The Power and Hidden Danger of Strategic Assumptions
Inviolable truths about the limits of technology govern every industry… until they don’t. “You can’t do that with client data” will soon be one of them…
Are consumer-grade camera manufacturers stupid?
No.
And yet they have presided over a near total collapse in sales in the last decade, and are experiencing profit shrinkage of existential proportions, with some of them exiting the industry entirely, by selling their assets at what must surely be fire-sale prices.
Consumer-grade camera sales have collapsed. How could the manufacturers sit back and just watch? Source.
This means they must have been watching the smartphone revolution and yet concluded they could either retain a profitable niche or perhaps even outlast it as a passing fad.
What was going through their minds?!
What were they thinking when they saw the emergence of smartphones with cameras of ever greater resolution?
Couldn’t they see that the only future that faced them was oblivion?
I have a theory.
I suspect they looked at the form factors of smartphones and correctly concluded that the compromises needed to fit the lenses inside the body meant the optics would always be worse than ‘real’ cameras. It was perfectly reasonable to conclude from this that there would always be a good market for cameras that could take ‘high quality’ pictures, with the phones filling the high-convenience, low-quality, commodity niche that they didn’t want to compete in anyway.
Software and CPU power means that optically inferior smartphones can outperform purpose-build cameras for all practical purposes.
But what they perhaps failed to appreciate were the advances in CPUs and software that would mean the photographs most people can take on the latest iPhones are better than they could ever have achieved with a standalone device.
Far from populating the low-value niche below standalone cameras, smartphones leapt ahead and relegated the standalone cameras to commodity status!
The manufacturers were right: there are hard physical limits on what the optical portions of smart phone cameras could ever achieve. But the ‘wildcard’ of advancements in software and CPU power meant the inviolable truth that ‘real’ cameras can always outperform commodity cellphones was neither true nor inviolable.
Technology Often Dictates Market Structure
Here’s another example: life in the London taxi industry used to be so simple. If you had a ‘black cab’ license you could pick up passengers on the street. Or you could get a ‘minicab’ license and focus on customers who had pre-booked. Two worlds. Two business models. No overlap.
If you can instantly match supply with demand and have pervasive connectivity, then the distinction between “black cabs” and
“minicabs” dissolves…
“That’s just the way things are.”
Until they weren’t.
We all know how the Uber story played out but we don’t always ask ourselves why and why then.
My answer is the emergence of pervasive connectivity and smartphones. You needed both.
A key insight on which Uber was built was that if passengers and drivers have pervasive connectivity then nothing stops you driving the time from ‘booking’ to ‘pickup’ to as close to zero as you like.
You can provide a ‘hail from the street’ experience under the licensing regime of ‘prebooking’ if you know where the drivers are at all times and the passengers have such confidence in the cellular network that they don’t worry about ‘booking’ until they’re ready for their ride.
You needed to believe that is where technology was heading or you couldn’t have pulled it off. Nobody could have justified the eye-watering investment in marketing, and driver and passenger incentives, without that belief.
In short: “minicab firms can’t do on-street pickups” was an inviolable truth until Uber and others saw where technology was going and realized it wasn’t going to be true much longer.
There are many examples of this sort of phenomenon when you start looking.
For example, it may turn out that 2020 proves that the ‘inviolable truth’ that companies need headquarters buildings also turns out to be false.
But, if it is false, it will only be because bandwidth and communications technologies have reached the right level of maturity.
It can be fun to find examples of this sort of thing in history too.
The entire structure of agricultural markets is driven by assumptions around our ability to predict the weather.
Thales of Miletus realized the prevailing wisdom that weather could not be predicted was wrong. And he profited handsomely when he acted on this insight. He correctly foresaw there would be a bumper olive harvest and bought up the right to use all the presses months ahead of anybody else.
Another example of something people saw as an ironclad fact of life—“you can’t reliably predict the weather”—that resulted in the restructure of an entire market when technology proved the assumption to be false.
What these examples all have in common is that the structure of entire markets is often determined by deep-baked assumptions about the nature and limits of technology.
“Nobody will ever have a permanently-connected super computer in their pocket.”
“The physics of light means a smartphone camera can never outperform a standalone camera.”
“The inadequacies of video-conferencing mean the commercial property market has to keep throwing up tower blocks in business districts.”
“Nobody can make even directionally correct predictions about this year’s harvest so nobody can buy hedges or sell futures.”
And here’s the scary thing: we often don’t even realize we’re making these assumptions.
Take the world of ‘customer data’. Every firm has to deal with it.
Some firms’ businesses are based on it.
If you’re a stock exchange, your job is literally to store and process data from multiple customers, to identify pairs whose desires to buy and sell exactly match each other.
If you’re a fraud analytics firm, your job is to take lists of payment transactions from banks and scan them for evidence of money laundering or other illegal activity.
Customer-provided data is the lifeblood of these firms. It’s what makes them useful and valuable. And yet it’s also very risky. It can be hacked. It can be misused. It can be inadvertently commingled with inappropriate datasets.
It’s a wicked tradeoff: your business depends on access to sensitive data, and yet your business can also be destroyed if you don’t respect it!
So, many of these firms have built their businesses on the basis that there are some things they just aren’t allowed to do. There are some data sets your customers will never let you have. There are some data aggregations, especially across your customers, that you will never be allowed to do.
And here’s the thing: this is going to look just as misguided in a few years as failing to anticipate the revolution in photography that was unleashed when ‘software ate the world.’
The most corrosive of these assumptions are the ones where you say: “we’d love to provide this service but the customer data we need is just too hot to handle. We just can’t risk having it in the first place.”
When you send data to somebody else, there is nothing technological you can do to control how they use it. Or at least, not until now…
These assumptions are, of course, not misplaced. Data doesn’t come padlocked as if in a straitjacket that allows it to be used for one purpose, but nothing else. Once you have it, you can do anything with it. And this means so can a rogue employee, a poorly trained intern, a malicious hacker or a distracted programmer.
It doesn’t matter how valuable the service you envisage might be, the risk that the data could fall into the wrong hands or be used for a prohibited purpose is just too great. Those sorts of data are just too hot to handle.
But what if that assumption was false?
What if it were possible for your customers to wrap their data in a straitjacket before they sent it to you? What if it were possible to control exactly how customer data will be used and to be able to prove this to your customers before they sent it to you?
What new services could you offer if you unleashed yourself from fear? What groundbreaking new insights could you discover for your clients—or for the whole market—if you could safely combine datasets from different customers with their full knowledge and permission, because they were assured that was all you would do with it?
Could you identify suspicious payment transaction graphs that spanned dozens of banks but which looked entirely legitimate in isolation? Could you operate a provably fair ‘dark pool’ for under-served markets?
What could you do for your customers if you could prove to them exactly how you would use their data… where you didn’t have to worry about what else could happen to it whilst in your custody?
Well, you have to wonder no longer. Because such a thing is now possible. Confidential Computing is a technological breakthrough that allows customers to put a ‘straitjacket’ around their data and control how it will be used.
And Conclave from R3 puts this power into the hands of your own analysts and developers.
Thanks to Rusheb.
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