Making Government Efficient Is Harder Than It Sounds

The DOGE experiment reveals some public decision-making challenges

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From budget hearings to political debates, one of the more reliable applause lines is the promise to “cut government waste.” And while Americans may disagree on the size and role of government, a majority—usually somewhere between 55 and 65 percent—say they support the idea of increasing government efficiency (e.g., King, 2025; Newport, 2024; Pew, 2024; Stagwell, Inc., 2025). That makes the Department of Government Efficiency (DOGE) an interesting case study. It seems to offer exactly what most people say they want: a leaner government.

But that support starts to waver once you dig into the specifics. Ask people about how efficiency should be achieved, what should be cut, or who is driving the effort, and the numbers shift—sometimes dramatically. While there may be support for the idea of efficiency, that doesn’t necessarily translate into support for the actual execution of measures intended to improve efficiency. That gap between concept and implementation reveals something important about human decision making.

At its core, the ongoing saga of DOGE and its mission to make government more efficient highlights a couple of issues that align closely with the themes I’ve explored in many of my posts on decision making. First, there’s often a misalignment between the ends people claim to support and the means they’re willing to accept to get there. Second, there’s far less agreement than we might expect about what should be cut in the name of efficiency. Together, these issues reveal why seemingly straightforward decisions—like eliminating government waste—are anything but.

The Means-Ends Problem

Majority support for government efficiency suggests a shared goal—but shared goals don’t guarantee shared support for the path to get there. And in the case of DOGE, much of the friction comes not from the idea of cutting waste itself, but from how those decisions are made, who is making them, and what gets prioritized in the process.

For example, King (2025) reported on polling data showing that while more people generally agreed than disagreed that the idea of DOGE was a good one, DOGE’s popularity was more negative than positive. How can that be?

Some of the reason may come down to execution—hence, the means-ends problem.

While some view DOGE’s actions as necessary and long overdue, others have raised concerns about the speed and scope of the department’s cuts. Critics argue that decisions appear abrupt or ideologically motivated, with limited transparency about the criteria used to determine what qualifies as waste (Elliott, 2025; Heath & Reid, 2025; Hernandez, 2025). The approach has at times been described as disruptive, even reckless—a kind of bull-in-a-china-shop strategy that prioritizes quick action over careful deliberation.

This reveals a central issue in public decision making: even when people support a general goal like reducing waste, that support often depends on how the process unfolds. People care not just about outcomes, but about the way those outcomes are pursued. If the process feels top-down, unbalanced, or politically charged, trust erodes—even among those who initially support the goal. What starts as a broadly supported effort to “cut government waste” can quickly become a source of public controversy—not because the goal changed, but because they dislike the means of getting there.

People don’t just evaluate outcomes—they evaluate how those outcomes come to be. When the process feels unfair or opaque, people are less likely to accept the result, even if it aligns with their stated goals. This is the Fair Process Effect (an effect originally coined by Folger et al., 1979), and it helps explain why getting what we want may be far less satisfying than we’d expect—and why not getting what we want may feel less upsetting if we believe the process was fair¹.

Fairness of process matters because it signals whether decision makers considered relevant input, weighed competing values (more on that in a minute), and applied consistent reasoning. When that’s missing, people don’t just disagree with the outcome—they question the effort itself. In this way, fairness essentially becomes a heuristic we use to evaluate the validity of the decision.

We often don’t have the time, information, or expertise to evaluate the specifics of a policy decision. So instead, we ask ourselves: Did the process seem fair? If the answer is no, we're more likely to dismiss the outcome—regardless of its merits (See, 2009). That’s especially true in politically or emotionally charged situations, where trust in institutions is already fragile. When fairness is perceived to be lacking, people stop assuming good intent and start looking for other, less benign, motives.

It's also worth noting that Elon Musk—while he may not be directly responsible for DOGE's day-to-day decisions—is nonetheless closely associated with the initiative. And Musk, as a public figure, is nothing if not polarizing. For some, his association lends credibility to the effort: disruption in the name of innovation. For others, it raises red flags about motive, ideology, and the potential of overreach.

It should be unsurprising that views on Musk are split based on ideology, with 73% of Republicans possessing favorable views and 85% of Democrats possessing unfavorable views (Pew, 2025). And this split tends to mirror the splits we see in people’s views about DOGE itself. Even if Musk isn’t actively shaping the process, his proximity to it biases people’s views of the department’s actions. And because Musk has been a vocal supporter of Trump, it opens the door to ideological thinking becoming a driving force behind people’s views². Inferences—valid or not—about how decisions are made may hinge less on the facts and more on who people believe is behind the curtain (Bianchi et al., 2015).

Disagreement About What Counts as Waste

Even if everyone agreed on the need to reduce government waste—and they don’t—there would still be the thorny issue of what actually qualifies as waste. One person’s bloated bureaucracy is another’s essential service. One program may seem redundant from the outside but irreplaceable to the community it serves. And so, while the general idea of cutting waste polls relatively well, the moment we get specific, support begins to fracture.

This isn’t just about policy differences—it’s a reflection of the values, experiences, and priorities people bring to the table. Everyone brings a different frame of reference to the issue. They evaluate trade-offs not in abstract terms, but through the lens of what matters to them personally³.

That frame of reference can also shape motivated reasoning. Someone who benefits from a student loan program may view it as a public investment⁴; someone who doesn’t may see it as government overreach. The same goes for arts funding, agricultural subsidies, scientific research, and hundreds of other budget items.

And then there’s employment. As soon as efficiency measures start leading to actual job losses—especially in visible or emotionally resonant sectors—public support takes a hit. We can see this in polls showing that, even though a majority supported DOGE’s work, a majority also disapproves of how it’s handling the federal workforce (Nguyen, 2025; Oliphant & Lange, 2025).

