Fake Entrepreneurship! Why A Record Number of Startups Are Shutting Down?
Lack of Strategy as a First Principle
In a Harvard Business Review (HBR) survey of 10, 000 senior leaders, 97% said that strategy is the most important thing to their organizations’ success, and 96% also said that they lack the right thinking framework and tools to engage in strategy development effectively. With such a statistic it is amazing, still, that so many startups continue to put the cart before the horse — focusing on building cool technology features first, rather than critical strategy.
Digital Transformation Is Not About Technology: Companies are pouring millions into “digital transformation” initiatives — but a high percentage of those fail to pay off. That’s because companies put the cart before the horse, focusing on a specific technology (we need a machine-learning!) rather than doing the hard work of first fitting the change into the overall business strategy — HBR.
In this rapidly advancing AI era, many startups seem to be caught up in the technology fascination game — fake entrepreneurship. Not understanding or learning from the lessons of past industrial revolutions. Mistakenly believing that artificial intelligence (AI) is somehow unique in the context of the history of technology and change. This uninformed and lazy thinking many startups and businesses are trapped in is counterintuitive to authentic business growth aspirations. Regardless of the era or the time and place, technology will always be about solutions and tools to run and enhance real business models that can be useful to society.
Cool technology in itself is not a business model. Even if that business is about selling technology. Fundamentals and strategies about business always apply and remain the main thing.
The startup business has become a disingenuous smoke-and-mirrors game, run by analysts, not real entrepreneurs — the really successful ones are busy running their businesses. So what we are left with is the VC-infused startup hunger games — pass the hot potato. VCs look for startups that fit their funding models best…moving them up the valuation curve. Making money off phony valuations rather than real business fundamentals.
These days anything and everything generative AI is the hook; just say you are developing new GenAI technology or features and funding will come knocking. This is the hype and fascination that drives the startup investing market.
This reality has created great fragility in the industry and startups can’t stand up to the volatility, so they break easily when the reality of fundamentals begins to rattle them.
If we take the pandemic as a marker of the point when the AI/digital transformation began to accelerate — everyone looked to become an AI startup of some sort, and with low interest rates, it seemed that everyone was on the catwalk.
If you have any basic stock market investing experience you should recognize that when everyone and their grandmother is in a high-flying market. The writing may already be on the wall. Eventually, gravity prevails. So it’s no big surprise to see this level of startups shutting down. The majority of these hyped companies don’t last more than 3 to 5 years and when the hype changes, the herd moves on, i.e., cryptocurrency.
Emad Mostaque, founder, and chief executive of Stability AI has pointed out recently the “stark similarities between the dot.com bubble of the late 1990s and AI today.” Today, it is widely known he says and encouraged that adding generative AI to your pitch deck will meaningfully strengthen your chances of getting venture capital.
Investors too must seek genuine founders who are curious and authentically critical thinkers, and leaders with backbone looking to solve big problems. And be skeptically savvy enough to pick out the fakers.
Founders must be more objective and empirically observant and resist the temptation of the big funding VCs coming their way. Remember, many VCs are just courtiers for big tech anyway who are looking to fund specific startups that are developing specific technologies. Ultimately, the plan is for the bigger fish to swallow up the tiny startups, ensuring that their technology can’t ever challenge them. So many startups serve as cost-effective outside R&D, and VCs facilitate that.
In the first quarter of 2023 for example, $15.2 billion was plowed into generative AI companies on a global basis, according to Pitchbook data services. Not surprisingly, the vast majority of that amount came from Microsoft (MSFT)’s $10 billion investment in OpenAI, the generative AI chatbot ChatGPT. But putting aside Microsoft’s amount, VC investments in generative AI were up by nearly 60 percent compared to last year (2022.)
Such concentration serves to stifle the potential up-and-comers — creativity and innovation are choke-out lessening the potential of finding those really great startups that can disrupt and challenge big tech incumbents. VCs are complicit here; distorting capitalism and holding back potential growth economies.
According to Professor Julia Ott, The New School of Economic Thinking, Centre for Capitalism Studies. She says that we shouldn’t buy into the myths about venture capitalism…that how early-stage VC-specific financing is essential for economies. Prof. Ott’s work uncovers the myths around VCs that “…the VC virtuous cycle narrative of return and reinvestment…innovation, job growth etc., the data shows that venture capital plays a very negligible role.”
It’s a game she says of “building up these high-valuation incumbents who buy up competitors with their own VC money and crush the competition, stifle innovation, raise prices and suppress workers etc.”
Therefore, the first step to bringing real entrepreneurship back is for startup founders to replace the technology-first, instant gratification mentality with STRATEGY as a first principle.
A prime example of the VC industry investing fascination-hype is the New York-based company Normal Computing. Normal Computing has raised $8.5m in seed funding to further its mission of “enabling artificial intelligence (AI) for critical and complex enterprise and government applications.” Normal’s probabilistic AI technology as I read it, is based on a subject matter involving chance variation theory. Normal’s technology development is designed to provide “unprecedented control over the reliability, adaptivity and audibility of models powered by customers’ private data.”
