Tech takeoff: A guide for governments to soar in technology transformation

Technology leadership in government may need a new decision-making approach to drive digital transformation.

Tim Li

United States

John Forsythe

United States

Joe Mariani

United States

Cathryn van Namen

United States

Being a government technology leader can often feel like a scene out of an action movie: flying at top speed between vertical cliffs, making quick decisions, and relying on technology to “see.” The difference is that in place of a fighter jet, leaders are often piloting whole organizations, and instead of cliffs, any number of hazards could “crash” technology projects.

The good part? Just as fighter pilots are trained to help make decisions to manage those risks, the same can be done for government technology leaders. Schools such as the Navy’s Strike Fighter Tactics Instructor or the Air Force’s Weapons School were created to provide a common foundation in tactics and decision-making to make the best fighter pilots even better. Government technology leaders may need something similar—a new decision-making approach that blends insights about their organization’s technology, work culture, and mission that can help them guide their teams to new heights of mission accomplishment.

The world has changed, decision-making should change too

Over the past decade, digital trends such as cloud adoption, ever-improving AI, and the explosion of data have fundamentally changed the environment in which government organizations operate. Government organizations are under constant pressure to keep pace with the rapidly advancing technological innovation. Leaders increasingly need to deal with technology that influences how work is done, where it is done, and who does it. A 2020 Global Technology Leadership Study found that technology leaders anticipate that only 67% of their current staff will be relevant based on their current skill set.1

While technology may be driving some of this change, it is not the sole solution. Besides, simply modernizing outdated systems may not be enough; organizations need to align those technology investments with their organizational culture and mission. If not, modernization efforts could fail. A study about government technology projects found that projects valued over US$6M succeed in being on-time, on-budget, and on-mission only 13% of the time.2 While there are myriad reasons that any particular project could fail, a misalignment between the technology and the mission and culture of an organization is often a common cause.3 Department of the Navy chief data officer Duncan McCaskill sums it up: “The biggest challenges that we have in the Department of the Navy are not necessarily technical, and it’s not necessarily dealing with workforce. It is cultural and changing our way of thinking about data.”4

So, just as a jet pilot needs information about not just the status of the jet but also its location and altitude to fly safely, technology leaders should have insights not only about technology performance but also about cultural alignment and mission effectiveness. For example, when Lidl, a major European grocery chain, decided to adopt a new enterprise resource planning system, they discovered a mismatch between how the technology tracked costs and how the company traditionally did it.5 Fearing that changing processes would undercut their mission of being a low-cost store, Lidl chose to modify the technology. However, significant leadership turnover undermined the cultural shift needed to accomplish these changes, leading to a €500 million loss.

That said, experiences such as these can help illuminate the path to successful digital transformations. When technology is paired with effective culture management success rates tend to spike. This new era likely requires a new approach to decision-making if leaders are to guide their organizations safely to the mission benefits that modernization promises.

Getting from a few insights to deeper understanding takes change

Government leaders make big decisions every day—reviewing dashboards and stoplight charts is already part of their typical day-to-day. They have data, but are they digging deep enough? Perhaps no. What government technology leaders may need is an approach that helps them:

Get actionable insights, not just siloed data points: Government organizations today are awash in data. And that is not a bad thing. Data is a critical ingredient in decision-making, but what leaders may really need are insights about the status of the organization with quantifiable risk. Dashboards that merely display data are often underwhelming and can even provide a false sense of security in the apparent precision of their numbers. What leaders may really need are tools that can provide context to real-time data so that they can pull out insights about how technology is impacting the organization.

Go deeper than just technology: The right insights are not purely technical. Even if the technology is working flawlessly, the organization can still fail. At times, employees can resist using new technology and work around a system that they feel inhibits the mission, rendering the modernization effort useless. Technology is valuable to an organization in so far as it helps the mission and enables humans to deliver. Therefore, what leaders need are insights about the status of technology, organizational culture, and mission all in the same place (figure 1). 

