State Capacity and Government Reform – with Don Kettl

Danny Buerkli: My guest today is Don Kettl. Don’s the former dean in the school of public policy at the University of Maryland and was most recently a professor at the Lyndon B. Johnson School of Public Affairs at UT Austin.

He has had and, in fact, still has a prolific output. He has written well over 30 books on government reform and state capacity, plus countless articles and columns, and has been an adviser to many government executives.

Don, welcome.

Don Kettl: Danny, it’s so good to be with you today.

Danny: Thank you. Now to start us off, I’m wondering that, really, the last time government reform writ large, was sort of showed up in mainstream debate, I believe, was in the nineties under Clinton and Gore, of course, with the National Partnership for Reinventing Government. Why has this idea become so salient again now?

Don: There there are a couple of reasons. The first is that every president in The US since has felt the need to launch his own government reform agenda. And so there’s been a president’s management agenda for every administration since. But I also think that what had happened was that a lot of the reform ideas that people had on the table had in a sense, if not run out of gas, at least run out of enthusiastic backing. It was just not clear, for example, if Kamala Harris had won, what they would have done, what would have been the big new thing that they had rolled out.

And in fact, I was in conversations with with some of the people who were working on putting it together, and it was they they would have had an agenda, but it wasn’t terribly exciting. Wasn’t the kind of thing that would either have have grabbed the media or especially the people inside the government. So one of the reasons why it’s back, I think, is that there’s a sense that that the old ideas that have been working had essentially run out their course and there’s time for something completely new. So that was one thing. The second thing is that there has been a a growing sense of of concern from both the left and the right about what government is and how it works.

From the right, there was, of course, the the sense that government bureaucrats had run amok, that they were uncontrollable, that had devolved into this deep state that Trump talks about all the time. So there’s there’s that piece of the problem that that the right had thought that that we needed something much more fundamental to try to shake things up and to try to especially shake up the power of the administrators who had gotten far too much power inside government. And then from the left, there’s also been this problem that is rooted in the abundance movement, where there’s an argument that the bureaucracy, in fact, if not out of control, at least had tied all of us up in too many rules and regulations. And so we needed a much more fundamental approach to changing what government does. And so the left is arguing that a lot of the problems that have happened are of its own making, and the right is arguing that, yes, that’s right, the problems are of the left’s own making.

And the left says what we need to do is to deregulate and get out of the way and to try to fuel abundance. And the right is arguing that, no, no, we don’t need that. We just need less government. We need fewer government administrators. We need fewer government programs.

We need less government spending, and come hell or high water, that’s exactly what we’re gonna do. And so what had happened, at least in The US, was the sense that the reform movement had essentially just just run out of gas as it was time for something completely new. And what we got because Trump got elected was the perspective from the right that amounted simply to trying to to take government, not just down to the the basic studs and the framing, but down to the foundation or worse.

Danny: Without, of course, necessarily endorsing it, what did DOGE get right?

Don: DOGE got right the idea that there really needed to be fundamental change and that it was possible to instead of thinking about small incremental steps, that that big, much more dramatic changes were needed. And so they they came through barreling through government. And the other thing that they had was an instinct about where to go to try to to get leverage. So that they focused first on personnel and particularly about how to try to fire government employees. And so that was the the first thing that they focused on.

Second thing is they focused on the structures of government. And so they went after a handful of agencies, including, for example, the Agency for International Development, and they decided just to just to wipe them out. And so that they at least had an instinct about the fact that structures mattered. And then the third thing, which I think has gotten less attention, but which also was an important instinct, is their eagerness to try to go after information systems and understanding how information provides a key for doing what they wanna do and to get get leverage and control over government. And more even more fundamentally, they were trying to use information to weave different information systems together and then use AI to try to probe for points of weakness.

For example, who is committing fraud? Illegal immigrants might be collecting money? And so their effort was to try to use information and AI and integrated information systems to try to get at some of their important goals. And so they had the right instincts about where to go to solve problems in ways that I think the left probably had not fully recognized. And DOGE did this in an integrated fashion.

The problem, of course, is that they went way beyond anything that the law allowed. And then in addition to that, dove into a lot of these agencies without having really any understanding about what it is that they did or whether what they found mattered or not. The complaint about AI is that it you’ve you ask it for information and it’ll give it to you. But what you can’t be sure is whether or not what it’s giving you is, makes any sense or what kind of sense it makes. And so for a while that they were talking about the number of people receiving social security benefits and the number of people who were over 150 years old who were receiving benefits.

Well, turns out that the problem is that the systems that they were using were largely built on COBOL and other kinds of antiquated data systems. When they didn’t have complete information on people, they ended up just having to put a code in, which then made it look like they were very, very, very old. And they produced then these, these figures that did not reflect the number of people who were over 150 years old receiving social security, it just people who were receiving social security for whom they didn’t have sufficient information and which the system had no way to be able to deal with. And so that they in case after case after case, they dove into into issues thinking that they had found problems when in fact they didn’t know what they were really looking at.

Danny: You’re in a sense saying it’s a fundamentally, the approach may may not have been completely wrong. It’s a skill issue almost in in its application. I think the one question that I’ve been interested in is if it’s not DOGE, and if it’s not what we’ve tried before, which also clearly does not seem to have worked, what is it?

