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15 September, 2021updated 01 Nov 2021 10:18

Lara Williams

Opinion: A data-driven approach can end the smoke and mirrors of deep tech investment

The court case of Elizabeth Holmes, accused of defrauding investors in Theranos, shows the pitfalls of blind faith investment in deep tech. There is a better way.


The fraud trial of Elizabeth Holmes, the founder and former CEO of life sciences company Theranos, shows how perilous the world of deep tech investment can be. (Photo by Nick Otto/AFP via Getty Images)

Silicon Valley-based Elizabeth Holmes, the founder and CEO of biotech start-up Theranos, went on trial at the end of August 2021, accused of defrauding investors in the company. Although Holmes’s plight is widely recognised as one of the tech industry’s biggest scandals to date, it raises wider questions about an increasingly fantastical culture of investing in deep tech start-ups.

Theranos claimed its proprietary blood testing device could deliver hundreds of diagnostic results from just one tiny pinprick. High-profile investors including media mogul Rupert Murdoch and former US education secretary Betsy DeVos were sold on the promise of a technology that never existed.

Accusations over the inflating of product capability is also a factor in the case of Trevor Milton, founder and former CEO of US-based electric truck-maker Nikola. The entrepreneur was charged in a securities fraud scheme in July 2021, which alleged he misled investors about the development of products and technology. US Attorney for the Southern District of New York Audrey Strauss said in a press conference at the time: “Milton lied about nearly every aspect of the business.”

More recently, deep tech synthetic biology company Zymergen saw its share price plummet in August 2021 as it announced that several potential customers were having problems implementing Hyaline, a high-quality flexible film used on the screens of electronics. The company said it “no longer expects product revenue in 2021 and expects product revenue to be immaterial in 2022”. Founder and CEO Josh Hoffman stepped down after the share price plummeted.

Over-promising and under-delivering

Each case demonstrates a trend of over-promising market-ready technology to investors. Deep tech is notoriously hard. It requires vast amounts of capital for research and development with little prospect of any short or medium-term return. This is why many deep tech success stories originate from government-funded programmes.

Investments are sometimes made solely on the basis of a founder’s compelling origin story and the convincing promise of world-changing technology. In many cases, as seen in the unravelling of Theranos, belief trumps logic.

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To raise equivalent levels of private capital, some start-up founders adopt the wider Silicon Valley culture of ‘fake it before you make it’ for capital raising by over-hyping their technology. Problems arise when the narrative spins too far ahead of the curve and cannot meet the necessary technology milestones. Add an investing environment in which investors are lining up for the chance to bet on the next decacorn or hectocorn, and you have a perilous combination open to fraud.

According to data from Dealroom, global venture capital investment is on target for an all-time high in 2021. Since the start of the year to 7 July, more than $312bn has been invested globally – up from $131bn for the same period in 2020.

Global investment in deep tech quadrupled from 2016 to 2020 when it reached $62bn. With investors competing for the opportunity to write cheques before the next investor in line gets a meeting, many consider the risks of investing with a minimum of due diligence outweigh the potential for massive profit. Investments are sometimes made solely on the basis of a founder’s compelling origin story and the convincing promise of world-changing technology. In many cases, as seen in the unravelling of Theranos, belief trumps logic.

The antidote to this 'smoke and mirrors investing' is milestone-based investing alongside effective due diligence. Primarily, it avoids the spectacular implosions, usually around deep tech, as seen in the examples of Theranos and Nikola, by requiring proof of progress at each stage – and in the case of Zymergen, a closer look at the company’s product would have saved massive investor losses even though there was no fraud involved.

Michael Kauffman, a principal at US technical due diligence consultancy Tech DNA, says that in the hundreds of deals the company has worked on to assess technical quality, actual falsehoods – as in the Theranos case – are rare, but underlying technical weaknesses that affect a deal’s validity are not. “In many cases, these are fixable and simply increase deal cost, but in some the underlying technical debt we find is significant enough to fundamentally call into question the deal theory – even for products or services already in market," he says.

In an investing environment in which major capital sources are making $500m seed investments in massively overvalued companies with no product and no revenue, the burden of proof is no longer weighted as heavily on start-ups. For example, the Softbank method of investing runs antithetical to milestone investing. Responsible investing means requiring start-ups to prove incremental progress so that capital-raising is scaled according to tangible progress. Otherwise, an abundance of available capital alongside a lack of governance is a recipe for disaster.

Bridging the knowledge gap

According to the Boston Consulting Group’s May 2021 report The Deep Tech Investment Paradox, deep tech suffers from a knowledge gap between innovators and investors. Venture capital funds often lack the expertise needed to understand advanced science and engineering risks, and to effectively support deep tech ventures.

Venture capital funds often lack the expertise needed to understand advanced science and engineering risks, and to effectively support deep tech ventures.

To bridge this gap, investors need to grow their in-house knowledge, including the hiring of both postdoctoral scientists and engineers, as well as develop strong ties with research and innovation ecosystems. According to Boston Consulting Group’s survey of deep tech investors, 79% needed to leverage external expertise, 42% have hired PhDs and 37% have hired people with master of science qualifications or engineer profiles to assess deep tech potential.

A simple business evaluation of company financials and due diligence around product development would have uncovered the holes in the claims of both Milton and Holmes. Boston Consulting Group estimates that deep tech investments could exceed $200bn by 2025 if more effective investor models are adopted. That is a lot of capital at stake. Without following the basic tenets of milestone investing, talking to customers to understand the proper product market fit and doing the required due diligence, deep tech investors are laying themselves wide open to risks of this kind.

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