Understand mission outcome, not just outputs: Many chief information officers have traditionally had a technology background and so, it may be natural for them to measure digital transformation success using technology as a yardstick. In a 2021 Deloitte survey of government executives, “delivering on mission” was ranked as a distant fifth rationale for digital transformation.6 The continued focus on purely technical measures of success, such as reduced downtime, risks diminishing the return on investment on digital investments. Over the years, technology has increasingly played a central role in delivering mission for governments. Therefore, the ultimate measure of success for digital transformation may be improvement to mission outcomes, not technical outputs.

Blending insights about mission, culture, and technology into a new decision-making approach

Knowing how this new approach can go beyond familiar forms of decision-making is just the start. Leaders should have a way to combine all of the ingredients of this digital way of thinking into a coherent decision-making approach.

Here, government tech leaders can take a page from their pilot counterparts. Just as programs such as the Air Force Weapons School train professional pilots to be even better, with the right “syllabus,” government leaders can train themselves to be even better, too.

It all starts with learning how to use the tools available. Insights about the status of an organization’s technology, culture, and mission outcomes are similar to gauges in a fighter jet. Take the example of a government agency looking to modernize its identity access management to prevent cyber attacks. Technology “gauges” can include a number of inactive user accounts, time taken to activate an account, failed password attempts, and access removal. However, such metrics may not be useful unless they’re paired with “gauges” of organizational culture such as response rate, customer satisfaction scores, adherence to policy, and so on. And finally, all of those should be viewed in the context of the mission. Even if the number of inactive accounts is low, and customer satisfaction is high, if workers are struggling to deliver government services, then the solution is likely not working.  

Much like a fighter pilot needs to learn how to do an instrument scan from gauge to gauge, tech leaders need to learn how to integrate insights from their “gauges” to form a picture of the organization’s functioning.

Tech + mission: Adopting a mission-first mindset

The first step to integrating all the insights technology leaders need is not an action, but a recognition: the goal of technological change isn’t just new hardware and software working properly; it’s an improvement to mission outcomes. For a human services agency providing assistance to low-income families, that mission improvement could be proactively identifying families at risk of food insecurity. For an intelligence agency, it could be the number of threats detected and, for an economic development agency, it could be the number of new businesses established.

The shift, then, is not seeing technology performance and mission outcomes as distinct measures, but as interrelated. Technology performance measures should have a clear line of sight to the mission outcomes they support, and those mission outcomes then should be linked to the technologies that make them possible. Linking technology performance to mission outcomes can help government agencies streamline technology investments, better navigate disruptions, and ultimately improve mission performance.

For example, the Air Force Research Laboratory’s mission is to spearhead the identification, advancement, and deployment of combat-related technologies. The Air Force is collecting on-orbit, commercial, geospatial, and drone image data to train AI to identify ballistic missile launch vehicles in as near real-time as possible. The goal is not simply to adopt AI, but to help enhance the Air Force’s mission of safeguarding the country.7

The Air Force isn’t the only federal agency to use data to help improve decision-making. One of the missions of the National Oceanic and Atmospheric Administration is to monitor global weather and climate.8 The agency is deploying new technologies to improve the accuracy and timeliness of forecasts. It uses the predictive capabilities of a machine learning algorithm developed at Colorado State University to forecast future rainfall and flood risk.9 This algorithm is also integrated into the Weather Prediction Center to provide the public with enhanced flood risk forecasts across the United States.

Tech + mission + culture: Driving change through organizational culture

Aligning technology with mission is only part of the solution. But even the best technology that is well-aligned to the mission can run into problems. Asking an overburdened workforce to use new technology, for example, can lead to resentment and workarounds that can undermine the intended function and efficacy of the technology.10 In short, when introducing a new technology to enhance digital transformation, it should be met with a corresponding shift in culture and how work happens within that organization.

