Ahead in the cloud: Transforming public-sector performance

The COVID-19 pandemic highlighted the importance of cloud technology and analytics in delivering public-sector services. Can governments build on what they have learned?

The COVID-19 pandemic sent companies, governments, and public agencies across the world scrambling to find new ways to deliver services. Workforces shifted to working partially or even fully remotely; existing services were scaled up or down and reconfigured to changes in demand; and essential new services were rapidly introduced to deal with new delivery needs in policy making and business.

Listen to this article

Cloud-based IT systems played an important role in enabling these shifts. The performance benefits of the cloud—secure, collaborative multiuser access to cutting-edge software, coupled with expanded storage capacity and analytical capabilities—have long been known. However, adoption in the public sector has been fragmented and ad hoc, and it has often been driven more by the enthusiasm of individual chief technology officers (CTOs) than by policy objectives. In this respect, the crisis has served as a catalyst, and has brought a greater focus on quality data and robust analysis. We have reviewed potential cloud-based analytics applications in the public sector to help pinpoint where governments can achieve the greatest possible business value.

Over the past years, we have collected a comprehensive library of detailed bottom-up use cases, based on significant prework by the McKinsey Global Institute and by our Digital Practices. The results were used in part to inform a framework for helping public-sector organizations identify areas in which cloud-enabled solutions would have their greatest potential impact. This article discusses six opportunity areas where cloud-based analytics applications can potentially deliver the highest possible business value—and also the highest possible return for taxpayers. While the analysis was based on US and European countries, the framework can serve as a guide globally.

The value proposition of cloud should combine long-term business value creation with pure IT cost efficiency

Public-sector spending on cloud technology is forecast to grow at an annual rate of around 20 percent until 2024, that is, double within the next five years (Exhibit 1). Total spending in Europe still lags far behind that of the United States—even when accounting for comparatively larger government budgets. Past investment has not always achieved the best possible value, however.

The United States spends significantly more than major European countries on cloud in government.
We strive to provide individuals with disabilities equal access to our website. If you would like information about this content we will be happy to work with you. Please email us at: McKinsey_Website_Accessibility@mckinsey.com

Prior to the arrival of the COVID-19 pandemic, most business leaders saw the cloud-transformation process as “something for IT to worry about.” Cloud-migration initiatives typically focused on efficiency in IT infrastructure and aimed to reduce operating costs in IT by removing captive data centers, increasing resilience and stability, improving the development environment, and enhancing cybersecurity.

It’s not about money. If you start out with the expense reduction piece, you’ve kind of lost your way in the beginning.

Director, US Technology Transformation Services

But cloud-based efforts focused only on cost efficiency in IT, and they have mostly proven disappointing, as cost benefits delivered were lower than predicted. There were two reasons for this: First, costs and benefits were not quantified realistically and holistically at the outset, creating false expectations. Second—and more importantly—the opportunity to enhance performance through cloud-based transformation was underestimated. Too often, the mindset was “business as usual, but in the cloud.” As a result, services and applications were not redesigned to take full advantage of cloud technology, and potential performance improvements were lost.

There are some examples of successful public-sector cloud-transformation projects, and they demonstrate that in order to deliver the best possible return for taxpayers, business leaders and CTOs need to collaborate and adopt a dual perspective that consists of both improving IT infrastructure and improving business performance. For example:

  • In 2014, the United Kingdom’s Ministry of Defence (MOD) began replacing its core legacy on-site IT architecture with a hybrid cloud-based solution. Migrating to the cloud has cut costs and improved performance. In particular, its 250,000 users can now access modern applications online via multiple devices, and approximately 80 percent of MOD data have been migrated to the servers of United Kingdom–based cloud service providers. Most of MOD’s core IT, nonmilitary architecture is now industry standard.
  • The United States Financial Industry Regulatory Authority (FINRA) is the largest independent regulator for all security firms operating in the United States, and it employs approximately 4,000 employees domestically to monitor financial transactions. As transaction speed and volume steadily increased, FINRA’s in-house solutions reached the limits of their capacity. In response, the agency adopted a cloud-based solution, which allows it to analyze more than 37 billion data sets per day, steer computing capacity where needed in response to changes in market volume, and ensure high performance—even during peak workloads. The system now completes around 400 times as many calculations as it did previously, and it does so at higher speeds, expanding FINRA’s insights on market activity as a result.

