Nowadays, it is hard to be in the startup world and not hear the buzz words: blockchain, artificial intelligence, and big data. Thus, it is very natural to have FOMO that if you don’t adapt any or all of these technologies for your startup venture, your solution will not be competitive long-term.
In this article and corresponding video, we discuss whether these fears are justified and how you should position your company for long-term success.
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Blockchain
Blockchain has become very popular with the rise of Bitcoin in 2017 and a flurry of Initial Coin Offerings, or cryptocurrencies, which served as mediums of exchange to access various blockchain systems. The nascent blockchain market got overheated and predictably crushed soon after peaking. Fortunately, we are now in the era of more responsible capital allocation, more transparency and more clear and comprehensive regulation, all of which are positive drivers for the future growth of blockchain applications.
What does it mean for you?.
There is no question that blockchain technology is revolutionary and has the potential to completely transform multiple industries – financial services, supply chain, healthcare, entertainment, just to name a few.
That said, even if you are operating in those industries, it does not automatically mean you should rush to adapting that technology. You must first have a robust use case justifying the use of a distributed ledger, which lies at the core of blockchain. You further must have a separate use case for the use of cryptocurrency, because not every blockchain solution needs its own medium of exchange.
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Artificial Intelligence
Artificial intelligence is the way of the future. At this point there is no doubt that it will be a huge part of our lives. Elon Musk recently unveiled the progress of one of his ventures, Neuralink, which is working on creating an interface between a brain and a computer. It’s only a matter of time before his or another venture succeeds in doing that, thus transforming the world, as we know it, forever.
What does it mean for you?
Just like with blockchain, not every business solution needs artificial intelligence, and even more importantly, not every business solution needs artificial intelligence right away. In fact, it can be very difficult to create the right data set and the right algorithm to train the AI in order for it to provide value. As we have seen in the case of X.AI, a virtual artificial intelligence assistant, even such simple tasks as scheduling meetings can be quite complex to implement.
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Big Data
Data is the king. Everyone collects data and everyone tries to sell it. However, all data is not good data. And even good and relevant data can only add value if:
- There is enough of it
- You know how to process it, and
- You can provide data insights that others cannot.
The first two requirements are sufficient for internal use, but all three are necessary for the data to become a meaningful revenue stream. Further, to achieve all three, you may need a significant time and capital investment which you may not be in a position to make.
Conclusion
You should not adapt a technological solution only because it is “hot” or others are using it, without conducting thorough comparative costs and benefits analysis and creating a robust use case for its use. Always focus on your core value proposition first.
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About Author
Victoria Yampolsky, CFA, is the President and Founder of The Startup Station, a comprehensive resource for modeling and valuing early-stage startups. She evaluates the financial feasibility of business models and specializes in the financial modeling and valuation of pre-revenue companies. She also created a finance curriculum for early-stage founders and launched The Startup Station’s educational program in 2015. Since then, more than 1,000 founders have attended her online and in-person finance classes and learned the basics of financial modeling, valuation, and startup financing.
Previously, Victoria worked for the Deutsche Bank Research Department and performed IT consulting for CapGemini’s Financial Services Division. Victoria holds a Bachelor’s Degree, Cum Laude, in Computer Science, with a minor in Mathematics, from Cornell University and an MBA, with honors, from Columbia Business School. Victoria is also on the Advisory Board of the Computing and Information Science (CIS) Department of Cornell University.
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