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  • Max Werny

A guide to techno-economic analysis for early-stage founders

There’s nothing like a good TEA. And no, this (unfortunately) does not have anything to do with Earl Grey, Darjeeling or matcha tea. The TEA we’re talking about stands for techno-economic analysis and is all about understanding your business at its core!

Given its importance for every hard tech startup, we decided to put together a short, concise TEA guide for early-stage founders. A TEA can seem daunting at first but very often turns out to be an incredibly useful tool for founders. Our mission is to make this journey slightly less bumpy and therefore more enjoyable for entrepreneurs. Read on to find out more!

What is a TEA?

A techno-economic analysis (TEA) is an evaluation tool that combines technical and economic aspects to assess the feasibility, competitiveness, and potential impact of a technology or project. It can provide you with a detailed understanding of your unit economics, cost drivers, technical key performance indicators (KPIs), as well as the benefits and risks associated with the implementation of your technology.

As every TEA is different, we recommend founders to use multiple resources to construct a TEA that fits their process or product (more on this at the end of the article). TEAs for pre-seed and seed companies will naturally differ from TEAs for later-stage companies as there are more unknown parameters and thus greater uncertainty. But don’t let this deter you - a TEA is a tool that comes in handy even at the earliest stages of company building!

What goes into a TEA?

Like a good cuppa tea, you need to get the ingredients right - see our graphic below for the most essential ingredients:

Relevant information that should go into a techno-economic analysis (list is not exhaustive).

For those of you who want to get to the bottom of this, take a look at our TEA checklist below (list is not exhaustive):

  1. A schematic figure (e.g. process flow diagram), especially if the system is complex

  2. A list or table of the key components in your system

  3. A concise technological description of the system, process or product that you are working on (if this is not already present in your data room)

  4. Key technical parameters:

    1. Mass balance (mass flows in and out of your system)

    2. Energy balance (electricity, heating, cooling, exo- or endothermicity of chemical reactions, etc.)

    3. Operating conditions (temperature, pressure, voltage, current, flow rates, etc.)

    4. Efficiencies

    5. Yield

    6. System capacity (equipment/reactor/plant sizing)

  5. Key financial parameters to assess your unit economics, pricing and profitability (some of these might not be assessable until later stages of development, use reference data or proxies until you have your own data):

    1. Capital expenditures (CAPEX): Building, machinery, reactors, equipment, balance of plant, installation, vehicles, IP, etc.

    2. Operational expenditures (OPEX): Electricity, water, steam, chemicals, materials, salaries, rent, maintenance, insurance, etc.

    3. Revenue projections

    4. Profit/profit margins

    5. Payback periods

    6. Net present value (NPV)

    7. Internal rate of return (IRR)

  6. Sensitivity analyses to assess the impact of various different commercial and technical parameters

  7. A comparison of your technical and commercial KPIs with those of incumbents and other emerging technologies (benchmarking)

  8. Scaling analysis (economies of scale + learning effects): Modelling your economics for a first-of-a-kind (FOAK) plant as well as the transition to an Nth-of-a-kind (NOAK) plant

  9. An overview of potential technical challenges and uncertainties in your model

Factors contributing to the operational (OPEX) and capital expenditure (OPEX) of a company and therefore the unit economics.

Remember: Like a good cuppa tea, your TEA needs to brew. Don’t expect a perfect outcome (i.e. highly accurate predictions) the first time you build your TEA. It’s an iterative process that requires time. Your accuracy will improve as you collect more and better data.

Check out the section below for more insights and recommendations on how to build a bullet-proof TEA.

What should I keep in mind?

  1. Start early: It is never too early to start building a TEA to identify the levers that are critical for your unit economics.

  2. Keep it digestible: A TEA should be well-structured and transparent. Always remember that other people might not be experts in your domain and may therefore require additional guidance. Include an overview page that briefly describes the system, process or product that you are working on and explain your general approach to the TEA.

  3. Focus on what matters: Start with the centrepiece of your system/process/product. Follow an 80/20 approach when working on your first versions and do not lose too much time trying to assess non-essential components. Simplify your calculations by making rational assumptions or using trustworthy reference data for supporting components/processes and balance of plant. These can be assessed at a later stage when more accurate data is available to you from testing or partnerships.

  4. Play with your variables: Perform a sensitivity analysis (i.e. variation of one or more input variables) to test the assumptions you have made, and how variations affect the overall TEA. Which parameters are the most important?