Don: That is a huge problem in American government right there. And the the core of the issue is this, and I I end up making all my friends on the left and the right terribly unhappy when I say this. But I think that that Trump in general and DOGE in particular had the right instincts about the nature of the problem and where to go to try to solve it. Where they made an enormous mistake was in the kinds of strategies and tactics that they used to try to advance, that it was kind of the wrong answers to the right questions. And the left, I think, has not yet caught up to that that sense of things.

So you raised the question about, well, if you’re not gonna do that, then what should you do? And I think that there are lots of answers, but there are, but they aren’t nearly as exciting and don’t grab as much immediate political support. And that’s the core problem. But, we do have structures that get in the way. There’s no doubt that we have problems not only of hiring people, but also dealing with poor performers, and also even more important of matching the people that we hire with the skills that are needed to do the job that has to be done.

And then last, there is this enormous opportunity out there through information systems and through AI to try to modernize government. And so those are the, those are the things that I think that we need to do that the DOGE got exactly right and did it exactly wrong. And in my mind, I think the the fundamental problem is this, that there was a a a big instinct and the part of of DOGE and the Trump administration more generally to think very vertically, to think in terms of control from the top and reaching down to the bottom, and to silo off individual efforts and initiatives and agencies in particular for particular targets, with the exception of what they did with with AI. But in general, what they did is that they approached what’s increasingly a horizontal world with pieces interconnected among agencies and sectors, and approached it in a primarily vertical way. So when you approach horizontal problems in vertical fashion, then what you’re going to get is a, is an enormous mess, which is in fact what they’ve succeeded in creating.

And the other thing that’s happened is that they’ve, the initial phase of DOGE itself has run out of gas. It’s run out of political support, and now that having broken all the pieces, they’re not quite sure what to do about it. And they’re finding that they need to rehire some of the people that they fired because they didn’t really have a strategic plan about what they wanted to do and how to, how to get rid of what it is that they didn’t need. And in addition to that, the problems of information have ended up just tripping them up because they’ve, they’ve violated all kinds of norms and laws about securing the privacy of information. And so they’ve, they’ve got themselves in trouble.

What I think we need is a system that focuses much more on flexible hiring based on matching people that we need and hire to the jobs that have to be done, which the system’s very bad at. I think we need to go back and rethink about not so much abolishing structures per se, but about how to try to interconnect them better, understanding that the federal government, of all the work that it does, only about 5% of the federal budget is work that it does directly itself. And the rest of it has to do with, with leveraging lots of partnerships on the outside, and that’s contracts and entitlements and loan programs. And then that’s even before you get to regulations, which aren’t captured by the, by the budget. And so we have to recognize that reality and find ways of making the government more capable.

So just abolishing structures doesn’t really get to that problem at all. And the, the way to get at that, I think increasingly is through information systems that allow us to understand what we’re doing and get leverage over the system and over the partnerships, and to understand how to apply AI to scale in a way that’s smart and intelligent, and that focuses on it in a way that that’s really focused on on producing results that matter to people, which is what what taxpayers care about. And it’s that that connection about weaving all those pieces together in terms of results that matter to people that really need to be what it is that drives it. And so I think they’ve, they’ve missed that. I think that the, the left is yet to try to grapple with that, but that I think clearly is the way in which we need to go.

And it’s not that’s really not quite what abundance is arguing, and it’s certainly not what it is that Trumpism is arguing. So I think we need a a kind of a third way of going at this in a way that is, think, much more focused strategically on the way in which government not only was ten years ago, but the government that we need ten years from now. Because, 2035 will get here pretty fast and get here even faster if we don’t spend the time in the meantime figuring out the government that we need because it’s gonna take a while to build it.

Danny: Right. On this exact point, it seems one key question is, these reforms that you’re talking about, can they be done gradually, or is the political economy such that you have to go in with the disruptive shock? Because the gradual reform leads you inevitably to some kind of tar pit out of which you will never find your way out.

Don: And that’s the fundamental dilemma. If and I think what we had discovered was that the, as I suggested earlier, the incremental pace of reforms that essentially just got yourself stuck in exactly that tar pit, There were, there just were not good ideas anymore. There wasn’t, all those instincts were kind of there. We need something that’s much more disruptive and we need something that, that really shakes the system to the core, but which does it in a way that focuses on, on results. And that’s, that’s a hard thing to do because it’s a lot easier to focus on symbols than it is to focus on outcomes and to focus on results.

And so I think that the days of just gradually bit by bit incrementalizing our way into the future, I think are gone. Doesn’t mean that we can’t do it with small steps, but we need to be very agile about how we do it and making a strong disruptive run at things, but to build in enough feedback so we can, we can self correct constantly. And, it’s so maybe it’s incrementalism, but with instead of small steps at a time, lots of steps as if you’re running a 100 yard dash, but we need to run fast because the the world and its problems are not gonna stop and wait for us to catch up.

Danny: And it seems like in your own words, the the problem you’re describing is not necessarily new. I think you wrote in ‘98, so not quite, but almost thirty years ago. And I quote, the field, which here is public administration, has shown a constant tendency to reinvent itself only to rediscover that new approaches frequently rehash old ideas. And you’ve also said that the field has struggled with the basic problem, the accumulation of knowledge. So not only are we not learning anything, also all the new ideas that we’re coming up with or that the field has come up with are not actually new.

Why?

