Recoding America: A Rallying Cry for the State Capacity Movement
(publishing June 2023)
Note: The following is a broad critique of American government. But (1) Government is not monolithic. Nothing said here applies uniformly. There are absolutely innovative pockets of excellence within government. Our goal in all of this State Capacity work is to grow the footprint of that excellence. (2) This is not a new critique; *many* people working inside government know these problems exist. We’re working to raise awareness outside government, such that we can more effectively partner with folks inside government to improve operating conditions and allow more great people to do great work in the public interest.
In a recent Ezra Klein podcast about China (82 min), Ezra talks to Yuen Yuen Ang, a China scholar. Ang observes: “In the US, elections are exciting, and bureaucracy is boring. In China, it’s the opposite.”
Ang goes on to say that experimentation and innovation in the Chinese bureaucracy is a big part of the country’s rise over the last 40 years.
In America, we don’t talk about bureaucracy nearly enough, and certainly not in terms of what more innovation & experimentation could bring us.
But this topic area — state capacity — can feel hazy and obscured. Why is it, exactly, that in a place like California, where we profess progressive values, we can’t achieve progressive outcomes on issues of homelessness, public safety, or the delivery of social safety net benefits?
The single best source I’ve encountered for understanding state capacity is a soon-to-be-published book by Jennifer Pahlka. Just as Rachel Carson’s Silent Spring helped launch the environmental movement, I believe Jen’s book can help launch the state capacity movement.
Below I’ll pull out key learnings from the book, using extensive excerpts.
A caveat: unlike a business book where a couple key ideas are ballooned into a few hundred pages, Jen is getting at subtle themes. So while I’ll do my best to summarize, I highly recommend you pre-order the book and read it for yourself.
First things first: although Jen is the founder of Code for America, the US Digital Service, US Digital Response, and Deputy CTO under President Obama, and the title of the book is Recoding America, this is not a book about IT or websites!
Jen is making a deep cultural critique of the way government operates. She discovered this cultural issue while doing digital transformation work, but the point of the book is not that we need new software to fix our government’s delivery issues. The point is that the mentality of government, with its waterfall approach to problem-solving, is fundamentally mismatched to our current problems.
What Is “Waterfall” Culture?
To understand organizational behavior, we have to start by understanding the incentive system:
When systems or organizations don’t work the way you think they should, it is generally not because the people in them are stupid or evil. It is because they are operating according to structures and incentives that aren’t obvious from the outside.
Government’s default operating process is “waterfall.” This phrase comes out of software development, and references a project management style where there is a clearly defined sequence of execution with project phases that do not advance until a phase receives final approval. Once a phase is completed, it can be difficult and costly to revisit a previous stage.
Clay Shirky once quipped that “waterfall amounts to a pledge by all parties not to learn anything while doing the actual work.”
While the term comes from software, Jen is applying it much more broadly:
Waterfall development of government software is a miniature version of a much larger dynamic that pervades all areas of government.
When applied to government process and culture, waterfall references a hierarchical form of authority, where decisions are made at the top of the waterfall by policymakers, and then flow down into the implementation stages with little opportunity for feedback or revision back up the chain of command. So for example, concrete lessons learned by frontline workers about what does or doesn’t work about unemployment insurance rules don’t flow back up to the policymakers setting that policy.
The core insight of this book is that waterfall is the cultural mode of government operations.
First Order Implications of Waterfall
So what are the implications of operating in a waterfall environment?
Policy Can Lack Practicality
Note: Refreshing my caveat here, I’m not saying all policy lacks practicality. But the gravity in the system pulls toward less vs. more nuance, because decisions are being made very far away from specific problems, and only the most conscientious policymakers incorporate deep feedback from folks at the implementation level.
In a waterfall world, we specify many things, but far away from the actual problem. So in a state like California, with 40,000,000 people, 120 legislators and their staff aim to specify how to solve problems. These approaches will be necessarily overgeneralized if not outright wrong. Society is complex! No one person, no matter how smart or charismatic, can come up with rules that will match the nuance of real life.
