In an article recently published in the Harvard Business Review, emblematically titled “Why Startups Benefit When Big Investments Come Later,” an interesting thesis is proposed: The timing and size of funding affect startup innovation: too much early capital reduces experimentation and sustainable growth.
The article presents the case of the startup Color Labs . Launched in 2011 with a record initial funding of 41 million dollars, the photo-sharing app has recorded more than one million downloads in less than a year. However, instead of improving functionality and user experience, the team focused only on acquiring new customers. Before long, technical problems and customer dissatisfaction caused usage to plummet. In 2012, despite $25 million still in cash, investors decided to close the company.
According to analysts, the main mistake was the pressure exerted by too much initial funding, which pushed the company to scale quickly without consolidating the product. In other words, Color Labs moved too early from experimentation to exploitation, sacrificing the learning and iteration phase, that is, that cyclical process of product improvement that involves continuous testing, gathering feedback from users, and subsequent adjustments to refine functionality and user experience. Color Labs has aimed to have lots of customers to “pay back” the investment instead of devoting itself to the original idea that starts small and grows with experiments, ongoing animated discussions, and sharing.
This affair has inspired more in-depth studies on the relationship between the timing and amount of funding and the innovative capacity of startups . Research by Harsh Ketkar (University of Texas, McCombs School of Business) and Maria Roche (Harvard Business School) analyzed more than 11,800 U.S. technology companies founded between 2010 and 2019, based on PitchBook and BuiltWith data.
Scholars have chosen to measure innovation not through patents – a tool little used by startups, both because the filing process is long and expensive, and because these companies move in very dynamic environments where it matters to get to product-market fit quickly, rather than to protect themselves legally – but instead analyzing the technology combinations adopted. A startup that uses very common technologies (e.g., Azure, Amazon RDS, and Tableau) is considered more conventional, while one that combines lesser-known tools (e.g., DigitalOcean, CockroachDB, Metabase) is classified as more innovative. The underlying idea is that revolutionary products often arise from the original recombination of already available technologies, as was the case with the iPhone. In that case, Apple did not invent entirely new components from scratch, but integrated existing technologies-such as touch screens, mobile Internet connection, music players, and intuitive graphical user interfaces-in a novel way, transforming them into a unique and disruptive device.
Indeed, we know that the Opposite cases, in which the revolutionary character comes not from recombination but from the invention of radical new technologies are much rarer. For example, the laser, which has introdeight a physical principle never before applied in optical devices; the transistor, which has replaceito thermionic valves revolutionizing modern electronics; or penicillin, which opened the way to antibiotic medicine thanks to a totally new scientific discovery.
From the study cited in the HBR article, the following emerge three main considerations :
- Timing – Startups that receive later first round funding tend to continue experimenting longer. Experimentation is a priority for an innovative startup because it allows them to validate hypotheses, quickly test different solutions and gather feedback from the market . This fast and iterative reduces the risk of developing products that are not in line with customer needs and allows the most effective technological combinations to be identified earlier while also keeping an eye on gradually changing customer needs. Without an extended phase of experimentation, startups risk burning resources in premature growth strategies, losing the ability to learn and adapt-essential elements for standing out in dynamic and competitive markets.
- Size – Those that receive large investments adopt more technologies, but in more conventional combinations, reducing exploratory capacity. Conventional combinations tend to replicate solutions that are already popular in the industry: this makes products more predictable and less differentiated, limiting the possibility of discovering truly innovative approaches. Conversely, Exploratory capacity is critical for an innovative startup because it allows them to experiment with untrodden paths, identify new market niches and create sustainable competitive advantages. Without an exploration orientation, the startup risks becoming imitative, losing its raison d’être and the ability to generate meaningful discontinuity from competitors.
- Track record of investors – The history of investors in startups affects the degree of experimentation allowed and their longevity. Investors with a long track record of exit (the strategy by which an investor realizes a gain by exiting a mature venture, startup, or company) tend to exert greater pressure to replicate already successful patterns, pushing toward rapid growth strategies and reducing exploratory risk tolerance. Conversely, investors accustomed to supporting young, highly innovative companies are more inclined to allow time and space for experimentation. This factor is crucial because a financial culture geared toward patience and innovation increases the likelihood that the startup will develop distinctive capabilities in the long run, while an approach focused only on quick exit can drastically shorten its life cycle.
Confirming this dynamic comes the testimony of Josh Walker, co-founder and CEO of Sports Innovation Lab, a Boston-based company that offers AI and data analytics solutions for sports. Founded in 2017, it faced critical times, especially during the pandemic, when it lost 30 percent of its customers in a single day.
Flexibility in the business model-from a focus on sports technology to fan data collection and analysis-was made possible by the nature of personal relationships between investors and the team, which ensured trust and patience. Walker points out that large financial institutions would likely have “cut their losses” after the initial difficulties, while investors close to the team believed in the team’s ability to adapt and innovate.
His recommendation to startups is to avoid raising too much capital too soon : high valuations without revenues generate unsustainable pressures, dilute founders’ control, and create unrealistic expectations. It is better to seek substantial investments only after demonstrating the ability to sell and retain customers.
In most cases, however, professional investors show neither confidence nor patience because they are constrained by short-term return targets , the need to reduce risk and the pressure to demonstrate quick returns to their stakeholders. This leads them to favor conservative strategies and disinvest as soon as difficulties emerge, even at the expense of long-term innovative potential.
Conclusion
The experiences of Color Labs, the research of Ketkar and Roche, and the Sports Innovation Lab case converge on a central point: it is not just the amount of capital that determines the success of a startup, but its timing, the attitude of investors, and the ability to preserve experimentation as part of the company’s DNA.
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Author: Gaetano Rizzitelli