Support for "cutting waste" softens when the cuts start to feel personal or when the human cost becomes more salient. In those moments, what looked like sound fiscal policy on paper begins to look more like harm. Efficiency may still be the goal, but now it carries a price that feels harder to justify. And the more these personnel cuts come to agencies or services seen as beneficial to people, the more the people worry that services they (or groups they care about) rely on will be adversely affected⁵.

In the end, disagreements about what counts as “waste” are really disagreements about purpose—sometimes, but not always driven by ideological thinking. What is government for? What outcomes are we willing to pay for collectively? These are fundamentally value-laden questions, and trying to answer them with spreadsheets alone is bound to fall short.

DOGE, by positioning itself as a force for efficiency, steps directly into this terrain. And when the department makes cuts to various programs—especially those that can easily be framed as political⁶—it’s not just the program that comes under scrutiny. It’s the values behind it⁷. The result is that what began as a debate about efficiency becomes a referendum on priorities, fairness, and sometimes even identity.

That said, not every cut is controversial. In fairness to DOGE, some targets appear hard to defend. One example cited by the department involved over $580 million in terminated contracts and grants, including an HR IT development program that was reportedly $280 million—or 780%—over budget and five years behind schedule, with at least two more years to go (DOGE, 2025). Cuts like that are the kind many people would likely support, regardless of ideology.

But even those kinds of cuts raise a difficult question: Will they actually accomplish the larger goal? While eliminating some egregious budget lines makes for good headlines—and may be justified on its own terms—it’s unlikely to produce the kind of systemic savings needed to significantly reduce the overall cost of running the federal government. And so, if DOGE is actually going to make government notably more efficient, cuts will have to come from areas where there is far less agreement about the worthiness of cuts.

And this leads to a double-edged sword. On the one hand, cutting in places where there’s likely to be values conflicts leads to an erosion of support. But on the other hand, if the optics of efficiency outpace the actual impact—resulting in minimal efficiency gains—there will be an erosion of support. In either case, the result may be the same: a public perception that the process was flawed or the priorities misplaced.

The Efficiency Trap

DOGE’s story offers a case study in what makes collective decision making so complex. The broad idea of cutting waste sounds simple—even obvious. But translating that idea into policy action reveals just how much our evaluations are shaped by process and values. The moment cuts become concrete—the moment jobs are lost or services are affected—people stop thinking in terms of abstract efficiency and start reacting to the personal and societal implications.

Say what you will about the personalities leading this effort (i.e., Musk and Trump), but many of the same challenges would arise no matter who was in charge. What would likely differ is who supports it and who doesn’t. That’s because our reactions aren’t just about policy—they’re often shaped by ideological thinking. When we strongly identify with the person or party behind a decision, we’re more likely to defend it. When we don’t, we’re more likely to scrutinize it, question its legitimacy, or reject it outright.

But even if ideological thinking were removed from the mix, values-based motivated reasoning wouldn’t disappear. The federal government’s decisions ultimately impact all U.S. residents to some degree—whether directly through funding and regulations or indirectly through shifts in policy priorities. People are naturally inclined to scrutinize decisions that they believe could negatively affect them, and they often interpret those decisions through the lens of their own interests, values, and priorities.

Hence, even in the absence of overt ideological thinking, individuals and groups will still find reasons to challenge cuts or policy shifts that threaten their perceived well-being, security, or economic stability. This tendency is less about partisanship and more about the fundamental way people respond to perceived losses, reinforcing the idea that political debates are rarely just about the policies themselves, but also about who benefits and who bears the cost.

Certainly, reasonable people can and do debate the merits of particular cuts, and it would be impossible to eliminate motivated reasoning from these discussions. After all, any decision about what to cut (or what to preserve) is shaped by value judgments, and perfect consensus is rarely achievable. While ideological thinking may amplify these disputes, the underlying tensions would persist even in its absence.

And that’s the trap: to achieve its stated goal, DOGE has to make hard decisions—the kind that involve real trade-offs and affect real people. But those are also the kinds of decisions most likely to erode the very support the department depends on. The moment efficiency becomes painful, public sentiment begins to shift. And once people believe the process is unfair or the values behind the cuts are misaligned with their own, it’s no longer a debate about waste—it’s a debate about legitimacy.

From a decision-making standpoint, that’s the real challenge. People don’t just judge outcomes. They judge how those outcomes were reached, who was involved, and whether the trade-offs reflect priorities they recognize as valid. If DOGE can’t bring the public along on those dimensions, it may struggle to build the kind of durable support any efficiency effort needs.

In the end, the success of reform efforts like DOGE may depend less on identifying waste and more on how the process of cutting it is perceived—and whether people believe the end truly justifies the means.

1. I wrote a post for Psychology Today that, at some point, I will expand on for Substack. But until then, you’ll have to settle for the Psychology Today version.

2. Musk has done himself no favors in this regard. But even if we removed that from the mix, Trump himself is a divisive figure in his own right. I suspect that no matter who was technically in charge of DOGE, people’s attitudes toward Trump would bias their perceptions of the entire process.

3. This is one of several reasons I’m cautious about labeling people’s decision making as irrational. Doing so assumes there’s a singular, correct way to evaluate trade-offs—something that rarely exists in complex, uncertain contexts.

4. Past benefit doesn’t guarantee continued support. We tend to favor programs we’re currently benefiting from, while discounting those we might need in the future—or ones that helped us in the past but no longer do.

5. Strong negative emotions, like anger, fear, or anxiety can be powerful drivers of human decision making (Grawitch, 2025).

6. Which, based on what I’ve seen, happens a lot.

7. Especially given the polarizing natures of both Musk and Trump.