Ducky vs. Sucky: What makes certain sectors more (or less) attractive than others for early-stage venture investors?

Julianne Brands - Feb 2016

What: Here at the Oregon Angel Fund, we strive to increase the collective understanding of the community as it relates to early stage investing. But, given we’re focused regionally, we see an incredibly wide range of companies solving problems across different sectors, industries, and business models. So, how do we frame our decision making within the context of investing in specific sectors? We hosted a workshop on “Ducky vs. Sucky: What makes certain sectors more (or less) attractive than others for early-stage venture investors?” to find out.

Who: We brought together a panel of industry veterans with experience investing across industry sectors and business models, Gerry Langer, Manager Director at OVP Venture Partners and former President of Mentor Graphics, Joe Cartwright, Economics at Impresa and Senior Policy Advisor for CEOs for Cities, and Tim Clark, Founder of Business Model You, to speak towards what makes certain sectors ripe for investment.

Takeaways:  At a high level, we learned that defensibility, scalability, and exit-ability vary widely across industries, but thinking about the application of these three ideas in each industry are important factors to consider when evaluating startups following different business models in different sectors and industries. Data from 2015 suggests that life sciences and software are seeing the highest number of total dollars exited - but with a far higher number of exits in software than life sciences. Emerging industries like fintech, IoT, cleantech, and edtech, are seeing smaller deals, both in number and capital, comparatively.  So what’s driving these returns? Here a few highlights and takeaways from the discussion to find out.

 

Defensibility: 

  1. Sustainable differentiation is key to building a successful business in any sector - whether that differentiation comes from classic disruption (i.e., cheaper and worse!), IP & trade secrets, proprietary data, high switching costs, brand equity, monopolizing a certain niche, and/or a founding team with hard-to-replicate relationships and skills. Companies often need more than a few of these to remain competitive.  
  2. Topology changes, but functions don’t!  Technology is driving changes in form factors, but ultimately, solving same problems. This is driven by technological changes. For example, Saas should be viewed as a technology that can enable several business models.  
  3. Place - the location of a startup - can often give a company an unfair advantage. Helpful, but not determinant.  In bioscience hubs like Boston and San Francisco, it’s no surprise there are success stories given the unique access to specialized resources - like the best people in the business, cutting edge labs, attorneys skilled at licensing bioscience IP, and smart money that can give companies unique advantages. 

Scalability:

  1. It seems obvious, but operating profit has to increase (a lot!) faster than revenue, and often a company’s sector affects the rate at which a company can scale based on market size, labor-intensivity of the business model, channel & capital efficiency, customer competitiveness, and whether they are attacking the ‘stubby head’ or the long tail of the market.  
  2. The ability to find mistakes and learn quickly is crucial for companies to find the right product-market fit and business model. Once achieved, they can scale using a repeatable process, but it appears that the ability to ‘fail fast’ differs by sector. For instance, it’s faster and cheaper to fail fast in software and IT, but harder to so in bioscience and cleantech, where innovation and market acceptance is more binary and less iterative. Product testing and market validation can be a much longer process given regulatory constraints and product development cycles. 
  3. Timing:  Finding a big wave to ride!  A company can only be as big as the market it’s in. Riding a wave helps tremendously, especially if one rides a wave early in its formation.  Does the entrepreneur see a wave materializing before others do? 
  4. Some business models are more conducive to scaling than others - SaaS business models have been successful, in large part, because of the ability to reach a large amount of customers, with relatively little overhead (read: high gross margins!) for both sales and product implementation. 
  5. Products/services that can sell themselves via a self-serve model have a huge advantage over those that require human involvement in sales, adoption, and support.  A product like Wave Sensor, which requires a direct sales approach, at least initially, and some support, might scale more slowly.  The cost of sales and support needs to be dwarfed by the average revenue per facility.  
  6. Consumer products and services have a higher degree of uncertainty and risk.  In B2B companies the ROI is often very quantifiable and measurable.  In B2C companies, the ROI is often “psychic” and therefore harder to measure and articulate.  

Exit-ability:

  1. Universe of potential buyers important and varies widely across markets. Exit-able companies must have a clear value proposition, large, varied, competitive, and profitable acquirers, and a “buy”, not build, mentality.  
  2. The dynamics of buyers vary across industries - it’s important to look for markets where buyers are both abundant (lots of them!) and expansive (buy lots of stuff!).  For instance, IT has a wide range of buyers, and those buyers are often interested in diverse technologies (sometimes even ‘cannibalizing’ their own technologies). Bioscience has a smaller group of active acquirers, but often, are interested in buying more narrow, specific products. Cleantech faces a similar problem with a very small universe of active acquirers. 
  3. Multiples on exits are different across industries.  The multiples in bioscience can appear infinite if a company has IP but no revenue.  On the other hand, returns in hardware are often just 1X revenue. 
  4. Companies with margins >60% (software and Internet) command higher exit multiples than those with lower margins (products and service-intensive businesses).  

Ultimately, though, it might be worth thinking about the intersection of industries and disciplines that makes for truly innovative companies like Data Analytics in Healthcare, IoT for Agriculture, and manufacturing design software. Happy investing!