Governments should take a systematic and structured approach to determine where cloud technology will unlock the most business value across agencies

Our research, based on previous McKinsey Global Institute and our Digital Practice, drew on two sources: public sector agencies that are undergoing cloud-based transformation processes and extensive interviews with our own public-sector and analytics experts and leaders. The research shows that governments should take a systematic structured approach to unlock the full value of cloud technology.

We have synthesised the results of the research into a heat map (Exhibit 2) that shows cloud-based transformation potential within different government functions (such as defense, general public services, and education) and across different stages of the public-sector value chain—from research and development, to procurement, to operations and claims processing, to citizen interaction. While many additional factors may influence cloud-based transformation priorities, we believe the framework provides a valuable starting point for guiding strategy in the public sector, because it highlights areas where impact is expected to be greatest.

The highest potential for cloud application in the public sector lies in six opportunity areas.
We strive to provide individuals with disabilities equal access to our website. If you would like information about this content we will be happy to work with you. Please email us at: McKinsey_Website_Accessibility@mckinsey.com

Based on our research, we have identified six areas of opportunity where the potential for value creation in the public sector is particularly significant. These are numbered on Exhibit 2 and described in more detail below. The first five areas show the potential impact of transforming core processes—such as procurement or asset management—across one or more government departments. The final opportunity area, digital health, focuses on the potential to transform delivery of an entire service.

Area 1: Improving data management and document processing. Cloud-based solutions can dramatically improve speed and quality as well as reduce costs in general services workflows across all agencies with high volumes of documents—such as healthcare, tax affairs, permit issuance, and licensing. Streamlined processes that enable the use of artificial intelligence (AI)–based applications also allow automated analysis and the integration of incoming data (such as claims-related data). This both improves decision making and reduces the volume of documents for inspection.

Use case example: Healthcare systems generate large numbers of patient-related documents that require reading and triage to validate the next action. Documents pass from one healthcare setting to another, which multiplies the amount of effort required from staff. A cloud-enabled process can allow machine-based document reading, dispatch to appropriate persons, prediction of subsequent actions with a high level of confidence, and provision of supporting information that helps staff members make decisions faster. Well-designed document-management projects have achieved 30 to 40 percent reductions in manual labor while improving service quality in parallel.

Area 2: Reducing asset-management and maintenance costs. Cloud-based approaches can significantly increase asset availability for agencies operating with a high volume of assets, such as defense and public transportation agencies. Systems that automatically track asset utilization, condition, and location (of moveable assets), and that predict shortages and breakdown times, greatly increase accuracy and effectiveness in asset management, which, for example, allows a more optimized distribution of assets.

Use case example: Armed forces rely on prescheduled maintenance of their assets (planes, for example) to ensure that they are ready for operational use. Assets often undergo maintenance operations before they are actually needed to prevent breakdowns or other conditions that would result in unnecessary costs. Unpredicted breakdowns may still occur, however. Cloud-enabled AI applications are able to identify faults and predict maintenance needs through pattern recognition. This allows asset output, capacity planning, and asset distribution to be optimized and ordering processes to be automated. Where cloud-based predictive maintenance has been applied, we have seen savings in equipment repair and maintenance costs of 5 to 15 percent.

Area 3: Enhancing situational awareness and operational control in uncertain environments. When a physical location is difficult to access (during a relief unit operation, for example), cloud-based solutions can integrate information from different sources, such as traffic cameras and satellites, and they can use these data to map an environment and monitor events in real time. This allows holistic, considered analysis of environments without the need for a physical presence, which facilitates improved decision making.