Don: Some interesting reasons for that in terms of just the intellectual history and development of the field of public administration and public management. Part of it is that it is is captured by a paradigm that’s existed for more than a hundred years that looks at the core problem of figuring out how you create vertical hierarchical structures and focus them on producing the goods and services. It’s a kind of a, this is too cruel and too crude an approach, but it’s kind of a Henry Ford Model T approach to the field. And the field has changed dramatically since then. There’s been a lot of focus on networks.

There’s been a lot of focus on information systems, lots of other kinds of innovations, but it’s still, I think at its core, captured by this kind of vertical piece because it’s the way in which everybody was trained and it’s the way in which a lot of the work gets done. But then on top of that, I think there’s, there’s an emerging problem of younger scholars coming up trying to feeling the need to demonstrate their technical proficiency and lots of statistical tools to try to make this feel more like economics in a way in terms of the the methodology. And what that really means is two things. One is that you need big data sets to be able to do that. And big data sets, not always, but typically exist only for problems in the past, because that’s where we collected all the numbers, as opposed to leaning forward into newer data sets that are just emerging, but are kind of clunky and messy.

It’s, it’s the AI AI problem there again, about what it is that you, that you’re focused on. So there’s that. And then there’s also a tendency to, to use the definition of problems in the past with old data sets to be able to find ways of of advancing issues. And that means that we too often don’t really focus on all the problems we’re talking about now. And, instead talking about what we can learn about the problem that somebody wrote in a journal five years ago that we can now advance incrementally through, through new data sets and new techniques.

And so the field is, is captured by by methods, by method of deciding which problems matter, and by this basic hierarchical approach. And you put all that together, and it’s you think about it kind of precisely what it is that Trumpism complains about. Not about the field per se, because it isn’t paying any attention at all to the field, but about government in general. And so it’s part of a broader problem that I think we need to try to work on, and again, on now, because I think the thrust of our conversation so far is that we are facing whole new problems where we don’t have ourselves equipped with the right kind of approaches, where the approaches from the left and the right are both wanting, and where problems in the outside world are moving so fast that we better move in a hurry, but at the same time, the field is unfortunately not providing the intellectual capital that’s needed to try to drive reform. There’s really no kind of reinventing government by Osborne and Gabler to try to drive a decade of change.

And the whether you liked the book or not, whether you think it was right or not, it was effective at at motivating first the Clinton administration and then Al Gore, and then a whole decade or more of of reinvention of the field and reinvention of practice. And we just don’t have that now because we have more of a sense of of just just wallowing out there in all the problems. And if you talk to lots of academics now, there’s a sense of, if not despair, at least profound worries that, oh, this is just awful about what’s happening. And people I think are drifting back into a sense of despair because what’s happening doesn’t match their view of the world, but there isn’t an alternative view of the world that has emerged yet anyway. So that I think is really our big challenge.

Not to write a bestseller in the field, which I’m not sure is possible because people don’t read books anymore and it’s hard to be able to get stuff out, but we need in a hurry, I think, to be able to refocus the field, to focus on problems because there is an urgency to try to reframe what government does. And it’s, this is of course not just an American problem. It’s a problem that, that every government in the world faces and where other governments that are not as large have greater urgency in some ways to to adapt because they can find themselves buffeted back and forth by by waves that over which they have even less control.

Danny: If we look at a possibly slightly happier angle to this, if you look at Operation Warp Speed, which was the procurement of COVID vaccines, by any metric, it was an absolutely resounding success, just an utterly outstanding example of government getting something incredibly difficult and incredibly important done. And yet, it seems oddly underappreciated. Why was it so effective, and and why is no one, talking about it?

Don: That’s such a great question because it it truly ranks as one of the greatest successes that government has had in a very, very long time. And as we talk now, it’s, it’s easy for people to just drift back and forget about how big of a problem we were facing. But at, at the beginning of COVID, there were public health experts who said, you know, we might have a death toll of maybe fifty to a hundred thousand. And people were saying, oh, would, that’s horrific. We can’t even imagine that.

And it turns out in The US, the death toll was 10 times that. It was over a million people. The the economy was shut down. Kids were were not in school. Problem after problem after problem was was piling up, and it was clear that we had an enormous crisis in our hands.

And the, the previous all time record for development and deployment of a new vaccine was four years. And so the, there was a sense that yes, we could develop a vaccine to try to deal with COVID, but the work in the past suggested that it was gonna take a long time. And what were we going to do with the, with public health and with the economy in the meantime, it took four years to be able to develop? Well, what happened was the Trump administration at the time, and it’s important to remember, was the Trump administration funded a group of, of companies to be able to investigate a variety of different strategies. They seeded a whole bunch of different kind of approaches.

And there was a competition among the companies to figure out the best solution, because each of them knew that whoever it is who got it was gonna make a lot of money because this is an international crisis of enormous potential. And so the incentives were for private companies to try to find solutions and find them fast, that government wanted to try to do that, that the research and development was going to be expensive. And so what they did is they launched it at warp speed. And it’s a term taken from those people who are Star Trek fans, who knew that the warp engine was designed to travel at faster than the speed of light. And so they, that was the strategy to try to do that, find incentives for companies that wanted to do what it is the government needed to get done.