Sometimes this distance leads to less good policy than we might get under a different system/culture of policy making. Sometimes it is out-and-out counterproductive.
Jen illustrates the dangers of waterfall thinking via California’s unemployment insurance debacle during the pandemic. While the full story is told across multiple chapters, one vignette is about the discovery that, contrary to reasonable intuition, hiring more staff actually slows down the ability for the Employment Development Department (EDD) to get through its backlog. This comes in the context of the Newsom administration and the California legislature pushing for the hiring of an additional 5,000 employees during the pandemic.
More people equals more productivity equals fewer backlogged claims, the logic went. But what the politicians didn’t know was that these brand-new employees, with their days or weeks of training by Zoom, could not do the work that would reduce the backlog. Only highly experienced claims processors could do that. In fact, new employees could do almost none of the work assigned to them.
But it was worse than that. As Marina watched Carl scroll through the emails from the four hundred new hires in his group, she wondered who was training, and responding to, the other forty-six hundred new employees around the EDD. The answer was grim: pretty much every staff member with tenure and knowledge of how the arcane and complex systems worked. They all had inboxes full of requests from new employees, representing hundreds of hours of work just to read and respond to them. It was clear that the new employees couldn’t help with recomps, the part of the system that was causing the backlog; it would be years before they were either competent or authorized to do so. But if the people who could help with it, the old-timers, were busy training the new employees, who was processing the claims?
Because elected officials didn’t understand how work actually got implemented at EDD, they were pushing for counterproductive measures.
Because of this distance, policymakers also aren’t forced to grapple with the layers of complexity they’ve built into policy that implementers then need to accommodate — instead they just keep passing law on top of law.
The politicians who jeer when a government agency like the EDD says that it will need eleven years to modernize its systems do not understand the nature of the technology in question. They envision a system, not a bunch of tenuously connected layers that function by way of awkward work-arounds. But they also don’t understand that those archaeological tech layers are an expression of archaeological policy layers. The tech gets complex because the program and the policy governing it are complex. And like the tech, the policy is complex in part because it always accrues but is rarely reduced or reconciled. Like a hoarder, government never throws out the old to make room for the new.
One reason the IRS has so much trouble modernizing its systems, for instance, is that there are over seventy-three thousand pages in the statutes and regulations the agency must implement. Between 2001 and 2012, the tax code changed 4,680 times, an average of once per day. When former IRS commissioner John Koskinen would get called in front of Congress and its members would gripe about the tax system, he would shake his head and say, “I didn’t write the tax laws, you did.” He had a point.
Incentives Favor Procedures Over Outcomes
As a result of the distance between policymakers and on-the-ground problems, we have a lot of dysfunctional policies and processes. But in waterfall, the upward flow of information from “lower” levels of the system, which are more proximate to actual end users, isn’t prioritized for cultural and historical reasons we’ll get into later in the piece.
The upshot is that when a process is not going to properly achieve an outcome, a government staffer can either (a) go along with the process, outcome be damned or (b) pursue the outcome, process be damned.
Jen shares a couple anecdotes where government staff take the former path — Paula, EDD’s leader during the pandemic, and Kevin, a senior IT leader at Veterans Affairs (VA).
In the VA story, Kevin has been handed down a set of requirements by policymakers that don’t make any sense and will definitely exacerbate the problem of getting veterans the mental health services they require. At the time, 16 veterans were committing suicide each day.
“I’ve spent my entire career training my team not to have an opinion on business requirements,” [Kevin] told me. “If they ask us to build a concrete boat, we’ll build a concrete boat.” Why? I asked. “Because that way, when it goes wrong, it’s not our fault.”
