Houston, We Need a New Narrative
Andreessen, Ellison and the Half-Thought Thought
Marc Andreessen on the a16z Podcast last week ‘Can Tech Finally Fix Healthcare?’ with a16z colleagues Vijay Panda and Julie Yoo, riffing on why spending rises but outcomes stagnate in the $4 trillion “paradox” of multi-dimensional dysfunctionality called the American Way of Healthcare:
“Healthcare is like a fifth of the American economy and growing. If this process continues, it will eventually be half the economy and then the entire economy.”
Which sounds roughly like the call for urgent action to fix healthcare from President Nixon almost 60 years ago, when he proclaimed, “We face a massive crisis in this area.” Without prompt administrative and legislative action, he added at a special press briefing, “We will have a breakdown in our medical care system.”
Here’s how the crisis looks today:
The “Process” Continues
Strategic problems don’t have technical solutions because technology is a commodity input, more like electricity. It’s cheap and easily accessible to pretty much anyone with access to a computer and the Internet. Which is pretty much everyone. So all the AI-enabled revolutionary potential to transform, the promotional selfies and stories pouring down the mountain last week from Davos, are notable not for their novelty, but for the steady charge of message decay. And what it says about leaders confusing operations for strategy.
This is what happens when means conquer ends:
“We have the best healthcare in the world in terms of doctors, hospitals, pharmaceutical and medical device companies, but we certainly do not have the best outcomes,” said JP Morgan Chief Executive Jamie Dimon after winding down Haven, the Amazon-Berkshire-JPMorgan venture to “disrupt” health care, after less than 3 years.
The strength of an embedded system is not in its action, but its staying power.
And that staying power — the kinetics of strategic collapse or renewal — is determined by feedback loops. Understanding feedback and how to model feedback loops is an interesting technique — MIT teaches it as part a five-day course in solving complex problems with business dynamics modeling — but it’s also the kind of analysis that can quickly devolve into blow-up-your-brain complexity. It's hard to sell and scale. PA Consulting famously used system dynamics modeling as technique to help the United States understand the complexity of military strategy in Afghanistan, producing a slide that prompted Gen. Stanley A. McChrystal, the leader of American and NATO forces at the time, to remark: “When we understand that slide, we’ll have won the war.”
Here’s that slide:
You Can’t “Fix” This
Feedback loops are essential in nature.
Knowing they exist and self-produce helps understand “the process” beneath and behind all big system fails in any government + industrial complex: militarily in Afghanistan or economically with healthcare in the United States. Feedback loops are also the secret to sparking flywheels — the Holy Grail of Silicon Valley — and solve 'cold network' problems, the stuff of ecosystem genesis, the Amazon Way of managing itself as a self-generating market, where its positioning as a keystone (‘the keystone advantage’) gives Amazon its intellectual overmatch versus, say, strategically-collapsing Walgreens.
“With the advent of AI — which has disrupted the world — we have a unique opportunity to define the narrative for the future,” said Ravi Kumar, Cognizant’s chief executive, from Switzerland last week.
I get the impulse from the technology services industry, the inarguable general gist, but I don't see the novelty, the big idea, the different end around which to organize and give direction to all the technical means to get there.
“Disruption” plays to our impatience with structures and situations that seem to coast on habit and inertia. (Which, I would suggest, is what powered Donald Trump into office — anger is an energy, and he knows how to harness it.) But how the public, the press, and the politics respond to both technology and its industry depends on a sense of what our current categories are, what they're able to capture conceptually, and what they need to be adjusted to capture.
As a battlecry, “disruption” (and its first-cousin “transformation”) is one way that allows people to do this without getting into the messy details of definition. (What exactly is “the narrative of the future” and how do I buy it?) Disruption acts as if it thoroughly disrespects whatever existed previously, but in truth it often seeks to simply rearrange whatever already exists.
Its gestures are always radical but its effects never really upset the apple cart (excluding, of course, Donald Trump).
What Technology Calls Thinking
The only way to "fix" healthcare is assume you know nothing at the start, other than everything works and everything is broken and everyone has personal knowledge of the experience that needs correcting. We have all been to a doctor's office or visited a pharmacy, we have all dealt with government and commercial insurance plans. We are a nation of 300 million experts in healthcare.
Better to step off into a corner for a different review of reality, and then put in place a deliberate process of creative destruction, position yourself as a keystone to manage the tornado of “value” created from an N-sided market, to cohere and compete at a system level. Bring pieces and parts together in a unique pattern, create a new bundle of knowhow, position 'producing affordable health' at the center of thinking about strategy and economic competition, not "cutting cost".