The government realized that it couldn’t do it itself, but it could play a role in catalyzing the development of innovation through competition with private sector partners, and they in fact produced the vaccine and had it deployed in nine months. That’s just a stunning, stunning, stunning success. And it had to do with this, not as we were talking before, it wasn’t vertical, it was horizontal. It had to do with the creation of innovation through in information, and it had to do with structures that were primarily horizontal instead of vertical, driving it through these incentives. And it’s something that the the first Trump administration deserves enormous, enormous credit for, but over which it is, it’s it’s run away from since as fast as it possibly could because people didn’t like the idea of maybe being encouraged or forced to take vaccines, vaccine mandates that it ran into the populist counterattacks.

And as a result, the administration now finds itself criticizing itself the first time around for what was an enormous success over which, for which it deserves just enormous credit, but which it hasn’t gotten and doesn’t want for itself.

Danny: If we trace that story to the end, it has a slightly less happy ending as it were because one thing is producing the vaccines. That was clearly, critically important. And then the second step was distributing them. And during the vaccine rollout, California and also other states had the doses, but no one knew where they were. It was incredibly difficult to find out who had them, which pharmacy was actually able to distribute them on any given day.

And there was a privately led effort by Patrick McKenzie and a handful of volunteers that built an organization called vaccinate CA, vaccinate California, to fill the gap. And, essentially, what they did was they built a website that would tell you where you could get vaccinated on that day. And because no one had that data, the way they procured the data was initially they called pharmacies. So they had a bunch of volunteers who would ring work the phones, call the pharmacy, and ask, do have you any doses today? And they would say, yep.

And then someone would enter that in the website. How come no one thought that this was part of their job? No one in the entire public health establishment either thought it was their job or was able to pull it off, given that the entire success of warp speed is utterly meaningless. It’s an o ring problem. Unless you complete every single step in the chain, nothing is achieved.

Unless you actually manage to distribute the vaccine, everything upstream is meaningless.

Don: Yeah. That’s a great point, and it makes a couple points. One is that you can have experts who are terrific at producing great ideas, but not necessarily in figuring out how to deliver them. And so there really was this problem at the beginning. There’s still a sense of panic over COVID itself, a sense that the answer was at hand somewhere, but we just can’t find it.

And so there was, especially among the the people who who were most eager to get vaccinated, there was this horrible problem of trying to figure out where to find it. And the next stage was the, was the realization, you know, that the way that we could get it out there was through private pharmacies, that there, everybody, everybody’s got a pharmacy. Everybody’s got in The US a CVS or a Walgreens or something else somewhere. And sometime, some places have a CVS on one corner and a Walgreens opposite it. And so that there were, there were pharmacies, you could train pharmacists to administer the vaccines, which is, was typically not part of the job description, but which wasn’t all that difficult to be able to do.

And then you could, because people knew about pharmacies, went there all the time, knew and had confidence in them too, on top of that, they often knew their pharmacist, That that was a, an important critical link in making the bridge between the government funding of the development of the vaccine and private development of the vaccine itself to enormous production, and then actually getting into the arms of individuals. And it was that link of using private sector partners to be able to deliver what essentially amounted to a public good through an innovation and delivery that was built around systems of trust, he says. So talking like a wonky political scientist. But that’s an important issue. I mean, how no matter how fast you move, can you connect with people?

And the answer was, yes, you can. And then the next stage was, how do you do it in a way that people’s gonna, people are gonna trust it? And the answer is you use systems that they already trust in pharmacies. And then at the early stages, well, that’s good, but I go to my pharmacist and they don’t have it. And so then you develop an information system that allows people to be able to find it.

And you not only do it, but you notice that it was, the way that system developed and the way it rolled out in other places in the country was that it was based on connecting with private pharmacists in a way that deployed the information that was place based on a picture, that is a graph, a map. And so you could, if you wanted to find, I was sitting here in Austin and you wanted to know where could I get a vaccine? And turns out, well, my local pharmacist didn’t have it, but, oh, wait a minute, I can, 10 miles away, if I wanted to drive there, they have not only vaccines, but I could pick which manufacturer vaccine I wanted. It was all on a map. So the idea of thinking about the chain of connecting lots of stuff with the people involved creating a delivery system based on trust that was nimble and flexible, based on information with the information, displayed in a way that was place based on a map.

And, you know, golly gee, that sounds like maybe what AI could do in the future, that you could create cross sector information systems that are meaningful to people by using easy to interpret pictures that display very, very complex bits of information. That’s kind of cool. And that is, I think, an important lesson from all of this. So you’re trying to figure out where should we go? Where can we go?

The answer is, I think, following that chain, which provides an enormous amount of clues about what worked. And the important thing to recognize is that it wasn’t just a, well, let’s see if this works. It they did check to see if it worked, and in the end they ended up with vaccination rates of, if I remember correctly, something like seventy percent or thereabouts of people who were able to be able to get it through the system that we described.

Danny: If we stay on the the question of technology, technological change has always brought about change in how government operates. It’s an old story. Railroads made modern bureaucratic states possible in the first place by reducing monitoring costs. Harold Innis, the Canadian scholar, had this fun theory that the move from stone to papyrus made the ancient Egyptian administration much more effective and expanded its power because you could sort of take the papyrus and then run with it as it were, which was much harder, with a stone tablet. The printing press obviously enabled us to produce standardized forms.

Hard to imagine Without that, you know, we could go on. What would you expect to see with AI systems in the future?