Adapting culture to make decision-making more data-driven can be difficult for many organizations, but it’s a change that can pay off in the end. In a survey of 1,000 business executives, organizations that reported the highest rates of using data in their decision-making processes were twice as likely to have significantly exceeded business goals.11

Take the Department of Defense as an example. DOD’s mission depends on recruiting the soldiers, sailors, airmen, and marines needed to defend the country. But DOD has traditionally struggled to recruit candidates with the talent in some of the cutting-edge areas that are becoming critical to the future of combat.12 However, a strategic, realigned culture shift is helping tackle that problem. DOD has started thinking of its reserve force as less of a backstop in case of war, and more of a unique pool of talent. With 1.2 million reservists all working in other careers, the reserve force often possesses unique skills not found elsewhere in the force. For example, the Marine Corps’ Marine Innovation Unit is a new unit designed to be staffed almost exclusively by reservists in order to tap into their unique technical skills and ties with industry in an effort to spur innovation.13 With that new culture beginning to take root, DOD is adopting technological solutions such as talent marketplaces that can match individual reservists to jobs that need their unique skills.14 Mission outcomes can drive a culture shift that fuels a technological transformation.

What is organizational culture?

Leaders may realize the importance of organizational culture, but it can be difficult for them to describe it.

 

In its most basic form, organizational culture is the system of beliefs, values, and behaviors within an organization. Culture is the recurring behaviors modeled by leaders and tolerated by those leaders in the people around them. Put simply, culture often drives the way work gets done around here. While beliefs and values can often be invisible, ingrained behaviors and the artifacts of culture can be more readily apparent. They can be stories told about the history of an organization, its rituals and routines, the processes used to evaluate performance and promotions, or even physical signs and symbols.

 

Although culture can be invisible, it should not be ignored. Culture produces powerful elements that can help improve mission performance—it can act as both an “accelerator” for success by incentivizing behaviors to strategy and a “signpost” indicating the level of alignment between mission and the people, processes, and technology of an organization.

 

Culture used to “just happen,” and given the disruptive nature of technology, leaders can no longer rely on the old ways of creating and reinforcing culture. Getting the right insights about the state of organizational culture can begin with understanding the diverse factors that influence it (figure 2).

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An example: Coping with the shock of generative AI

A decision-making process that blends technical, organizational, and mission data can not only be useful in planning digital transformations but can also help leaders respond to unexpected disruptions. Take generative AI as an example. It is hard to find any industry, from academia to manufacturing, that is not wrestling with the unprecedented ability of generative AI to create convincing text, images, video, and sounds. Generative AI can help government agencies with a variety of tasks from writing contracts more quickly to designing public transit systems.15

But with the promise of generative AI comes technical challenges. On one hand, there are technical risks from potential exposure of sensitive or private information. Adversarial efforts to manipulate AI models have been shown to be able to extract sensitive data or even influence a model’s outcome. On the other hand, there are social risks as well. Without proper support to workers and messaging to the public, government use of generative AI has the potential to undermine trust in government decisions.

Generative AI isn’t a stand-alone wonder technology. It needs other technologies, such as data management and cybersecurity, to work safely and effectively. Human intervention is also necessary to ensure that the output generated by the technology is trusted by users. To effectively use generative AI, organizations should have new business processes built on the principles of human-machine teaming. Moreover, organizations shouldn’t just bolt on generative AI simply because the technology is available. Rather, leaders should consider beginning their thinking not with the technology, but with the mission outcome they are looking to deliver. This perspective can help them think deeply about if, where, and how generative AI can help the mission, and how organizational culture can enable its success. They can then craft technical solutions that meet those needs and create the culture interventions that can allow human workers and the new AI to work together effectively.

Leaders may need to build new decision-making muscles

With a clear approach to intertwining technology, culture, and mission insights into a single decision-making process, leaders now just need to practice. Three lessons gleaned from fighter-pilot training can help tech leaders build the right decision-making muscles. Similar to tactics for fighter pilots, decision-making for government tech leaders should be: 

  • Trainable
  • Continuous
  • A team sport, not an individual one

Leaders can be trained on decision-making

As leaders rise in an organization and change roles, they often see that the data they need for decision-making keeps changing. The way they make those decisions should change accordingly (figure 3). 