The last thing he wanted was to have a seat at the table. Keeping his teams in order-taking mode didn’t make them immune from criticism—there were constant headlines about the VA backlogs and ongoing fury from administration officials who wanted veterans taken care of—but it had been a winning strategy for him personally. Like Paula, he’d been promoted countless times, rewarded by a rule-bound civil service regime that values years of experience and a clean record but has little ability to judge competencies, leadership acumen, or a track record of meaningful results. Like Paula, he saw withstanding the criticism as part of the deal. In the end, he could say he’d just been following the established process. He’d just been doing what he was told.
In waterfall, work is chunked up sequentially into discrete pieces, such that each piece of work is judged in isolation, as opposed to being part of a larger whole. So instead of seeing Kevin’s team’s work as part of a shared mission to reduce the suicide rate among veterans, it is instead judged only on its fidelity to instructions given by the steps in the process before his.
In the EDD story, EDD is struggling with massive fraud, and Jen’s taskforce asks Paula to deviate from the prescribed fraud-flagging process — which is empirically not working, to the tune of $20bn of fraud — and implement a new process. Paula is resistant.
But Paula was the product of a system that values deference to the hierarchy and punishes risk-taking. It had rewarded her with job security and successive promotions for thirty-seven years, just as it rewarded people like Kevin at the VA. State and federal civil service rules are a big part of that system, but they are simply the expression of a culture in which fidelity to flawed rules and practices is valued more than solving problems.
She [Paula] was in a lot of hot water, with a lot of very powerful people angry at her, but she believed her ability to show that she was following established procedures would leave her immune from consequences. That stance only further infuriated the assembly subcommittee. But she stuck to it in question after question.
Jen identifies alternative leadership cultures within the government, including in the military, where they’ve managed to break out of waterfall culture. But it’s not the norm.
General Stanley McChrystal put it this way: “I tell people, ‘Don’t follow my orders. Follow the orders I would have given you if I were there and knew what you know.’” But Paula didn’t give that direction to the people who reported to her, probably because she had never been given that direction herself. Following the orders as handed down had worked for her for decades.
In both cases, with such high stakes, it seems galling that these senior officials would elevate (flawed) process over outcomes. But as Jen lays out, these decisions are a function of the incentive and risk structure that Kevin & Paula are operating in.
That’s because there are two accountability pathways happening in government — one responsive to outcomes, the other to process.
The outcome-focused process is the political pathway: these are Congressional oversight hearings where an agency head gets brought up in front of the Legislature and lambasted for their failings.
The process-focused review is via the civil service, run by the agency itself, an Inspector General, or the Government Accountability Office.
Only one review — the process-oriented one — has real teeth. This is the review that can get civil servants fired, lose them their promotion, etc. The safe thing is to follow the process rules.
Or replace “safe” with “fit,” as in Darwinian fitness. In this evolutionary environment, the staffer who takes the lower risk pathways survives the gauntlet and advances over time, to the point where Paula leads EDD and Kevin is senior at the VA. Meanwhile, outcomes become second-class citizens, and our worst fears and feelings about public servants are reinforced.
Metrics Are Not For Learning
The system produces poor outcomes, and so legislators and the public search for additional mechanisms of management control. We implement dashboards, scorecards, and key performance indicators (KPIs).
But as accomplished government reformer Ken Miller notes, data can either be used for learning or accountability — he calls this using data as “flashlight vs. hammer.”
And as Clay Shirky pointed out, waterfall is an agreement not to learn — thus in government we often see data used for accountability and blame.
Ken further points out that data without the autonomy to course correct naturally leads to gaming the system (9 min).
Jen returns to the stories of the VA’s Kevin and EDD’s Paula to give examples.
Before we met with Kevin, we had been told that latency in the Veterans Benefit Management System (VBMS) was a problem. We all experience some latency in the apps we use, but if we have a good internet connection and we are connecting to a fast database, the latency may be so low we don’t even notice it. In the case of VBMS, we’d heard that adjudicators would click on a file and then go start the coffee brewing and come back before the next page loaded.
“Latency’s been solved,” he told us. “As of last month, there are hardly any reports of latency.” We’d barely gotten our own coffee, and he was telling us the thing we were here to work on wasn’t a problem after all?
