Updated: Dec 12, 2020
Companies Fail to Succeed Digitally Even When Investing in Data Technologies. Why?
There is a question that we are constantly been asked when we present our company. If the concept and solutions we are working on are so good, why banks are not already doing it?
As I did not perform a robust academic research to base my opinion, I usually use some analogies as my answers. I can re-phrase the question: If banks can do everything, why do companies like PayPal, Revolut, Monzo, Transferwise, Robinhood, Ant Financials, and so many others, exist? If VISA is so good, why did Stripe appear and keep striving?
But I admit, this is still a fair question. Why traditional companies just do not do what so many newcomers are doing so successfully with so much less resources available for them? So I decided to find a deeper answer to this question than my sole opinion or my fallacy comparisons. In ‘Machine, Platform, Crowd’, written by A. McAfee and E. Brynjolfsson, I found my answer, brilliantly described by the authors just using a bit of historic data.
During the years of 1800’s in the UK, the industrial revolution, being led by the new machinery, was powered by steam. Never before has mankind been able to produce so much with so little effort. It was a massive automation revolution. However, number of new waves of technology is not a prerogative of our times. Around the 1900’s, a new power source appeared, the electricity. This event, obviously, represents a revolution by itself. According to the authors, for the disgrace of the steam companies, the owners of factories of that time completely misunderstood the true opportunity of this event.
Comparable to AI, electricity did not bring the automation as a concept, but had the potential to bring it to unimaginable levels.
Back to steam. Tormented by the coal bills, factory owners saw a magnificent opportunity of reducing 60% of their costs. With that in mind they transformed their factories by adapting electrical motors in their steam machines, making it modern and updated, to make is work faster and cheaper. Margins up!
Any similarities with AI adoption so far?
As it unfolded, all steam factories, now adopting electricity, and after having revolutionised the world, failed. Newcomers, who were using absolutely the same technologies, took the incumbents’ place in the market within just a few years.
And the question is, why did that happen?
So why did the owners of the steam factories could not stay alive after adopting the new power source? After all, they were the kings of the industrial revolution, ruling the world, and had all money at their disposal.
The newcomers built their factories from the scratch, using new perspectives, considering new possibilities, and looking at the opportunities that the new technology could provide. Smaller engines spread all over, replacing large machines, factories placed closer to the consumers, and so on. Conceptually, the electricity would allow to rethink not only the expenses, but the entire new way of producing goods, faster, cheaper, better. So, the new companies’ productivity skyrocketed due to new processes. New businesses appeared, still called factories, but not even compared to the steam ones when looked from the concept perspective. From the view from our current times, reducing coal bills seems to be a silly argument. The newcomers with the new technology in mind, building their companies around the new possibilities of the technology, made them achieve productivity levels with such lower costs, that incumbents just could not compete anymore.
More recent cases show that this way of thinking is not so unusual. The giant bookstore Barnes & Noble started selling books online simultaneously with small Amazon. If it didn't start earlier. They had a gigantic brand, strong distribution and all the necessary financial resources. But they could not understand what they were doing - or why. British travel agency Thomas Cook collapsed after 180 years, although it was making online sales, just because it refused to adapt to a business model that could extract the real value of what digital channels could offer. In both cases, the new technology was available to all of them. Of course, there are crazy cases where companies simply refuse new technologies, like Kodak - but this is another story.
This situation repeats itself with financial institutions and the adoption of AI and Machine Learning. We have seen so many financial institutions being bypassed by new entrants while they are investing multi-million-dollar budgets in digital transformation.
The biggest lesson learnt from history is that adopting the latest technologies is not enough and does not guarantee any success. It doesn’t matter how much money you throw in it. New technologies are tools that, if applied with the right strategy, they unleash productivity to the levels never seen before. It brings me to new ground-breaking approaches like the real-time customer-centricity in digital businesses like Amazon, Netflix, Spotify, AliPay - and the list just keeps growing
Let's not be fooled. History will repeat itself. Let's make sure we don't make history in this case.
Changing processes and rethink completely the business is a must for success. New productivity levels are achieved because of new thinking with AI. And AI success does not start in the IT departments. It starts in the CEO's minds and board's rooms. And finally, financial institutions are not data science companies. So that is why we keep working here at London Analytics to make the companies of the future being build around their clients, powered by AI.
Pablo Morales, CEO of London Analytics