameters such as energy costs. Include all relevant items across the lifecycle (transport, procurement, maintenance, etc.).
Main levers for cost reduction: After working out the main cost drivers, show us how you will drive costs down as you scale up.
Sensitivity Analyses: Many variables are highly volatile and conducting thorough sensitivity checks to assess impacts of e.g. rising material prices is a must-do.
Disposal and Co-Products: Many processes come with additional cost or revenue streams based on secondary products that are outputs of the process (e.g. H2, acids). Make sure to factor this into your calculations.
Learning Rates: As an investor, we are interested in your current TEAs and your numbers at scale. To get from your first-of-a-kind (FOAK) to your fully developed n-th of a kind projection, you likely need to work with learning rates. Be sure to state such assumptions openly and show us how scale effects influence your costs. Direct estimates of projected cost reductions from specific exogenous changes, technical breakthroughs, or scaling effects are preferred to more general learning rates, however, as these are more transparent and easier to assess than a general rate.
TRLs per Process Step: It is often times useful to see the TRL broken down to separate process steps to better assess the science and scale-up risks associated with each step of the process.
Energy Procurement Strategy: ‘Abundant’ renewable energy seems far out and the grid is far from green. Therefore energy-intensive processes should have a proper procurement strategy in place.
Tradeoffs: Often times there is a tradeoff between different parameters (e.g. pressure and reaction kinetics, OpEx, and CapEx). Be aware of those balances and highlight what is the most efficient combination of parameters.
Material sourcing at scale: Many processes might face bottlenecks in industrialization due to inexistent supply chains or challenges with material availability (e.g. minerals). Let us know how you will address this.
Thermodynamic limits: Every process has certain limits. While we know that TEAs will never be 100% accurate, be sure to follow the basic laws of physics when doing your calculations. 🙂
GET YOUR TEA TEMPLATE
We hope this little guide will help you to approach your own TEA. This should be an initial sanity check to see if your idea makes sense but doesn’t replace the need to investigate whether there is an actual need in the market. As a little bonus, we prepared a very basic template to help you get started. You can access the TEA template here. Please note that the file is optimised for Google Sheets and not Excel, so just copy it to your drive to access it.
As every process is fundamentally different, it is advisable to see this as a starting point for structuring your thinking, while working with subject matter experts as you build out your analysis. There are great resources and people like Grant Faber from Carbon-Based Consulting and Katrin Sievert from ETH Zurich out there that can help you. If you do think your TEAs are yielding interesting results and also create a large impact, reach out to us!
🤝 Helpful resources:
- Activate TEA Whitepaper: https://www.activate.org/techonomics
- Techno-Economic Analysis: Best Practices and Assessment Tools by Sandia National Laboratories: https://www.osti.gov/servlets/purl/1738878
- Global Co2 Initiative: https://assessccus.globalco2initiative.org/tea/guidance-documents/
- Towards improved guidelines for cost evaluation of carbon capture and storage: https://www.osti.gov/servlets/purl/1779820
- Towards improved guidelines for cost evaluation of carbon capture and storage: https://www.osti.gov/servlets/purl/1779820
- Best Practice Example 1: Techno-economic assessment of CO2 direct air capture plants https://www.sciencedirect.com/science/article/pii/S0959652619307772
- Best Practice Example 2: General Techno-Economic Analysis of CO2 Electrolysis Systems https://pubs.acs.org/doi/abs/10.1021/acs.iecr.7b03514?casa_token=Ob51LzXuqCcAAAAA:7Pb_CSjfpQ8OElGDk0PNsufe947ra4x8NleMvn-bFvpoJlhEhG910GIrW4VZG_ENd5t09O4hqbXPi6c