The three of us looked at one another and silently decided to put that question aside for the time being. We were to find out the next day what Kevin meant. Some work had indeed been done to speed up the system, but his office had sent a memo defining latency as a delay of over two minutes. If you clicked on a button or link, waited for a minute and fifty-nine seconds, and the page appeared, you were not to report latency. You could easily start a pot of coffee in that amount of time, or already be drinking a fresh cup of tea. But officially, that wasn’t a problem; Kevin had defined it away.
We knew the first thing we needed to do was to define and count the EDD’s backlog of unemployment claims. The department had publicly said that 239,000 claims were backlogged, but state legislators were convinced it was much higher based on what they were hearing from their constituents. They also angrily noted inconsistencies in how the department was reporting on the number of pending claims each period. Without a clear and consistent definition, each report was comparing apples to oranges, and we would never know how fast the backlog was shrinking—or growing, as the case turned out to be.
The job took the entire seven weeks that the task force had been convened for. Mikey and the EDD team were refining the queries right through our very last day on the job. And the final number was not 239,000, plus whatever other applications had become backlogged during those seven weeks. It was 1.2 million.
In a waterfall organization… data functions less like a compass that helps you steer and more like an after-the-fact evaluation, a grade you get that says how well or poorly you did on something that has already happened. That’s why there was such a big fight at the state assembly’s EDD hearings about how many claims were backlogged. Paula wanted the backlog to be 239,000, not the 1.2 million it was eventually assessed at, because while the difference may only have been between a D and an F, that mattered to a leader who cared about the reputation of her department. For people stuck in waterfall frameworks, data is not a tool in their hands. It’s something other people use as a stick to beat them with.
Why Do We Persist With Waterfall + Second Order Implications
We’ve established that waterfall culture has many negative first order implications. But why do we persist with waterfall, and what are the second order implications of a government run in this way?
Let’s start with the cultural and historical factors that keep us in the waterfall mindset.
Intellectuals vs. Implementers (“Mechanicals”)
Waterfalls are hierarchical, with a certain status imbued to those at the top. Elected legislators are doing the intellectual work of setting policy. The mechanics of implementing policy is left to harried government staff (aka “bureaucrats”).
Policy people tend to see those working to implement the policy decisions they make as being far below them in the pecking order, perhaps even at the bottom of it.
The British civil service traditionally divided the work of government into two categories: the intellectual and the mechanical. Although Koskinen [senior official of Office of Management & Budget (OMB)] wouldn’t have used those terms, it would have been easy to see the field of digital technology in 1995 as just the latest evolution of mechanical work. It didn’t belong in the OMB or anywhere else in the White House, where intellectuals were engaged in important, strategic work. It belonged wherever mechanicals bought things that carried out those strategies. So even as computers and the internet began reshaping society as we knew it, government leaders simply handed anything digital off to purchasing officers. They had more important things to think about. They did policy.
This specific example is about how technology expertise has been viewed in government, but it applies more broadly to a hierarchical way of thinking. Intellectuals are at the top of the pecking order, making policy pronouncements from on high. Government staff are tasked with the mere mechanics of implementation. One can imagine an alternate structure, where the truth comes up from the “factory floor” (a Lean principle of improving outcomes by truth-seeking close to the actual problem) and we build stronger bi-directional communication channels so those learnings can be incorporated into policy.
Per another quote from the book:
The way the administration managed the program looked “almost as if they thought that actual governing, the nuts and bolts of governing, is for peons. And they are policy people.” Intellectuals versus mechanicals. Policy people versus operational peons. You can almost hear Koskinen reminding Congress that the digital world was “operational in nature” and didn’t fit with OMB’s policy role.
This hierarchical way of operating can lead to distance, distrust, and ultimately disdain:
Privately, some California officials told me they thought the EDD staff was just incompetent at technology and our team would find the problems easy to fix.
