22nd March 2021. Silicon Valley | Wages
The end of Silicon Valley?; living wages are good for businesses
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Tim O’Reilly has spent his entire life working in and around Silicon Valley, and has always been sharp about trends. He (or his company) is credited with inventing the phrase “Web 2.0”. So it’s worth paying attention when he asks, speculatively, if we are seeing “the end of Silicon Valley?”. It’s an extended essay.
He has four “predictions”, each of which point in this direction.
Prediction: The nexus of machine learning and medicine, biology, and materials science will be to the coming decades what Silicon Valley has been to the late 20th and early 21st century.
Here, he observes that the required skills for success in this sector are different, and (as Theranos demonstrated) it’s harder to maintain a hype bubble in the sciences sector. It’s possible that this sector will emerge in places that have leading research institutions in bio-sciences.
And:
Many Silicon Valley investors have been lucky rather than smart. They may not do so well in a world where capital must be directed toward solving hard problems rather than toward winning a popularity contest.
Machine learning is also a problem here. It can show correlation but not causation. “Real science”, as O’Reilly says, needs causal relationships to be identified.
Prediction: Because platform businesses have failed to regulate themselves, they will have limits placed on their potential for good as well as harm.
This is the longest section of the article, and perhaps the most heartfelt: “the tech industry set out to model something better. The generosity of open source software and the World Wide Web, the genius of algorithmically amplified collective intelligence are still there.”
In short, O’Reilly argues that the big Silicon Valley companies—in different ways, driven by their different business models—have ended up being too ruthless in their pursuit of ‘shareholder value’ and have left externalities everywhere. Which is the point at which regulators get interested. It would be in the tech companies own interests, he says, to
understand their social responsibility to create more value than they capture, focus their algorithmic systems on improving human welfare, find ways to measure and communicate the value that they create, and help our broader society to better “model and manage complex interacting systems.”
Prediction: There will be more climate billionaires created in the next two decades than in the internet boom.
Businesses that are aligned with decarbonisation are already growing rapidly. As O’Reilly adds, “who will get rich helping us transition to a new energy economy is unimportant compared to the question of whether we will summon the political will to make the transition in time to avoid the most disastrous consequences of climate change.”
Again, Silicon Valley’s mental models get in the way: a focus on efficiency doesn’t help.
A strong argument can be made that only a crash mobilization of the economy to electrify everything can get us there in time… As economist and former venture capitalist Bill Janeway said to me, mobilizations can get hung up and stalled out due to excessive concern with efficiency as the dominant metric of value.
More on Bill Janeway later this week. There’s great section here that summarises Rewiring America’s case for electrification as the answer to our urgent need to limit greenhouse gas emissions, which I recommend.
Prediction: When the bubble ends, greater opportunities will remain.
Silicon Valley’s current incarnation is a product of a decade of cheap capital.
There are two economies, often confused: the operating economy, in which companies make and sell products and services, and the betting economy, in which wealthy people bet on which companies will win and which will lose in the beauty contest that stock markets have become. In the operating economy, the measure of success is, as Nick Hanauer and Eric Beinhocker memorably put it, “the solution to human problems.”… In the betting economy, the measure of success is stock price, the higher the better.
But the money that is put into the betting economy isn’t investment, it’s just chips. When WeWork’s price collapsed, there was nothing left of SoftBank’s money, and nothing else either—no assets or patents that might have been repurposed.
Two quick thoughts: People who have read my blog will know that I am a fan of Carlota Perez’ model of how finance and technology combines to create long 50-60 year surges which reshape both economies and society. These follow an S-curve. One of the things that O’Reilly’s essay says to me is that the digital surge—50 years old this year—is running out of steam. Money will start looking for new sources of investment (and hence the points about biosciences or electrification).
The second is that there’s still going to be value in Silicon Valley, just as cars are still made in Detroit. Economic clusters are built on deep technical knowledge and practice, reinforced by social networks, supported by specialist services such as law and finance, and connected to research institutions. Despite complaints about California, and despite more virtually located workers, Silicon Valley is still going to be the place where the most complex software work is designed and managed.
(Thanks to Karl Wilding for the link)
#2: Higher wages are good for business
Just Capital published a chart that suggested that companies with a higher proportion of staff on the living wage also have a better return on assets [ROA-the blue bar], although it seems to have no effect on Return on Equity [ROE-the brown bar]. They explain the way they’ve made the calculation in the piece.
Of course, this could just be correlation, not causation. But the piece references a case study and underlying research from the Good Jobs Institute, which suggests that the following dynamic is at play:
[C]ompanies’ investments in living wages and complementary operations improvements drive worker engagement, which in turn drives productivity, and that ultimately creates value for shareholders. It has found that this has worked across different sizes of companies, and across all industries, including ones with notoriously low profit margins, like certain sectors of retail.
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