Regardless of level, leaders can train the appropriate skills. There is often a common approach across all levels. Pilots and technology leaders alike should have training to constantly scan for changes in the environment and adjust quickly using the “observe-orient-decide-act” technique. For technology leaders at any level, decision-making should factor in both short-term and long-term objectives that include technological, cultural and mission effectiveness factors.  

Decision-making is a continuous process

Making sure that technology, culture, and mission metrics are aligned is not a one-time exercise. It should be part of a persistent cycle. For example, introducing a new technology to address a mission shortfall could create an organizational need for talent with new skills. To address that need, leaders could create a new learning platform to help the workforce develop the needed skills. But with additional time that may be required to train them on new skills, leaders should monitor mission metrics to ensure that there has been no drift in performance, and so on.

Decisions should not be taken in isolation

The myth of the heroic individual leader is a powerful one but can also be a dangerous one. No single leader can be everywhere or know everything. So, concentrating all decision-making authority in one individual can inevitably lead to dangerous errors. Rather, the more that organizations can institutionalize these principles of decision-making, the better their decisions can be. Leaders, even at the lowest levels, should be trained in these methods, with their pay, promotions, and incentives tied to the same technology, culture, and mission metrics they are using for decision-making—driving that thought process throughout the organization. Then there’s not only one good decision-maker; there is an entire team of good decision-makers.

The city of Memphis applied these skills when officials developed a pilot program using AI and machine learning to tackle the city’s persistent pothole problem. Prior to the pilot, Memphis spent 32,000 hours repairing over 60,000 potholes a year—most of which had to be found and fixed by road crews driving around the city. Rather than just deciding on a technology, Mayor Jim Strickland took the problem to the city’s chief information officer, Michael Rodriguez. With a clear idea of what their mission outcomes and citizen preferences were, they came up with an innovative solution to use existing bus cameras and AI to identify potholes for crews to fix. The result was a 75% increase in potholes fixed and savings of more than US$200,000. The process started with a leader who identified the challenge, but ultimately, a team of city employees and tech companies who were all on the same page solved the problem.

Getting started

Flying a jet faster than the speed of sound can seem impossible when just learning to fly. Similarly, adapting an entire organization to a new digital decision-making culture can seem daunting. But government organizations around the country have found that with a few concrete steps, they can get started toward a better future:

Prioritize and communicate the organizational mission and values with key metrics to how outputs will be measured

See it in action: The Office of Digital Services Georgia serves as an example for this in the state of Georgia. According to Nikhil Deshpande, Georgia’s chief information officer, the goal of Digital Services Georgia is to design user-friendly technology that makes life easier for state residents. To ensure the solutions are meeting users’ needs, Digital Services Georgia launched the Digital Center of Excellence, a state-wide community of public- and private-sector technology professionals. The community meets regularly through two committees and discusses how technology solutions are progressing as well as new ideas and challenges. The regular communication helps to ensure the solutions meet the guidelines and values of the organization—and that the Digital Services Georgia team is aware of how the technology solutions they create are affecting people’s lives.

Create pathways to get continuous input from mission leaders, so that technology leadership can build trust beforehand without having to devote time to networking

See it in action: Arizona created a multi-agency review process as it started transitioning from traditional data centers to cloud solutions. Eventually, the state was able to close 85 on-site data center facilities and move 90 different agencies’ emails, calendars, and collaboration tools—2,600 applications in all—to a cloud-based platform.

“We have a governance process and we’ve included representation from all agencies to review the controls and to advise on best processes, with standards around how we execute the various security controls,” says Arizona’s chief information officer, J.R. Sloan.16 “When COVID hit, we had the relationships and the organizational infrastructure in place to facilitate communication in order to be able to respond rapidly,” he adds.