  5. Use reliable data: Any TEA is only as good as the data/assumptions used to build it. Be clear about your assumptions and provide references

  6. Constantly refine your TEA: Remember that a TEA is a living document - use it to find your critical path and refine it regularly.

  7. Benchmark your startup: Compare your unit economics to those of incumbents and competitors (including pre-commercial, emerging technologies).

  8. Think ahead: Identify how you think main components will change over time (e.g. with regulation, competition, economies of scale, new geographies/markets) and simulate different scenarios.

What are common pitfalls?

At ZCC, we see a huge variety of different TEAs every year. We have tried to put together a list of things that can lead to greater levels of uncertainty in your TEA:

  1. Unreasonable assumptions:

    1. A very low power price (assuming 100% cheap renewables)

    2. High capacity factors at very low power prices

    3. Low feedstock prices (e.g. for green H2 and biogenic or captured CO2)

    4. Unlimited feedstock availability (e.g. biomass)

    5. Abundant waste heat availability

    6. High green premiums for products with insufficient justification

    7. Aggressive carbon pricing on incumbent technologies to justify own technologies

  2. Modelling the core technology instead of the full system: The system boundary should be clearly defined. Take all equipment, engineering and balance of plant into consideration as these can add significant costs.

  3. Unrealistic or incomplete benchmarking: It is important to not only benchmark against mature technologies but to also take emerging technologies into account. Compare your costs and sales price to the market prices of these technologies: What is the floor price of incumbents and newcomers? How high can your profit margin be?

  4. Focusing on the wrong or a limited number of metrics: A good TEA takes all relevant metrics into consideration.

What are reasonable assumptions for the prices of electricity, hydrogen and carbon dioxide?

Given that many climate technologies depend heavily on electricity prices, and a significant number, on the cost of hydrogen, carbon dioxide or both, we thought it would be helpful to discuss the numbers here. Please note that all prices mentioned below are bound to change with time.

Electricity costs:

Quarterly average wholesale prices for selected regions in $/MWh (2019-2024). Source: IEA.

  • Our recommendation: €60-80/MWh (~$64-86/MWh) as a starting point

  • The Lazard LCOE report gives values for different technologies (in $)

  • The lowest LCOE for solar/onshore wind is not available 24/7

  • Cost of energy available depends on ability to load-follow intermittency

  • Cost of energy depends on whether energy bought from the grid or from dedicated (renewable) energy assets

  • Cost of energy depends on geography

  • OPEX depends on capacity factor

  • Use a sensitivity analysis to evaluate the impact of varying electricity prices

Levelised Cost of Energy (LCOE) for different renewable and conventional energy sources. Source: Lazard 2024 LCOE+ Report.

Hydrogen costs:

  • Electricity costs are the major component of hydrogen costs:

  • Using a €60/MWh electricity cost and assuming energy requirements of 50 kWh/kg H2 (78% efficiency), electrolytic hydrogen production using the same electricity will cost at least €3.0/kg (~$3.2/kg)

  • There should be a sensible correlation between the electricity price and the green hydrogen price

  • The Lazard LCOH report gives estimates of $2.5-6.1/kg for green hydrogen, depending on subsidies

  • Our recommendation: €3.5/kg (~$3.8/kg H2) as a conservative starting point

  • Use a sensitivity analysis to capture the uncertainty around future hydrogen prices

Levelised Cost of Hydrogen (LCOH) for green and pink hydrogen. Source: Lazard 2024 LCOE+ Report.

Carbon dioxide costs:

  • Choosing a carbon dioxide price can be tricky due to the wide range of CDR technologies that are emerging

  • Costs for point-source captured CO2, biogenic CO2 and some types of biologically captured CO2 fall in the range of approximately €23-93/t CO2 ($25-100/t CO2)

  • Direct Air Capture (DAC) companies are aiming for €93/t CO2 ($100/t CO2, some even lower) but will inevitably need time to reach these prices

  • Use a CO2 price that is aligned with your CO2 suppliers/sources (refer to the IEA’s report on carbon capture costs to get a better understanding for how CO2 costs can vary)

  • Use a sensitivity analysis to capture the uncertainty around future CO2 prices

Costs of capturing CO2 from different sources in $/t CO2. Source: IEA.

Where can I learn more about TEAs?

Need more information or examples? Here is a list of resources that can guide you on your journey to your first TEA:

What is a TEA?


Data sources & tools:

Did we miss something? Are you a founder or investor with an idea that will drastically improve every TEA? Then reach out to us! We would love to learn from you.


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