And the way to do this?
Chop the Knot. Start with a clean slate. Reorganize markets to interoperate within the context of new economic systems.
“We just need to start over,” Blue Shield of California Chief Executive Officer Paul Markovich said when explaining the logic for replacing some of its drug procurement services from CVS Health. (His view is echoed by economists Liran Einav of Stanford and Amy Finkelstein of MIT, in their new book “We’ve Got You Covered: Rebooting American Health Care.)
And as I wrote recently in Fortune, ‘ripping up the playbook’ is the right approach.
“Unleashing exponential growth in the largest and most lucrative market on Earth starts by leapfrogging complexity. And if you buy into the logic that it’s not just one market that determines health care’s value but an infinite flow of them, then a strategic advantage goes to leaders with the skills to harness a number of interconnected markets and manage them as a new industry ecosystem.”
It’s the competitive mindset that needs a big rethink.
Which was the ‘structural break’ in Larry Ellison’s logic last week when he praised the potential of AI to produce cancer vaccines, prompting Moderna stock to surge more than 7 percent on the news (note: Moderna is still down following a disastrous 12 months, in which Moderna shed 60 percent of its share price):
During a meeting at the White House, President Donald Trump announced a $500 million investment in AI infrastructure, according to the Economic Times. The same meeting saw Ellison tout the impact AI has had on health care. He specifically called out cancer detection, treatment and cancer vaccines.
Ellison claimed using AI, a messenger RNA-based vaccine could be produced robotically in just 48 hours. Moderna is using its mRNA technology to develop a cancer vaccine in partnership with Merck (MRK). Moderna is using the same platform it used to create its Covid vaccine, Spikevax.
Pfizer has the same technical capability as Moderna, or has all the resources it needs to easily buy it. Ditto for GsK. Ditto for Sanofi. Ditto for Grail. Ditto for the more than 500 public and private healthcare and life sciences companies who presented their technical potential at this year's JP Morgan confab.
And all this technical potential -- to develop drugs more efficiently, to diagnose disease earlier -- will still run headlong into a system self-sustaining its stasis, powered by the kinetics of utilization management and prior authorization, the economics and practice of medicine defined and controlled by a very small handful, most notably Big PBM.
In the a16z Podcast, Andreessen and General Partners Pande and Yoo said they were asking “some of the biggest questions shaping the future of healthcare” [my answers in brackets]:
Is the solution to our healthcare crisis a policy, technology, or competition problem? [Yes]
Will AI and technology transform the industry, or are regulatory and structural barriers too entrenched? [No]
Who will crack the code — healthcare incumbents, tech giants, or AI-native startups? [Neither]
When it comes to cracking the mad riddle of healthcare, I would argue we are either asking the wrong questions, or our questions are based on the wrong framework.
Panic at the Disco
You can’t tech your way to “fixing” healthcare because of the deeper and wider set of feedback loops that are baked into a massive flywheel of dysfunction. It's become the defining feature of a global disfiguration: healthcare is "uneconomic" because of an obsession with cutting cost, which isn’t the same thing as producing health.
Our solutions are not mind-stretching enough because we have normalized cliché as objectives and as strategies. The magic leap to "economic value" is made by reframing the game. And that process starts with a different set of concepts around which to write better strategy stories.
Healthcare already is the economy, not something statistically separate from it.
In related news disrupting the Silicon Valley disrupters,, Meta Scrambles After Chinese AI Equals Its Own, Upending Silicon Valley, via The Information:
Artificial intelligence researchers at Meta Platforms have been in panic mode.
In recent days, leaders of some of the company’s AI teams openly worried that new conversational AI made by a Chinese hedge fund meant Meta was falling behind in the AI race. Leaders including AI infrastructure director Mathew Oldham have told numerous colleagues they are concerned that the next version of Meta’s flagship AI, Llama, won’t perform as well as the Chinese AI, DeepSeek, according to two Meta employees with direct knowledge of efforts to catch up.
Which only proves the maxim proven since time immemorial: technology is never decisive and is often strategically distracting.
More to the panic-inducing point triggered by DeepSeek:
Technology-led visions are the short road to competitive convergence, not competitive advantage.
When everyone has access to the same amazing technology, and everyone uses the same amazing technology in the same amazing way, you get a sea of sameness at an amazing scale.
/ jgs
John G. Singer is Executive Director of Blue Spoon, the global leader in positioning strategy and innovation at a system level. Blue Spoon specializes in constructing new industry ecosystems.