Every new industry such as Virtual Reality, Augmented Reality, AI or even Blockchain, will bring revolutionary technologies to the world, but often it is the startups in the first wave which fail to commercialize effectively, dying in the drought after the initial market hype. The reason for this isn’t lack of innovation in product or services, or even disruptive technology, or the amount of funding; rather it is a missing business model in a space where customer needs are initially uncertain.
One of the best hardware startup examples of this situation where the challenge was successfully navigated is Fitbit. Though there have been many IoT sensor products designed for different applications including fitness, Fitbit managed to not only innovate on the product offering but it also found a sustainable business model to scale revenue, helping them cross the chasm of innovation to reach mainstream customers. But why is creating a great business model so difficult? Why don’t more startups start first with the perfect business model and then seek a technology innovation? And why is it often the second or third waves of startups which have a higher success rate than previous ones?
All of these questions are valid and require a deep dive into the obstacles associated with being a pioneer leading a new industry. In particular at my startup, we have learned a lot in our journey and still have not crossed the chasm. Yet I would like to share some of the lessons that have come with being early in VR, AR and AI with both hardware and software.
Abstract Concepts Are Harder To Grasp Than Tangible Ones
With new technology and breakthroughs everyone can easily imagine products or services which seem to be much more tangible than abstract business model concepts. This is especially true in hardware where you can touch, feel and demonstrate what you have built. Therefore you can often find many first time entrepreneurs in a completely new technology industry, as the playing field is reset to zero and every idea seems to be a first of its kind. But as is often the case, though those startups are very creative and unique in their ideas, the initial business model and value proposition of the product remain uncertain as customers have no experience and lack the knowledge to understand the core advantages.
Frequently, what ends up happening is that customers tell you they want your VR/AR, AI or Blockchain but as it is not solving a real pain the initial excitement dies down because the new solution is not adding more value than existing solutions. One of the recent reports I read was on facial recognition and companies starting to integrate it into everything like paper dispensers in restrooms. This innovation sounds initially exciting, but if there is no clear business model and value add in comparison to dispensing via hand motion, then this solution may be doomed to fail as well.
The hard part is to find a suitable business model, since they are often non-tangible and comprise many touch points with the product offering. This requires a deep understanding of how the value is created and a high-level view of how it impacts the customer long-term. From a consumer perspective this becomes even trickier, as consumers often do not know what they want and initial feedback from conversations can mislead the startup to believe there is a product market fit. From a business perspective there may be longer discussions and the right indicators to adapt the solution to a corporation’s needs, but then you may end up with a single solution which may not have a broad market.
Because new industries rely on never-before-seen technologies, it is even more difficult for the first wave of startups to succeed, as they do not have past data or the mistakes of other companies to learn from and then use that information to predict future demand and customer behavior.
Startups Learn More From Failures Than Successes
When you compare first, second and third wave startups in emerging technology industries, you will realize that success rates slowly increase, business models substantially improve and talents keep consolidating. Those changes have to do with previous failures and learnings, since the startups following the pioneers can learn faster from the mistakes of their predecessors in terms of customer needs by reading negative feedback online, generating revenue by listening to their pitches and analyzing pricing structures and improve team members’ capabilities by watching the rising stars and their achievements among industry peers.
Great examples for fast followers can even be found in the corporate world such as Apple and Google in launching hardware products. They learn quickly from previous company failures to iterate and launch a product into the market with fewer errors and then dominate the space through their brand. Apple does that with specific features in their iPhones like the dual camera after other players have already tested it in the market but failed to commercialize it. Google did this with Google Pixel, a phone which was launched into the market significantly later than anyone else but improved the value for customers through a complete Google system and business model with cloud, docs, email etc. It sold more than a million units in its first year.
In startups, as the first wave of pioneers try their luck on a completely new industry and technology, they often leave a landscape dotted with many lessons which can be acquired and adopted as the second wave takes over. If you look even more closely you may observe that the second wave typically has a more refined and smarter business model than the first. That’s because they deeply analyzed the feedback of users posting problems about the products and then addressed exactly those pain points using a combination of technology and business model solution. The small number of startups surviving the first wave are extremely rare but embrace fast and frugal business model iterations as they operate through the valley of despair in the technology evolution cycle.
The Game Of Capital And Creating Sustainable Businesses
Of course capital and investments are crucial to every startup’s success, but this also increases the pressure to deliver on a promise relatively quickly. First or even second wave startups deal with markets which are much more uncertain at this point than during the third or fourth wave. Even if you leverage a previous existing business model for a completely new technology market, there is no guarantee that the customer response will be the same. That’s why very early startups in a new technology space raise much more investment than needed. For example, Magic Leap received more than $1B+ or Jaunt which raised more than $300M+ in funding.
They know that it will take them time and lots of effort to design a business model which works for customers while delivering a technology which has never existed before. However the pressure to deliver and the large amount of capital can distract executives from long-term objectives to short-term gains impacting the startup’s direction and focus. A startup’s downward spiral starts when it is trying to do a lot of things simultaneously without listening to the market and deeply analyzing failures to extract insights necessary for the next iteration of the business model.
In addition, with more capital automatically comes more headcount which leads to a higher burn rate and shorter life span for the startup. The trade-off those startups face, however, lies in the market maturity and technology speed. If market maturity hits quickly, and competition rises with the right timing, you may be overcome quickly by these other companies. That means that even if you bootstrap the business for a long time as Airbnb has done, you must be smart with your timing in raising a larger round coinciding with the market uptake to create long-term impact.
If market maturity is slow, and your startup runs out of capital, then you failed before technology adoption hit mass market. Therefore, the game of capital is a very tricky problem to solve, particularly as many startups become very worried about not being in the spotlight through funding announcements, VC branding or displaying their company size to reach public mindshare. The question you really should be asking yourself is whether the market timing is right or not for a large amount of investment and if raising the capital is truly for the company acceleration or just your ego – probably one of the most difficult questions to answer for any entrepreneur out there.
A Business Model Search Never Ends
Admittedly there is no magic bullet to solve the business model problem, especially for an early industry. It even took very successful companies like Netflix many iterations until they found the right approach, and even to this point they may be still revising it as markets change and new competitors enter. But having the business model top of mind in whatever a startup does is crucial to its success. Companies from the very early stages to millions of dollars in funding, and even all the way up to IPO and beyond will fail without a viable business model. The main difference between success and failure is the company’s agility and flexibility to change by taking in all the mistakes and learnings along the way. The difficulty comes with company size, since larger organizations are more resistant to change and may run into their inevitable death.
For hardware startups and those in new industries there is no better option than to iterate much faster and stay paranoid as market and technology cycles have accelerated over the past few years. In our case, as a first wave startup, the paranoia was created through starving in funding and the core need of finding revenue as we switched into survival mode and must kill to live — probably one of the main instincts which has brought humanity to its stage of evolution today, and will do so for every startup.
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