In fact, the EDD staff wasn’t incompetent at technology. They were being asked to operate an impossible-to-operate system, built on layers and layers of technology and policy. But operational failures lead the policy class — and the public who elect them — to escalating levels of distrust and disdain.
Government’s obsession with requirements—voluminous, detailed requirements that can take so long to compile that the software is obsolete before it’s even bid out—stems from a delusion that it’s possible to make a work plan so specific that it requires no further decision-making.
This culture of distrust, and the attempt to remove human decision-making and agency in the system, is so strong that even when the original law leaves discretion to the implementers, the culture of government drives strict, risk-averse implementation over time.
In the business world, they say that culture eats strategy for breakfast—meaning that the people implementing the strategy, and the skills, attitudes, and assumptions they bring to it, will make more difference than even the most brilliant plan. In government, culture eats policy. Even when legislators and policymakers try to give implementers the flexibility to exercise judgment, the words they write take on an entirely different meaning, and have an entirely different effect, as they descend through the hierarchy, becoming more rigid with every step. When rules rarely have their intended effect, more rules are not likely to improve outcomes.
Old Governing Paradigm
Before the New Deal, the federal government didn’t do all that much — it mainly collected tariffs and delivered mail. Then for a period during and after the New Deal, it did a lot, and was innovative and experimental in its approach. As FDR said at the time, in response to critics who wanted to subject the new agencies to more legal oversight, “Substantial justice remains a higher aim for our civilization than technical legalism.”
Starting in the 1950s and 60s, for many valid reasons — urban renewal, environmental degradation, general regulatory capture — we started reigning in the power of the agencies, and we did this using a judicial vs. administrative paradigm.
As Jen explains, via insights from Nicholas Bagley’s Procedure Fetish (25 min):
Agencies today are supposed to implement our laws, turning high-level direction from Congress into the practicalities of functioning government. But they’re made to do that while operating like they’re constantly in court.
The result is that very procedure-heavy, cumbersome, and lengthy decision-making processes—which are necessary and appropriate for high-level decisions—bleed into determining the details of implementation. There absolutely should be a lot of debate, due process, and formal rules governing the commitment to provide food assistance to the needy nationwide. But precisely how to word the questions on the application for that food assistance might benefit from less debate and more informed research.
Judges do not seem to care about speed, whether in the courtroom or in administrative agencies. As one analysis puts it, they want agencies to practice “intensive, multipolar forms of deliberative rulemaking,” and they tend to punish them if they deliberate too little or consult too few stakeholders.
As Bagley remarked in a recent podcast with Ezra Klein (81 min), this is ultimately an issue of calibration. The New Deal era absolutely contained excesses of administrative state power and the trampling of minority rights, and judicial oversight was a necessary corrective. But has the pendulum swung too far in the other direction? If we ascribe the risk-averse culture of EDD’s Paula and VA’s Kevin to these changes, which lead to procedures displacing outcomes as the ultimate goal, then I’d argue it has.
Cramped Professional Thinking & Technocratic Fussiness
We’ve pointed out the hierarchical distinction between the policy class and the implementation class. This exists at the macro level (Congress vs. Agencies) but also within agencies themselves. There are folks who are writing policy implementation language — and by some accounts there are 10x as many words in regulation as in statutory law — and folks implementing that language on the ground. Again, the policy makers have the upper hand, and their thinking is dominated by a legalistic commitment to “correctness,” narrowly construed.
This culture of technocratic fussiness, which gets the details technically correct but adds up to nonsense, is a traditional critique by the political right. This is framed as a critique of expertise, which in its output lacks common sense (e.g. a set of processes that yield a $1.7m toilet in San Francisco).
Jen explores this theme via the story of a US Digital Service product manager, Natalie Kates, who is attempting to simplify the experience of doctors signing up for a new Medicare program, but is clashing with a team (MITRE) of fussy technocrats.
The MITRE team wasn’t trying to be difficult. They were trying to be accurate. And technically, they were right.
