But despite 2020's technological leaps, government still remains behind the humanity it serves, and so must race to transform. Remember, waiting in the wings are rapidly maturing technologies, from gene editing to self-driving cars. To truly harness these technological advances, government should act quickly, and be both deliberate and flexible.
How should government transform? What should government look like five or ten years from now?
Given that government has so many missions, departments and varied activities, it's hard to contemplate its broader future through those vertical lenses. To help, in a Deloitte report entitled Creating the Government of the Future my colleagues and I identified five principal domains of government activity that are ripe for technological transformation: service delivery, operations, talent/workforce, policy- and decision-making, and regulation and enforcement. Virtually all government agencies are engaged in each of these domains, albeit in different proportions.
Service delivery: In Estonia, taxpayers can file taxes online simply by approving forms auto-populated with their income data. This ease represents the future of service delivery: focused on the user, automated for no-touch government that serves people without them having to fill out long forms. (Think hospital data of a birth triggering a birth certificate, Social Security card and health-care record for the child and family allowance payment to qualifying parents.)
Services will more and more tailor to such anticipated life events. Ideally, a single login omnichannel experience provides access to tasks as varied as collecting unemployment benefits to registering to run for office. With once-only government, citizens and businesses need only provide their data once, and it's then shared across departments with appropriate privacy protections.
Operations: Government operations should take a cue from the private sector, where technologies like data analytics and cognitive automation converge to create serious efficiencies. Operations from HR to procurement can combine in an integrated center office, creating insights from shared, analyzed data about what to expect and how to improve. "As-a-service" acquisition allows contractors to provide basic infrastructure, such as cloud services, leading to faster scaling. To transform operations, strike teams of specialists and subject-matter experts meet in digital factories, using agile processes without traditional bureaucracies.
Policy- and decision-making: Evidence-based policymaking can identify what approaches produce the best results. With artificial-intelligence-based scenario analysis, machine learning can test the relationship between factors in systemic problems. Potentially, understanding these relationships could allow policy to be self-correcting. Likewise, increasingly sophisticated statistical models will allow government by simulation — a cheap way to A/B test systems like traffic management, disaster response and city planning. Meanwhile, mass-communication tools enable crowdsourced and distributed policymaking, in which ordinary citizens contribute their expertise.
Regulation and enforcement: The future of this governmental domain is tied to the predictive abilities of AI and analytics. In a form of risk-based regulation, for example, AI can identify factors likely to contribute to a food-borne illness outbreak, helping food inspectors focus energies on restaurants more likely to violate. Modeling systems to identify beneficial behaviors can enable positive enforcement strategies, which reward a business' focus on the big picture and going beyond the bare minimum. Lastly, countries like New Zealand have experimented with legislation written as software code. The bureaucratic effects of the legislation could be simulated ahead of time.
Talent/workforce: Flexibility will be the hallmark of the future public workforce. NASA and other agencies are trying a talent marketplace model, in which some workers have the ability to move from project to project, even between agencies, based on their documented skills. Talent won't go to waste in this just-in-time civil service. Such a talent marketplace would cover an open talent spectrum, from freelancers to career employees.
The flexibility goes two ways. Workers may yo-yo between jobs, but will increasingly work in adaptive workplaces — places where they are most productive and engaged, whether in offices, at home or a hybrid of the two. Meanwhile, human-machine collaboration can provide civil servants with AI-enabled tools to be more productive and effective in their jobs.
The challenges of 2020 forced a high-volume field test of technological and organizational edge cases. Many survived to become mainstream, while others kickstarted further intersections of technology. As we face a transformed economy with transforming needs, governments must adapt. Can an institution designed in an era of incremental change succeed in an era of transformation? Absolutely.
Governing's opinion columns reflect the views of their authors and not necessarily those of Governing's editors or management.