Don: Before we get to AI is just the the comfort level of individuals dealing with technology to be able to deal with the systems that they want, and in some ways that are self-service. We have here in Texas a requirement that you get your car inspected for emissions, at least in the urbanized areas every year, and that you need to make sure that you have insurance, and that in addition to that, you need to display a little registration sticker on your car. And once upon a time, that was a really complicated process because each of those things had to be done individually and had to then require maybe a trip to a large bureaucracy that where you had to wait in line for a long time. I’ve yesterday just got my sticker for next year, and I, after I got my car checked for emissions, which it passed fortunately, I would and I had my insurance, which the people who checked for the emissions checked for me, they registered that into a comp a data system. I went home, got out my credit card, because they charge you for this of course, to register your car because it’s a way of making money.

But I was able to tick, tick, tick, and enter all the information in. And then week and a half later, I got the sticker in the mail. And so we’ve short circuited a lot of what had been the, the bane of the existence of most Americans of having to go to the department of motor vehicles and wait endlessly in line. And all of a sudden the job is done electronically. I changed my I was able to update my driver’s license all electronically, and I got a handy new shiny driver’s license in the mail as well.

And so if you think about that, that provides a way of thinking about how individuals can interact with government in a way that’s far less painful, and that provides better, faster service in ways that people are likely to trust. And you rely on the postal system, you rely on the internet, and you rely on information systems that are set up by government, as well as private partners who do the the inspections. Because I went to a private garage that that inspected for me. So you think of all the different players there, and that’s the and just mapped it out. We have the Postal Service, a kind of quasi governmental organization.

We have the inspection, which was a private company that then checked with another private company about whether or not I had insurance that entered it all in a data system, undoubtedly provided by a private contractor, managed by the Department of Motor Vehicles, and then integrated all this stuff and all of a sudden it pops up in the mail. So you think about the way in which those systems work is a way to try to figure out, a way to, to solve these problems. Now, what, where, how can I figure out where to go to get my car inspected and checked for emissions? And so I went to this website for the, for the department of motor vehicles, and they have a way to be able to check addresses and up pops a map where I could be able to see who does it within a short drive of where it is that I lived. And there was one place that I checked and it was really close, but I knew the lines were likely to be long.

And there’s another place that was a little bit further away. And I said, ah, you know, I could go there. Turned out to be, I was out of there in fifteen minutes and I was able to find that because it was a place based information system that drove the the inspections that were being put together. More of that, I think, with AI weaving the pieces together, being able to allow individual citizens to engage in self-service at a time of their of their convenience, in a way that works either on their phones or their tablets or their computers, and to be able to work through an integrated system that for them is seamless. And that I think is the way in which we’re likely to go.

Place based systems created and constructed and integrated through information systems involving public and private service providers, where the idea of, of figuring out how individuals can connect with government as easily and painlessly as possible, regardless of sector, with information as the driver is I think an important way that we can go. It of course doesn’t fit everything, but for a lot of things that government does, it it works, I think, pretty well. The problem, of course, is that you have to be have access to and be familiar with the internet. And there was a time not too long ago where there were you had a hard time trying to reach older people who didn’t have a clue about how to try to do this. But now we’re we’re getting to the point where more and more people who were in their sixties and seventies and eighties, have had smartphones for a long time.

So we’ve crossed the threshold for being able to make this happen. So that’s, that’s an important thing. It also creates problems potentially for those who are, who don’t have access to smartphones or to computers or the internet. We to be careful about, about inequalities and the delivery of government services that pop up because of income. And there are ways of being able to provide that in libraries, for example, where there’s access to the internet for everybody.

But that’s, that’s something we need to need to think about. But it does, in terms of thinking about the delivery of government services for the future, have enormous potential. You can also leapfrog up to the highest levels of government. There really are problems of waste, fraud, and abuse in social security, for example, and in Medicare and in Medicaid, our big healthcare systems funded by the government. The reason is that most of those systems are operated through private contractors.

One of my favorite statistics about the federal government is that Medicare and Medicaid and related, child’s health program constitute about 25% of the entire federal budget. The number of federal employees in charge of managing that are 6,000. So we’ve got, I’m sitting here just a few miles away from the University of Texas at Austin, and they’ve got 25,000 people in charge of managing 50,000 students, faculty, staff, and all the rest. So we’ve got six times as many, I’m sorry, almost nine times as many employees at the University of Texas for 50,000 compared to 140,000,000. And so what we have is a system that operates through private contractors.

So the way to be able to get to waste, fraud and abuse problems is to, what, to use data systems that allow you to track what’s happening and who’s doing what, and using AI to track down the likely sources of and so that’s the that’s the the the new frontier on issues that people really care about.

Danny: When it comes to outsourcing, which is something you’ve thought a lot about, is it ultimately as simple as it works really well when outcomes are measurable and cannot be gained, and it works significantly less well when the outcomes are not measurable and or can be gained? Or to make a specific example, the reason why NASA was able to outsource the development of some rockets to the private sector was because you can unambiguously know whether a rocket has achieved its objective or not. It’s very simple to know. It’s very simple to specify what you want from that rocket. The same thing, of course, is not true for many other things.

So is it really this simple in the end? Is it actually much more complicated?

Don: At least much more interesting. Let me put it that way. And the, the case of rockets on the one hand is, is fascinating because NASA decided that it was going to get out of the business of, of specifying particular outcomes, except for we want to be able to launch people into space and bring them back safely, but we’re going to allow private companies to be able to compete for the business given that broad piece, instead of specifying the individual components as NASA used to do, it, was buying outcomes. And the problem is that it and what it is, is it encouraged multiple organizations to compete for NASA’s business because it did not wanna be in the business of being captured by one supplier. Well, it turns out that that one of the companies, Boeing, has had a terrible problem trying to get anything to work well.