“I understand that it’s complicated,” she told the MITRE team. “But it needs to make sense to a person.”
Making sense to a person is something that often gets lost along the way.
To them [the MITRE team], simplicity came at the expense of what was technically accurate according to the law, and accuracy was their job.
“Professional” isn’t often meant to be derogatory. But it’s an expert with specialized knowledge who will insist on nine different definitions of a group. Sometimes it’s lawyers who do this, but other experts in niche subjects are just as likely to. Their identity—and the measure of their value—can become deeply tied to the specialized knowledge they possess. And that knowledge, which ought to serve the goals of the program, instead begins to serve its own, often conflicting goals. It becomes master of the people who wield it.
When a service designer like Natalie says, “I understand it’s complicated, but it has to make sense to a person,” she is rejecting elite, professionalized authority in favor of something more accessible, practical, and commonsense. She is also invoking a historically deeply rooted notion that we, the people, are allowed to interpret the law in ways that make sense to us.
It is only recently that we have given over the ultimate power to interpret law to such professionalized authorities. Law scholar Larry Kramer, describing what he calls “popular constitutionalism,” explains that courts were never considered the final say on interpretation of the Constitution until the late twentieth century. The system was originally designed to have play between the views of the different branches of government and ultimately to allow the public to choose the winning interpretation.
Liberals’ penchant for suing to enforce regulations contributes to the cramped professional thinking that loses sight of the big picture. As scholars have demonstrated, litigation changes agencies over time. To begin with, the more they are sued, the more legal staff they must invest in. But more importantly, courts tend to hold agencies accountable not for their outcomes but rather for their fidelity to procedures, compounding the accountability trap the bureaucracy is already stuck in.
Second Order Implications of Waterfall
The waterfall culture that dominates government, which generates process and paperwork and extreme risk aversion, makes the status quo dominant. If you’re an incumbent and you want things to stay the same, the system is stacked in your favor. In its ever-growing complexity, the system favors the big/rich over the small/poor — after all, who has the money to pay for the lawyers and expertise needed to wrangle with this system?
Waterfall is also terribly suited to a world that is increasingly complex and fast-changing.
To the extent that we define “progressive” as wanting progress, then our current waterfall system is deeply conservative and makes any kind of progress — toward egalitarianism, racial justice, a clean energy transition, etc. — much harder.
And yet liberal and progressive politics do not currently feature a critique of our hobbled state capacity.Progressives would be well-served to put more attention on this important issue in the years ahead, re-assessing the cost benefit analysis of a powerful government vs. an incapacitated one.
Conclusion: Where Do We Go From Here
As I’ve caveated several times, this book may critique government, but it is ultimately a love letter to government and the good it can do when public servants have the courage to push back against the waterfall. There are many success stories featured in the book, including projects like Covidtests.gov, the Center for Medicare Services’ MACRA implementation, and even healthcare benefits at the VA. There are stories of many capable public servants doing great work in government despite the difficult operating environment we’ve set up for them. Positive changes are afoot.
Still, lots more work needs to be done — there are many layers of dysfunction to pull back. And while there are some policy fixes, these are principally *cultural* problems. Culture is hard to change — but not impossible!
To conclude, I’ll highlight a few closing themes from the book, including (1) a vision for how the administrative state should work (2) the stakes for improving state capacity and (3) the role we (readers of this post) can and should play.
The first is a vision for how the administrative state should work: we should be driving toward a system that enables “product management.”
Project management is the art of getting things done. Product management is deciding what to do (and what not to do) in the first place.
The right is deeply skeptical of the bureaucracy on principle. The left sometimes is too and may see the empowerment necessary for product management as fundamentally undemocratic. Staged rollouts that don’t try to serve all users equally from day one can be seen as inconsistent with values of equity and inclusion, even if they serve everyone better in practice. On the flip side, diffuse authority and consensus-based decision frameworks appear to promote inclusion; in fact, they are thought of by people of all political persuasions as hedges against abuse of power.
