The Real Reason 81% of Health System Leaders Are Frustrated With Their Own Organizations
The number that should stop every healthcare leader cold:
81%.
That's the share of U.S. health system C-suite leaders — CEOs, CFOs, COOs, CMOs — who say their current operating model is not effective or efficient.
Not a minority. Not a fringe concern.
Four out of five leaders, across systems of every size, surveyed by McKinsey in May 2025, expressing dissatisfaction with the very structure through which their organizations operate.
And yet, 48% of those same leaders have already redesigned their operating model in the past two years. Another 31% are in the middle of a redesign right now
They're changing. And still, it's not working.
That gap — between effort and outcome — is the real problem worth examining.
What leaders say is broken
According to McKinsey's Provider Operating Model Survey, published March 6, 2026, the challenges health system leaders cite most often are not what most would expect:
→ Ineffective decision-making and prioritization
→ Costly and complex structures with limited integration
→ Duplicative or unclear distribution of responsibilities
→ Insufficient training for leaders to navigate uncertainty
→ Lack of agility and data-backed performance metrics
→ Inconsistent use of technology and AI
Notice what's missing from that list.
Not "we don't have enough technology." Not "we need more AI tools." Not "our software is outdated."
The problem is structural. It lives in how decisions are made, who owns them, and how accountability flows — or doesn't — through the organization.
McKinsey puts it plainly: 52% of surveyed leaders said 11 or more people are involved in making systemwide decisions. 38% said their organizations have established at least nine committees just to support decision-making.
When decisions require that many people, they don't get made. They get diluted.
The operating model is a decision system
This is the insight most organizations miss when they attempt a redesign.
An operating model is not an org chart. It's not a process map. It's not a technology stack.
An operating model is the structure through which an organization makes decisions — consistently, at scale, under pressure.
When that structure is broken, everything else breaks too. AI tools underperform. Talented leaders disengage. Growth stalls. Margins compress.
McKinsey's research confirms this. According to their analysis, structural and operational failures — compounded by macroeconomic pressures — could compress health system margins by more than 1,500 basis points. The financial stakes of a broken decision system are not abstract.
And the fix isn't more technology layered on top of a broken structure.
As McKinsey notes in the same study, organizations that redesign end-to-end workflows around how decisions are made — rather than simply adding tools — see the greatest impact on their bottom line.
Why AI alone won't solve this
This is where many health systems are making a costly mistake.
They invest in AI. They pilot tools. They stand up committees to govern those tools. And then they wonder why adoption stalls and ROI doesn't materialize.
The answer is simple: AI doesn't fix unclear decision rights. It amplifies them.
If your organization doesn't know who owns a decision, an AI system won't clarify that. It will produce outputs that nobody acts on, or that three different people act on in three different ways — compounding the inconsistency rather than resolving it.
An AI-native organization — one that actually captures value from intelligence embedded in its operations — first requires a decision system that is structured, clear, and consistent. AI then accelerates that system. It learns from it. It improves it over time.
But the system has to come first.
Three things that actually move the needle
McKinsey identifies three critical areas for building a high-performing operating model. At Soluntech, we've seen these same patterns across the organizations we work with — in healthcare and beyond.
1. Structural clarity: who owns what
High-performing health systems are moving toward federated models — centralizing strategy, standards, and governance at the system level, while preserving execution flexibility at the local level.
This isn't full centralization. It's disciplined clarity about what gets decided where and by whom.
The key question every leader should be able to answer: for each critical decision in my organization, who decides, who advises, and who executes?
If the answer involves a committee, a consensus process, or "it depends," the decision system needs redesign.
2. Decision-making speed and discipline
McKinsey found that organizations that simplify their decision infrastructure — reducing standing committees, clarifying decision rights, training leaders on a common language for accountability — move faster and make better decisions.
This is not about cutting corners. It's about removing the structural friction that slows organizations down without adding value.
The organizations winning in today's environment have made decision speed a competitive advantage. Not by moving recklessly, but by removing the unnecessary complexity that makes every decision feel like a negotiation.
3. Talent aligned to value
McKinsey's research shows that fewer than 10% of healthcare CEOs know which 30 to 50 roles drive the most value in their organization — and whether they have high-performing people in those roles.
An operating model is only as strong as the people executing it. Redesigning structure without redesigning how talent is deployed, developed, and retained is redesigning the blueprint without building the house.
What Soluntech does differently
At Soluntech, we work with organizations to build the decision systems that make peak performance possible.
Not tools on top of broken processes.
Not AI features added to existing structures.
We start with the system: how decisions are made, where they break, who owns them, and how intelligence can be embedded to make them faster and more consistent over time.
Our approach is AI-native by design — meaning we don't bolt AI onto what already exists. We help organizations redesign how they operate so that intelligence becomes structural, not decorative.
For health systems specifically, this means:
→ Mapping where decision risk is highest and most costly
→ Redesigning the workflows and accountability structures around those decisions
→ Building the data and intelligence layer that allows those decisions to improve over time
→ Ensuring the operating model can scale without depending on heroic individual effort
The result is an organization that doesn't just survive margin pressure and macroeconomic volatility — it builds the structural resilience to navigate it and come out stronger.
The bottom line
McKinsey's survey makes one thing clear: the urgency is real, the awareness is there, and the investment is already happening.
What's missing is the right frame.
Health systems don't have a technology problem. They have a decision system problem.
And solving a decision system problem requires more than a new tool, a new committee, or a new org chart.
It requires rebuilding how the organization thinks, decides, and acts — at every level, consistently, at scale.
That's the work. And it's the most important work any health system leader can do right now.
This article draws on insights from McKinsey's Provider Operating Model Survey (May 2025) and the McKinsey Healthcare Blog article "What it takes to build a high-performing health system operating model" by Jung Paik, Michael Elliott, and Philippa Duffy, published March 6, 2026. All data and survey findings cited are attributed to McKinsey & Company.
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