Elon Musk’s company, SpaceX, on the other hand, has tended to to be far more effective and it has captured an enormous chunk of the business. And so there’s not as much competition as the model suggested at the beginning. And Musk lately has had a problem of of of launching things that blow up. And so, well, we know that didn’t work. But on the other hand, they’ve got, they say, a strategy of launching things and launching lots of things often, allowing them to blow up and learning quickly.

And so that’s a new kind of model where NASA’s sitting there keeping its fingers crossed that having found that it’s got not all, but most of its eggs in one basket where the basket blows up, that the strategy of of of rapid learning will actually work for it. So it’s it’s a different kind of strategy with that. On the other hand, you go down to the grassroots and a large part of the social service system in this country is managed by nonprofit organizations that operate through federal money and state money and local money. And so you’ve got often very fuzzy outcomes that are difficult to try to nail down. And we have a problem of trying to figure out whether or not these programs work.

We have an administration that’s come in and said that this is just a bunch of liberal left leaning progressives who are trying to fund their favorite kinds of programs and strategies, and it’s not really based on anything that really works because we can’t really measure the results. And so the fact that on the one hand, if things blow up, that’s, that’s not good, but at least you know that it’s blown up and you know whether or not it works. On the other hand, for social services, it’s very hard to be able to tell what the results and the outcomes are, and therefore it makes them more vulnerable to political attack. So you have your choice on the one hand of of highly technical, easy relatively easy to specify outcomes that turn out to be pretty hard to pull off. And on the other hand, you have social service programs that are pretty hard to pull off, but where the outcomes are are less fuzzy and where, therefore, the the problem of building political support is much tougher.

Danny: Personally, what did you learn from Paul Volcker?

Don: That’s a great question. And I had a chance to be able to to get to know him, but also that built on a on work I did with for a book, The Leadership at the Fed, where I had a chance to be able to look at the the history of the Federal Reserve leading up through Volker and his efforts to to try to stabilize the economy. And the first thing I learned was you look at his work to stabilize the economy by putting the economy through the ringer with super high interest rates, which was needed to try to to beat down the the inflation that had grown up during the 1970s. And so it’s not only as we look at the, the economy and some of the battles over the federal reserve now, you better be pretty careful about which you let loose, because if you screw up, the consequences down the road can be monumental. And so sometimes it’s more important to stick to the pain in exchange for the long term gain.

And there’s it helps to be able to look over the hill and through the problems to be able to do that. Second thing is that, he was he was the master of communication when he was at the Federal Reserve. And there he would sit there and he’d be chomping on a cigar and he’d be testifying and there’d be smoke coming up and people were trying to figure out after he got done talking, what did he just say? And he had this way of being able to talk to to be able to allow people to somehow divine his his words without him being specific about it. And sometimes it was like the ancient Romans cutting open a chicken to check the entrails to see what it was that the fed was about to do.

Because he knew that that people were not only just betting on the fed’s actions, but betting on the expectations about the fed’s actions. So it’s important about not only managing what you’re doing, but managing expectations about what you’re doing. Another really important thing. It’s useful to be, I think it was six six or six seven, and I went to lunch with him one time and we were sort of walking down the sidewalk and having a conversation, and I got a cricket in my neck just having to look up at him. And I was five’eleven, but I was just nothing by comparison to his sort of towering presence.

There was something to that as well. But most importantly, here’s a guy who spent his entire career in central banking. He was president of the Federal Reserve Bank of New York, which was the single most powerful Federal Reserve Bank in the entire system. He was chairman of the Federal Reserve and was responsible for probably the the single biggest economic accomplishment of the last century in in stabilizing the economy in the after what had happened in the seventies. And after all this, instead of turning to consulting, which would have made him a fortune, he focused on the public service because the lesson he had learned through all of this was the importance of, not only the policies, but having smart people with a public service mindset in place to be able to administer what had to be done.

And it was a powerful, powerful driver for him. And the reason I was able to finally figure out, because I’m trying to figure why Mr. B, did you do this given what you could have done? And one thing he told me was a story. When he was little, his dad was heavily involved with, with public service kinds of things.

He’s a city manager of a small town in New Jersey, and they were interested in trying to get some insights from the gurus who were at the Institute of Public Administration based in New York. And at that point, the the head of the institute was Luther Gulick, who was one of the real giants of public administration in the middle part of the twentieth century. And so he remembers having gone with his dad to visit Luther Gulick at the Institute for Public Administration to talk about city management. And the lesson that he drew from that was the importance of a kind of intellectual leverage over complex systems, coupled with the importance of the public service that drove his career for the rest of his life. And that story has really stuck with me because from the time he was small, he had in his mind the importance of of serving the public, of doing it through public service, making sure that there were others who could come along with him on the journey, and to be prepared for the the really tough battles that lay ahead because he knew that there was a core of values that the field could teach and that he could take with him in the way in which he did his job.

And he could as as he told that story, which I don’t think he told very often, but he was talking to me about that and the as one of these the scales fell from my eyes as I was listening to him because it was clear where he had gotten it, where it had come from, and what drove him and the work that he did.