Include mission impact metrics in acquisition processes so that technology buying decisions can have a clear link to mission accomplishment and required culture shifts from the start

See it in action: Based on a recommendation from the Minnesota Technology Advisory Council, Minnesota IT created an Office of Transformation and Strategy Delivery and a playbook that serve as the foundation for their technology projects. This system makes it easier to help ensure the projects deliver the intended value. As an extra layer, IT projects expected to cost more than US$10 million are regularly reviewed and must be independently audited once a year.

Create a learning pipeline to help leaders at every level make decisions pertaining to digital transformation

See it in action: Digital Services Georgia created a comprehensive training program to help ensure decision-makers at all levels have the knowledge and skills to use digital solutions and address challenges. The program, known as the Learning Management System, is in addition to live webinars. The training models include courses and content for agency site editors to help them seamlessly navigate digital tools. The agency also publishes regular blogs to share information and insights.

A course, such as the Air Force Weapons School, may end, but as any fighter pilot will tell you, training never does. Embracing that lesson can help put your organization on the journey to more mature, agile, and effective technology decision-making.

By

Tim Li

United States

John Forsythe

United States

Joe Mariani

United States

Cathryn van Namen

United States

Endnotes

  1. Khalid Kark, Ahn Philips, Bill Briggs, Mark Lillie, John Tweardy, and Scott Buchholz, The kinetic leader: Boldly reinventing the enterprise, Deloitte Insights, May 18, 2020. 

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  2. Mark Lerner, “Government tech projects fail by default. It doesn’t have to be this way,” Perspectives on public purpose blog, Harvard Kennedy School, October 21, 2020.  

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  3. One Gartner survey of government technology leaders found that siloed mission decision-making and culture were the top two barriers to modernization. See: Gartner, Transitioning to digital government in 2022, 2022.  

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  4. Cate Burgan, “Navy CDO touts new policies aimed at shifting culture,” MeriTalk, March 15, 2023. 

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  5. Henrico Dolfig, “Case Study 12: Lidl’s €500 million SAP debacle,” May 5, 2020.

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  6. William Eggers, Jason Manstof, Pankaj Kishnani, and Jean Barroca, Seven pivots for government’s digital transformation, Deloitte Insights, May 3, 2021. 

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  7. Brandi Vincent, “Air and space forces lean into data-driven decision-making,” DefenseScoop, March 22, 2023. 

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  8. National Oceanic and Atmospheric Administration, “Our mission and vision: Science, service, and stewardship,” accessed November 30, 2023. 

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  9. Anne Manning, “CSU machine learning model helps forecasters improve confidence in storm prediction,” Colorado State University, February 26, 2023. 

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  10. Sara Hinkley, “Technology in the public sector and the future of government work,” UC Berkeley Labor Center, January 10, 2023. 

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  11. Thomas H. Davenport, Jim Guszcza, Tim Smith, and Ben Stiller, Analytics and AI-driven enterprises thrive in the Age of With, Deloitte Insights, July 25, 2019. 

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  12. Inspector General, US Department of Defense, Fiscal Year 2022: Top DOD Management Challenges, November 2021. 

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  13. Megan Eckstein, “Marine innovation unit tackles some remaining force design needs,” DefenseNews, May 10, 2023. 

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  14. eightfold.ai, “GigEagle: The solution to the DOD’s talent discovery challenge,” blog, accessed November 30, 2023. 

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  15. For contract writing see: Jory Heckman, “DoD builds AI tool to 'speed up' antiquated process for contract writing,” Federal News Network, February 9, 2023. For city planning see: Sidewalk Labs, “Delve,” accessed November 30, 2023. 

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  16. Adam Stone, “Digital States Survey 2020: Cloud is more critical than ever,” GovTech.com, October 23, 2020. 

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Acknowledgments

The authors would like to thank Franklin Sherrill and Apurba Ghosal for their invaluable contribution in shaping this piece. They also thank Abrar Khan and Shambhavi Shah from Deloitte Insights for their editorial support and inputs.

Cover image by: Jim Slatton