The Capital Conundrum
Understanding the impact of venture dollars on the intersection of AI and vertical software
The Theory of Good & Bad Capital
Good (Patient) Capital: funding that aligns with a startup's long-term vision, enabling exploration and refinement of strategies
Bad Capital: funding that demands short-term growth, potentially leading to unsustainable practices and adverse consequences
The theory of good and bad capital, as articulated by Professor Bhide in "The Origins and Evolution of New Business," holds major implications for startups seeking funding in today's AI revolution. As we touch upon the nuances of investing in vertical-specific AI and software applications, it becomes evident that who you raise from matters. Founders shoulder the responsibility of charting their company's strategic course, while investors must recognize the unique challenges and opportunities present to provide effective support.
In the early stages of company building, startups face the challenge of assessing the potential success of their strategies while dealing with limited funds. The importance of adaptability and the willingness to pivot when necessary cannot be overstated. Research shows that 93% of successful companies change their initial strategy, highlighting the importance of being agile and open to change.
To increase their chances of success, startups need patient and supportive capital (aka âgoodâ capital). Good capital is about creating solutions for customers' biggest problems and using that as the basis for long-term growth and profitability - it gives founders the time and resources to try new things and improve their business models or strategies without feeling rushed to grow too quickly and unsustainably.
Conversely, bad capital, which demands rapid growth without concern on profitability, usually leads to adverse consequences. Numerous anecdotes from previous boom and bust cycles serve as cautionary tales, highlighting the risks of prioritizing growth at any cost. For startups specializing in vertical software, this is particularly relevant, as they must strike a balance between solving critical problems with innovative products while empathizing with the industry dynamics - for example:
Some verticals require customer education, resulting in lengthier sales cycles
MVPs often require more upfront work to deliver sufficient ROI and justify replacing existing products
TAM usually starts small and needs a roadmap with multiple products to reach its full potential
Unlike investing into horizontal SaaS businesses, investing into vertical software comes with its own intricacies. For example, there arenât well-established playbooks from GTM to pricing that work across all industries. Each has its own unique demands, making it hard to follow a one-size-fits-all approach. Hence, trying to impose familiar, rigid growth expectations from existing software models on these companies can set them up for failure.
In summary, vertical plays, especially in underserved markets, tend to require more time to build.
When it comes to assessing build vs. buy decisions for customers willing to leverage vertical AI solutions, the choices arenât always clear-cut (the trade-offs for teaming with an upstart vs. an incumbent are more salient today than before). Startups need to be ready to take multiple shots on goal, given the rapid advancements in AI technologies and the need for continuous adaptation and thatâs where good capital comes in.
Applications of Good Capital
Within the dynamic field of healthcare, where regulations are constantly evolving, Big Tech is actively seeking partnerships and making inroads, and data privacy remains a top concern, startups leveraging AI/ML technologies encounter complex challenges that require multiple shots on goal.
Let's consider a scenario where an AI startup introduces a new personalized diagnostic tool to the market. Their mission is to detect a specific disease at its earliest stages, leading to more effective treatment and improved patient outcomes. This aligns with the broader discourse on healthcare organizations exploring ways to integrate value-based care measures to lower service costs while optimizing patient care. However, as would any startup that embarks on this journey, challenges arise that requires iteration and adaptation.
For instance, in the initial version of their product, they might work on integrating different data sources to enhance the tool's predictive capabilities and fine-tuning algorithms based on patient feedback and real-time data to improve its performance. While the model may demonstrate high accuracy rates in detecting the disease during initial testing on controlled datasets, real-world implementation introduces complexities like diverse patient profiles, variations in data quality, privacy and compliance concerns, and ever-evolving medical knowledge. Addressing these pressing action items requires patient (good) capital.
At Zenda, the theory of good and bad capital serves as a guiding principle, as it should for others looking to invest into the world of verticalized AI applications. By embracing the tenets of good capital and recognizing the complexities of these mission-critical industries, we can support founders in unlocking the transformative potential of AI while charting a sustainable path towards long-term growth and success.
In other newsâŠ
â Fellowship Updates
We are thrilled to introduce our latest addition to the team, Bailey Richards, our new research fellow! Bailey brings a wealth of expertise and a strong passion for driving healthcare efficiency and equity. With a background in public health, research, and healthcare technology, Bailey will support our research efforts as we continue to explore advancements in innovation within the areas of value-based care and beyond.
As we welcome Bailey, we also want to extend our appreciation to our previous fellow, Ben Pasco-Anderson, for his invaluable support. Ben played a crucial role in helping us develop our healthcare thesis focusing on Revenue Cycle Management (RCM) and Fraud, Waste & Abuse (FWA). More to come in future issues on our key learnings hereâŠ
Asks: In the meantime, if you know of founders, industry operators or professionals who are building or operating software within these theses, donât hesitate to reach out: jeff@zenda.vc or er@zenda.vc!
đą Zenda Highlights
Our General Partner Esteban was recently featured on an exciting podcast episode with fellow friend Ty Findley from Ironspring Ventures. In this episode, we discuss everything from what it means to invest behind founders building for underserved industries to building a new fund as an emerging manager in todayâs competitive VC landscape. Check it out!