Use case example: During relief operations, units from different organizations—the fire department, police department, and emergency medical services—often need to collaborate in difficult situations with many variables. Personnel may need to go inside a burning building or deal with the aftermath of a terrorist attack, and they may have only limited knowledge of the situation when they arrive at the scene, as well as a restricted means for real-time coordination during an operation. Cloud-based solutions allow operational control for anticipating high-risk situations and coordinating units more effectively through the use of integrative monitoring and analysis of geospatial, body-sensor, and bodycam data. They also provide enhanced interpersonal communications for units on the ground.

Area 4: Preventing inappropriate cash outflows as well as fraud. Cloud-based systems can perform automated analysis of vast amounts of data (financial, for example) to detect patterns and anomalies. This ability gives agencies a means for combating payment fraud and errors occurring in subsidies, welfare payments, or other cash outflows. Cloud-based AI applications also allow more-targeted inspections and methods of fraud prevention. They can, for example, match existing data sets with inspection targets to identify sources in potentially suspicious transactions; detect potential cases of identity fraud in the context of healthcare or welfare claims; and focus tax-fraud-prevention efforts through targeted audits.

Use case example: To detect tax fraud, agencies typically need to scan a large number of documents in the context of one or more audits. Since the amount of data to be processed exceeds the manpower available, only a limited number of cases can be audited, leaving “blind spots.” Rather than rely on random sampling, cloud-based solutions enable machine-learning applications to analyze all machine-readable data available and to identify cases with high potential for fraud. Available manpower can then be targeted at performing detailed audits. If implemented holistically and rigorously, cloud-based solutions can generate savings of up to 0.5 percent of payment totals.

Area 5: Streamlining procurement processes and reducing supply-chain-related risks. Procurement is a particular challenge for agencies that purchase in high volumes across multiple sites. Many public-sector organizations also manage complex supply chains in, for example, defense, public safety, and healthcare. Cloud-based analytics can fully or partially automate procurement processes in spend categories, for example, and they can streamline high-volume procurement across different agencies to increase process speeds and reduce costs. By integrating data on supply, cloud-based solutions can also identify interdependencies in the supply chain, even at a granular level (a tier-3 supplier level, for example), which ensures greater transparency and enhanced risk assessment.

Use case example: Public requests for the provision of assets require that contracts for all offers are stringently reviewed. This due diligence is costly, requires high numbers of skilled individuals, and is vulnerable to human error. Cloud-based AI/machine-learning solutions can automatically identify and extract potentially harmful content, such as risky clauses related to penalties or value owed. This reduces the time and manpower required for review, and it helps in avoiding conflicts of interest. In typical cases, cost reduction of up to 0.1 percent was generated for overall procurement volumes.

Area 6: Enabling integrative digital health solutions. Cloud-based solutions can support physicians along patient journeys in areas ranging from data-driven diagnosis (AI-driven analysis of CT scans and early detection of disease patterns and high-risk patients, for example), to prescriptions (predictive treatment informed by machine-learning-based analysis of outcomes).

Use case example: Health-related information on patients is typically fragmented over various nonstandardized databases, both within and across different healthcare providers (physicians, hospital clinics, and pharmacists, for example). This disconnected approach to recording data jeopardizes treatment quality by allowing diagnoses that differ from one another and findings that are not shared. It also generates unnecessary costs, as the patient is required to register separately with each provider, and providers must also register each patient separately. A cloud-based approach enables integrative identity management with a single patient file and identifier across multiple healthcare providers. Processes such as diagnosis can be streamlined, and cross-organizational collaboration can be facilitated between physicians and specialists, for example.

Public-sector investment in cloud technology is predicted to double by 2024 in both Europe and the United States. When contemplating cloud transformation, governments and agencies should take into consideration both improvements in the IT infrastructure as well as benefits of a business transformation. This will ensure that cloud-related spending delivers the strongest possible value for taxpayers. National governments should also consider the nature of their relationships with major providers of cloud services, such as Amazon, Google, and Microsoft—particularly where issues of security and data sovereignty are concerned. We will explore these and other challenges around the adoption of cloud technology in the public sector in future articles.

Related Articles