But I would argue that good product management, or whatever other name you want to give it, is not only helpful but necessary to honor the core values of American government. It is not an excuse to go rogue; it is a path to getting the outcomes the democratic process has agreed upon. When done well, it appeals to the better angels of both the left and the right.
The second is that the stakes for this State Capacity movement are high. In my own words, we need to rapidly shift the debate from Big vs. Small government to Effective vs. Shitty government.
In his 1966 book The Nerves of Government, Karl W. Deutsch said, “Power is the ability to afford not to learn.” When power flows one way—down the waterfall—from policymakers to implementers, from federal to local government, from those with high-priced lawyers and tax accountants to those without, even those the system appears to benefit lose out. Is it any surprise that the most powerful institutions within the most powerful country on earth have resisted the uncomfortable work of developing new and foreign competencies? If our timing is better in this moment, it may be related to our nation’s loss of power. Our global standing isn’t what it was in 1995. Our response to COVID was embarrassing, our tax system is the joke of the developed world, our military might is waning, and our health outcomes rank dead last among eleven peer countries. We can no longer afford not to learn new tricks.
What could a government that delivers at internet speed and scale achieve? And what role might each of us play in bringing that vision to life? If we lack that faith in government, perhaps we need to reframe the question. “Government is simply the name we give to the things we choose to do together.”
The third is that we — citizens — should rally to this work. As Teddy Roosevelt said, “The government is us; we are the government, you and I.”
If our elected leaders have the wrong incentives, perhaps there is one more layer up the chain to implicate. In our system of government, no sequence of causes can end entirely with our elected officials, in Congress or elsewhere. There is still someone above them, and in fact above all three branches of government: us. Yes, there is a staggering amount wrong with our electoral system and campaign finance laws, which has loosened the connections between what the public wants of its leaders and what it gets. But that doesn’t give us as a public the right to absolve ourselves of all blame in our government’s failures of delivery, nor does it let us off the hook for what role we might play in fixing them.
And a final note: we “elites” — as in people who are reading this Substack post — should be particularly committed to this work. We should care about implementation, even of programs we don’t directly use, vs. getting caught up in the aesthetics of policy pronouncement.
The shortcomings of government service delivery affect different parts of society very differently. If you can afford to pay someone else to handle your taxes, your car registration, your building permit, even your passport renewal, chances are that you will do so and that you won’t notice the burdens they impose. At the same time, you’ll be less likely to apply for social services, deal with child welfare agencies, be involved in the criminal justice system—all high-burden interactions, and all interactions that tend to erode trust in government.
For people who do have to deal with such interactions, delivery matters a lot more than politics. But politicians rarely get voted out of office for failing to clear the criminal records of former felons or making it hard for the needy to access food benefits. Instead, the people who get burned in those ways tend to pull away from politics and government altogether. Their experiences teach them that the whole system is hopelessly broken and not worth their time or energy engaging in. They are not going to feel differently about government unless and until they experience something very different from what they have in the past. Delivery must come first. The only way to build trust with them is to earn it.
Thanks to Jen Pahlka for writing such a great book, and allowing me to summarize it here. Pre-order the book here!
Also thanks to Monica Chellam and Jesse Wolfson for editing help.
In my opinion “civic tech” (e.g. orgs like Code for America or US Digital Response) have been hampered by this common brand misconception that their core work is IT / websites. Policy makers thus consider it as off to the side of “real” policy.
We can analogize this to scientific discoveries. Advances like penicillin, plastic, and gunpowder were discovered by accident. Better solutions are discovered via experimentation and iterative learning. If we optimize our policy-making process for faster feedback loops, our outcomes should improve.
Both names are pseudonyms.
In contrast with waterfall, an agile paradigm uses data for learning.
In the tech industry, as a counterpoint, engineers, the doers/implementers, are the first-class citizens.
Though that’s starting to change via the work of folks like Ezra Klein and Jerusalem Demsas among others.