The Baseline Question Nobody Asks First
When the Department of Government Efficiency announced it had identified over $55 billion in potential savings by early 2026, the political reaction split almost perfectly along partisan lines. Conservatives celebrated the discovery of waste in the federal machinery. Critics called it accounting fiction. Both responses missed the more fundamental question: what exactly are we measuring, and against what baseline?
This matters because federal workforce analysis sits at the intersection of several different policy conversations that don’t always align. We’re simultaneously asking three separate questions: how much money can the government save, how many people will lose their jobs, and how will the delivery of federal services actually change? Those aren’t the same question, even though most political commentary treats them as interchangeable. A contract cancellation might save money without eliminating a single job. A buyout offer might reduce headcount while actually increasing per-person costs. The federal government employed approximately 2.3 million civilian workers before these initiatives began, according to Office of Personnel Management Workforce Data, but raw employee numbers tell you almost nothing about whether government is actually smaller or more efficient.
Understanding what DOGE actually accomplished means moving past headline numbers and into the specific mechanisms through which workforce reduction happens. That’s the only way to see what changed and, more importantly, what didn’t.
The Buyout Numbers and What They Actually Mean
Approximately 75,000 federal employees accepted the Office of Personnel Management’s deferred resignation buyout offer in early 2025. That’s a real number representing real people making real employment decisions. If you’re a federal employee in most parts of the country, that’s probably someone you know or worked with. The buyout offered monetary incentives to encourage voluntary departures, and for many mid-career workers facing uncertainty about their job security, it seemed like a reasonable exit.
But here’s where the complexity begins. Losing 75,000 employees from a workforce of 2.3 million represents roughly a 3 percent reduction. That’s significant, but it’s also roughly equivalent to normal attrition rates in many government agencies across a normal year. The difference is that normal attrition happens gradually and somewhat randomly, while this happened concentrated and intentional. That concentration matters. If those 75,000 departures landed in specific agencies or specific skill areas, the impact could be disproportionate. If they spread evenly, the effect would be more muted. The available data doesn’t tell us enough about that distribution to make firm conclusions about service impacts.
More importantly, buyouts are expensive in the near term. You’re paying people to leave. That’s different from simple attrition, where you just stop filling positions. The money spent on buyouts doesn’t necessarily show up as “savings” in the first year, even if it reduces future payroll costs. It’s a present-tense expense meant to generate future savings, and whether that trade-off was actually worthwhile depends entirely on whether the positions stay vacant or get refilled, and at what level.
The Savings Claim and the Accounting Question
When independent analysts began examining DOGE’s $55 billion savings estimate, they found methodological problems that reveal how slippery “savings” can be as a concept. The Congressional Budget Office identified a particular issue: many of the savings claimed involved contract cancellations that had already expired or already been completed. Those aren’t savings in any meaningful sense. They’re contracts that were ending anyway. Counting them as new savings is like claiming credit for not renewing your gym membership in December and calling it a financial achievement you personally engineered.
You can explore the broader analysis at the Congressional Budget Office Federal Workforce Analysis page, which breaks down how federal workforce changes actually affect budget totals. The accounting gets particularly complicated when you factor in severance costs, early pension payments, and the administrative expenses involved in mass departures. Letting people go costs money upfront, even when the long-term goal is saving it.
Here’s the part that matters for your local community specifically: contract cancellations hit contractors differently than they hit federal employees. A cancelled contract with a defense contractor in your region doesn’t just mean reduced federal spending. It means jobs lost at that contractor, reduced tax revenue, and economic ripple effects throughout the area. A federal employee buyout means someone stops drawing a federal paycheck but might find work elsewhere in your local economy. The impact isn’t uniform, even though the savings number treats it as such.
What Courts Actually Blocked, and Why That Matters
Throughout 2025, multiple federal courts issued injunctions blocking various orders directing agencies to restrict access to records, information systems, and in some cases their own facilities. This legal pushback didn’t make headlines the way the workforce reductions did, but it might be more consequential for what actually happened on the ground.
When courts block agency access orders, they’re essentially saying that whatever efficiency gains you’re pursuing can’t override existing legal requirements. A judge doesn’t care about your savings estimate if you’re violating the Administrative Procedure Act or the Freedom of Information Act to achieve it. That means some of the operational changes DOGE wanted to implement simply couldn’t happen, regardless of whether they would have saved money. Your local FBI field office can’t restrict public record requests because Washington decides that’s more efficient. Your regional Social Security office can’t eliminate specific programs because a federal agency decides they’re redundant.
The injunctions created a partial implementation problem. DOGE could pursue workforce reductions and contract cancellations through legal mechanisms like the buyout offer. But it couldn’t pursue operational restructuring through executive order if those orders violated statutory requirements. The actual changes were constrained by law in ways the initial policy announcements didn’t acknowledge. Some of the efficiency vision was unrealizable from the moment it was announced.
What Changed and What Didn’t: The Real Story
After a year of DOGE initiatives, the actual federal workforce is smaller. That’s verifiable. Approximately 75,000 people accepted buyouts, and those positions haven’t all been refilled. Some savings came through contract cancellations, though many of those overlapped with ordinary contract expirations. Some operational changes went through, though courts blocked others. So something clearly happened.
But whether that something constitutes the transformational federal efficiency that supporters claimed, or just incremental workforce adjustment, depends almost entirely on what you measure and when. The 3 percent workforce reduction is significant if you’re one of those 75,000 people or if you live in a region where those jobs concentrated. It looks modest when you evaluate it as a percentage of total government employment. The savings claims are large if you’re credulous about the methodology and much smaller if you scrutinize the accounting. The operational changes were real where courts allowed them and nonexistent where courts didn’t.
What we actually know is this: the federal government is smaller than it was, some contractors lost work they expected to continue, some people made difficult employment decisions under pressure, and courts preserved legal requirements that limited how far efficiency could be pursued. That’s the real story, one more complicated than either cheerleading or categorical dismissal. The question worth asking now is whether any of that actually changed how government works in your community, and whether those changes made services better, worse, or just different.