The majority of what payers identify as 'care gaps' are actually 'data gaps'—a lack of information leads to an assumption of missing care. By solving the data acquisition problem first, organizations can distinguish between the two. This dramatically shrinks the problem set, focusing expensive outreach efforts only on patients with true care needs.

The government's standard procedure is to disburse funds and attempt to recover improper payments later—a highly inefficient process that costs hundreds of billions annually. A more effective system would require real-time prepayment verification, defaulting to "no pay" if eligibility cannot be confirmed, preventing fraud before it occurs.

Shutdowns halt the release of key data like jobs reports and inflation figures. This obstructs the Federal Reserve's ability to make informed interest rate decisions, creating market uncertainty. It also delays Social Security COLA calculations, impacting millions of retirees who rely on that data.

Social Security is framed not just as a successful anti-poverty program, but as a system that annually moves over a trillion dollars from the younger, less wealthy working-age population to the most affluent generation in history, who are often asset-rich.

Recent breakdowns in student loan processing, AI governance, and cloud infrastructure highlight the vulnerability of centralized systems. This pattern underscores a key personal finance strategy: mitigate risk by decentralizing your money, data, and income streams across various platforms and sources.

The primary reason multi-million dollar AI initiatives stall or fail is not the sophistication of the models, but the underlying data layer. Traditional data infrastructure creates delays in moving and duplicating information, preventing the real-time, comprehensive data access required for AI to deliver business value. The focus on algorithms misses this foundational roadblock.

A significant source of waste stems from "zombie payments"—recurring government funds that continue indefinitely without review. When the official who authorized the payment leaves, retires, or dies, there is often no system to shut it off, creating a perpetual drain of funds to companies or individuals who rarely report it.

The traditional approach of building a central data lake fails because data is often stale by the time migration is complete. The modern solution is a 'zero copy' framework that connects to data where it lives. This eliminates data drift and provides real-time intelligence without endless, costly migrations.

To improve federal efficiency beyond partisan politics, Oliver Libby proposes creating a Chief Operating Officer for the U.S. government. Modeled after the long-term, cross-administration tenure of the Fed Chair, this role would focus on making government work better for citizens regardless of who is in power.