However, if we apply logic and some of Aristotle’s commonsensical approach, it would seem that Normal’s business model is essentially another lame attempt to ride the AI wave with another theory that goes nowhere. Normal seems to be correcting-to-perfection of LLMs. But LLM’s main problem is hallucination. Normal says it will correct “errors of unpredictability and hallucinations” and make them more “reliable.” In other words, throwing more data and loops at the problem. But the errors are not errors of insufficient computational power so Normal can run as much data and as many loops as it likes, but it will still be going around in circles.
Probably the biggest single problem with large language models is that they make things up, enough so that by now common but overly anthropomorphic term for such errors, hallucination, was dictionary.com’s word of the year for 2023.
— Gary Marcus
Normal and many others in the startup game have not come to terms with the original problem, that generative AI has struggled mightily when it comes to interpreting the real world. Even basic reasoning and factuality, even with ever-greater magnitudes of data and sophistication — still a significant problem that has yet to be answered.
Therefore, at the end of the day, the fundamentals of business investing remain steadfast. Riding fascination or cool technology features as a pure business model is not a long-term sustainable one. Logically then, everything must begin with a good strategy, whether it be operational, functional, governance, or business growth strategies.
The survey below conducted by CB Insights revealed that the number one reason for a startup’s failure was a ‘lack of market need.’ If the product doesn’t nail the problem, customers won’t go along with it to find a solution. This mistake is a function of not having a viable strategy as a first principle because what you might believe to be true about a market is irrelevant. The only thing that matters is what is objectively true and that can only be discovered through disciplined process research.
Furthermore, every one of those reasons listed in the chart above could be risk mitigated with proper strategy-development application. So before a business initiates an idea and embarks upon an action or development process, it should ensure that the strategy process is at the forefront of everything it does.
Strategy is fundamental to everything!
The phone book is littered with plenty of businesses that have raised millions of dollars and built great tech teams, but have nevertheless flamed out because of poor strategy or no strategy as a building cornerstone.
Quibi may be the most notorious example— all hype and no strategy. Quibi never put strategy first, so they were never able to learn and discover what they didn’t know. Never really designed an overriding fact-based growth strategy. The Quibi brain trust believed that they knew everything and that their technology was “brilliant” enough to make things happen.
However, Quibi faced significant challenges right from the beginning, with a pricing plan that was never really well thought out being a major contributor to its failure to attract subscribers. More amazingly they never had a basic stress-tested strategy for subscriber growth. Never bothered to engage in a content development digital marketing strategy so they never understood how people perceived value, or what they were willing to pay for it. Quibi never even took the time to research platforms like YouTube, Twitch and TikTok, identify the gaps and turn them into opportunities for its business model.
Despite raising $1.75 billion, an astronomical figure, Quibi never created a chance for itself. Management believed that a stunning app and A-List Hollywood original content was enough. Both Quibi and its Hollywood moguls investors and big tech mogul investors alike were arrogant, believing they knew more than the market. Never cared to find out what they didn’t know, so unawareness brought an epic flame out.
Strategy development can often protect you from yourself, your ego and quick and reactionary emotional-based thinking. Strategy is effectively System 2 thinking— from the 2011 book Thinking, Fast and Slow, by Noble Prize-winning psychologist Daniel Kahneman. The book’s main thesis is a differentiation between two modes of thought: “System 1” is fast, intuitive and emotional; “System 2” is slower, more deliberative, and more logical. So the strategy process is effectively System 2.
But to truly maximize the productive value of strategy development, a more focused and higher dimensional paradigm of information retrieval, augmentation and integration is required. A process that uses data-driven intelligent contextualization for comparative strategic value analysis. This effectively is what the applied intelligence (ai) methodology for strategy is all about.
…ai uses generative AI as an insight engine tool, making its capabilities accessible regardless of an individual’s professional or technical background. Its 6ai software empowers users to find their own insights and craft their own strategies at a fraction of the cost of using consultants. Designing anywhere from high-level multi-billion-dollar corporate strategies to personal growth strategies.
The goal of the applied intelligence | ai discipline is to enable those without technical backgrounds the ability to develop highly effective strategies without having to learn complex software or digital tools.
Here are four critical insights to understand towards developing effective strategy.
- Why. You can’t figure out a strategy unless you can clearly state what winning looks like, most especially, what winning looks like for your context and your organization.
- The Winning Conditions. Break things down into the different constructs that would create different ways to identify the optimal playing field for winning.
- Success. Understand how you will position the offering against competitors on your playing field: a. offer a lower-cost alternative in a way that you can afford and make a profit with. b. differentiate through a new and better offering? Or c. a combination of both.
- Implement. Have a realistic assessment and differentiate between the organizational capabilities that allow you to “play” in this area, vs. those that can allow you to compete at a high level and win.
In the end, strategy is the first principle for success in any endeavour in life. Never “wing it,” strategy increases your probability of success. Remember, it’s about what you do next that counts and strategy guides those critical steps along the journey, it helps to objectively observe reality and avoids fantasy thinking. And serves as an inherent risk management function. Moreover, the 6ai intelligent data-driven strategy development tool allows you to accentuate your competitive advantages with amazing speed, accuracy and precision. It informs and bolsters capabilities and management systems that are conducive to outperformance and long-term sustainable growth.
6ai, therefore, is the strategy tool for real entrepreneurs.