Danny: That’s a great story. We’ve talked a lot about the US government for good reason. The US is also in a long term competition arguably with China, and China seems to have quite a lot of what you could call state capacity. What should we learn from the Chinese way of doing

Don: The first thing is that they have invested a lot in the state capacity, and they’ve they understood and still understand the importance of creating a system that allows them to, to move fast about what it is that they want to do. That’s important. One, one small thing, two small points of history. One is that the Chinese in fact invented bureaucracy, invented the public service thousands of years ago. And they had, in fact, a testing system for civil servants that was incredibly complex.

And so there’s a temptation to cheat. And if you’ve cheated on your civil service exam, however, the the penalty was death. And so only one to two percent of people passed, and you didn’t wanna try to cheat to make sure that you were among that. There’s always high prestige that came along with the civil service in China for thousands of years. The second thing is a kind of reverence for knowledge and for expertise itself, a real level of respect.

The something that I wish that they could bring to The US there in about the year January or so, professors were held in such high esteem that they had sedan chairs with people carrying them around from meeting to meeting. And so I’ve, I’ve often thought that would be, that’d be nice to be able to have, but I don’t think that’s gonna But again, it’s the sort of the reverence for knowledge. I was struck at during when I visited China about the the kind of level of respect that I was shown, unlike the situation in The US, and not because of anything having to do with me, but because of the position that I occupied. So there is at the core, this appreciation for for knowledge and for capacity that lies at the core with an understanding that that’s that’s how governments, effective governments work. Related to that is something that we don’t often pay a lot of attention to, but there was China’s a big country, And unlike The US where there is a system of federalism where we have a kind of understanding about self government, one of China’s big problems has always been trying to figure out how decisions in Beijing get transmitted out to the to the provinces.

And long, long, long, long ago, they’ve they’ve figured out the importance of of devolution and how to try to to manage that from the center. And of course they they now have a a communist apparatus that allows them to to do that. But it’s based on much more than we have decided this is what you must do kind of approach. There’s a real, a very sophisticated system of devolution goes along with that. And you’ve got a country as large as China, where the basics of service are important, you’ve got some importance there as well.

There’s, I think in addition to that, the importance of investment in government and government services and technology, which you can see in both high speed trains and airports. I was struck the last time I was there getting on a plane in Beijing and then landing in LA and trying to figure out, well, which one is the third world country here? The airport in Beijing was just miraculous in comparison to, you know, LA works and the airport’s huge and, and people don’t seem to care a whole lot that it’s not super fancy, but there’s a big difference there in the kind of investment in technology. And so we we have that. But on the other hand, the risks of course that come along with a a country that has done all this, where we have both economic competition that’s that’s real and strategic problems that are, that are enormous, and now tensions coming through, through tariffs and other kinds of, of issues that really put on the table the, the risks of picking a fight.

So that there’s that, that tension underlying it. But the, the importance of the respect for information or technical expertise for using that to try to, to manage relationships between the center and, and communities throughout the country, the investment in technology. Those are pretty interesting lessons that I think that the Chinese have, and there’s a and it’s more and more sophisticated by far than the impression that I think most Americans have, just saying, well, you’ve got an all powerful center, which, which they have, and they make decisions and everybody has to fall in line. It’s a, I mean, it’s a big country and it’s, it’s pretty easy to just sort of slide underneath the radar if you’re, if you’re doing stuff. And not to say that they’re not in problems of of depriving citizens of access to some source of information.

But on the other hand, there’s no, there’s no secret that that Hollywood movie makers spend a lot of time figuring out how to appeal to to chinese audiences of the movies that they make because there’s a as a large audience and there’s a a a strong set of of both pride and and culture in China that they have to be able to tap into that’s that’s also part of the of the culture and part of the the way in which society works that that help to drive the nature of government’s power and capacity.

Danny: What’s something you used to believe about government that you’ve changed your mind on?

Don: Something that I used to believe that I’ve changed my mind on. In some ways, I’ve had one thing I that I haven’t, deduct your question for a second, is, the importance of, of creating a government that really connects with people. That I started this business really focused on why it is we do what we do and how do we know that it works and understanding that that government isn’t government unless it really connects with the people. On the other hand, something that I’ve changed my mind on, think, is the mindset that I had that I think a lot of the rest the field shares about role of of traditional structures and authority and hierarchy in figuring out how to deliver those services to citizens. Because I’ve seen through warp speed, I’ve seen through research that I’ve done.

I’ve, I’ve seen the way in which people connect with government, the importance of these, of these connections that the government increasingly has through the, the nonprofit world and through the for profit world. One of the things that I did was to, I served on a, on a task force once to advise the secretary of energy about nuclear waste storage, not what to do or where to put it, but how to develop trust and the decision that was being made. Because the storage of long term waste is important. You don’t wanna mess with something that’s gonna be lethal for ten thousand years or so. But on the other hand but on the other hand, technically it’s a it’s a solvable problem, but the problem is the political one of trying to figure out how you convince people that that having this 20 miles away isn’t such a bad idea.

And so I, we toured the country, talked to lots of people, talked to contractors, talked to others about the problem of figuring out how to make that work. And so two stories still stick with me about that. One was that I visited the place where they used to make the the triggers, the plutonium triggers for nuclear weapons. So it was the the in some ways, one one of the most dangerous things on earth and got to the to the front gate. I I wasn’t allowed to go anywhere without an escort, including even to the men’s room.

They wanted to make sure that somebody was there all the time because didn’t want to have any spies doing anything that they should do. So I had to wait at the gate for an escort to go to my next meeting. And the guy came out and, he, we were just talking and I said, oh, it must be a tough, tough job. He, this was a guy who looked at me and said, I don’t wanna mess with him. Because he was, he was big.

He was hulking. You see the, the stories of, of North Korean guards at the border. They have nothing on this guy. And he said that he was trained in, in 20 different weapons. So I started my mind trying to begin, counting up how many weapons I knew.

And I got to about eight or nine, and I said, I don’t, I don’t wanna know about the rest of them. And on the then I looked at his uniform and there was a patch on the side that said, Wacken Hut, which is a very large private sector company that that had security tighter than at the White House, provided with over some of the most dangerous stuff on earth, provided by a private contractor. And I’m saying, this is, you know, talking about figuring out how to, how to deal with with issues, that gave me a flavor about the way in which things work. Then on a different trip, we went to Las Vegas and we had a public hearing. And one of the things that, Las Vegas was about 20 miles away from where they wanted to store a lot of the stuff deep inside a mountain.

And so there are a lot of people, as you can imagine, who are pretty worked up about all this stuff. And we had TV cameras there. There were people who were rabble rousing, we were being picketed on the outside, all having to do with problems of creating trust. But then there was a there’s a woman who came up to the microphone to testify, and she said, my name is Cynthia of the desert. And given the issues that we were facing and someone who was obviously a naturalist, I was thinking, I better grab my seat belt because wow, I know what’s coming.

I was dead wrong. She said, I live with my husband and my child in the desert, not far away from Yucca Mountain where they wanted to put the nuclear waste. And I was terrified about it and I was, I just really was strongly opposed. But then there were meetings out there with the department of energy staff who talked with me about what it was they were going to do, about how it was going to work. And I came away from those conversations really trusting what it was that they were saying.

And so I think that this is a good idea, and I think it’s something that the country needs that I’m, I want to support it. And I was thinking, wow, here’s somebody who you’d be sure in advance would be an enormous opponent of the, of the idea of putting nuclear waste anywhere, who started out in that position, who had gained trust in the process through conversations and interactions with government officials. And so things that I, where I’ve really changed my mind, or at least I’ve gotten more properly, probably a more sophisticated understanding about what happens is understanding the important role of the horizontal connections that make government work and the importance of, through those connections, building trust in citizens based on the nature of those interactions. And that’s something that is really, that’s sort of, that’s sort of my Paul Volcker story about what matters, how to connect, the importance of trust, and the ways in which these networks operate to deliver government services. And it’s, so it had to do with, again, not so much changing my mind, but rubbing shoulders with the the way in which government actually works that I think has has created a different sense, in my mind at least, about the way in which a public administration ought to ought to behave.

Danny: Final question. What is something I should have asked but didn’t?

Don: I think we’ve explored a huge part of the world out there, but I think that not so much should have asked, but but the question we need maybe to focus on, because it’s I still have kind of fuzzy in my own mind, but we really need, I think, now, to think about what government in 2035 ought to look like, how it’s gonna operate. And I mentioned that earlier, but it really is not very far away. If you think about the number of presidencies that we have in The United States in the meantime, not many. If you think about how long it takes to develop, even if you’re, if you’re warp speeding everything, that took nine months and then another year or so to get things going. So you take two years and you, so you take 2025.

And so at that point you’re at 2027 and maybe a new presidency is coming in, has to get his feet wet in 2028, 2029. At that point, 2035 is looking pretty close. And and the world in 2035 is certain to be different than what we have now. We can be sure that the the pressures of government are going to increase, that the, in some ways, the tensions between nations, but the importance of interconnections are going to grow. You can think about the interpenetration of government and the private sector, where I think we need to think about government’s use of its private partners and private partners that increasingly have to think about, on their own part, a sense of citizenship, since they’re gonna be heavily involved in delivering services.

Simply just delivering things on contract, that’s not gonna be enough. And so we need to think about that and how that’s gonna operate. I think it’s clear, you look at the, the enormous pace of AI, it’s clear that’s gonna be a huge thing. The, I’ve, we, we can’t today sit in the, toward the 2025 and even guess what AI is gonna look like in, in the middle of 2026, at the way things are going. I’m constantly stunned at what it is that we could do, but we, but we know it’s, it’s, it’s stampeding ahead.

And so the question is, how we use information to make government work better and connect better with citizens? That’s a big thing now that we can’t solve, but which we need to put front of mind, I think. And then ultimately, not only how can we government work better for citizens, but ultimately, and this gets back to the Paul Volcker point, how can we hire the public servants that we need with a culture and the mindset that’s gonna be required to be able to help the government navigate its way through. And for for a big democracy like The US, that I think is one of the one of the biggest challenges that we face. And it’s pretty clear that that most of what we have now is not a very good answer to the question of what’s gonna happen then.

So we need lots of smart people like you and and others who are sort of exploring the world, figuring out a road between where we sit now and where we know we’re gonna need to be with intellectual capital supporting it all. The Chinese had that and have had that for thousands of years, and they’re they’ve got that one approach that is developed here. What what’s what’s ours gonna be? And we have no choice but to figure out how to adapt, and we just have to make sure that we’re not clumsy and stupid about the way we do it.

Danny: Don, thank you so much.

Don: Danny, it’s been such a pleasure talking with you.