Welcome to Innovating Government: Digital transformation insights, a blog series dedicated to exploring the transformative power of digital technologies in the public sector.

Over the next ten posts, we will explore various aspects of digital transformation, from modernising legacy systems to enhancing citizen engagement and ensuring digital inclusion.

Each post will provide insights, best practices, and real-world examples that can help you to navigate the complexities of digital transformation.

Part 1: Transforming legacy systems for the future

What happens when government services rely on outdated systems in a world that's rapidly advancing? Legacy systems, operating beyond their original design parameters, pose significant challenges to productivity and service delivery. These challenges include:

  • Technical debt: Accumulated inefficiencies and outdated code that make systems harder to maintain and upgrade.
  • Integration complexity: Difficulty in integrating legacy systems with modern applications and services.
  • Siloed data: Data trapped in isolated systems, making it hard to access and use effectively.
  • Migration risks: Potential for data loss, corruption, or breaches during the transition to new systems.
  • Lack of funding: Insufficient financial resources to support comprehensive modernisation efforts.
  • Inertia resisting change: Resistance from users and stakeholders accustomed to existing systems.

Did you know that the UK government spends around £400 billion annually on the day-to-day running costs of public services, this is around 37% of public spending, with a significant portion dedicated to maintaining aging legacy systems?

How can government departments, agencies, and public bodies overcome these obstacles? Through artificial intelligence (AI) and digital transformation strategies they, can safely and reliably transition from legacy systems to modern digital infrastructure and services.

This blog explores how AI can accelerate legacy modernisation in government services. It addresses the challenges and solutions for transitioning from outdated systems to a future-ready digital framework. Designed with adaptability, scalability, and modularity at its core to ensure it evolves seamlessly with emerging technologies and changing requirements, providing long-term value and resilience in an ever-evolving landscape.

The role of AI in legacy modernisation 

AI has emerged as a pivotal technology in accelerating the modernisation of legacy systems. By automating routine tasks, enhancing developer efficiency, and providing intelligent automation, AI can reduce the time and cost involved in transitioning to modern systems.

For instance, integrating Robotic Process Automation (RPA) and AI to automate end-to-end business processes can achieve substantial cost efficiencies and free up developer time. This saved time can then be reinvested into further backlog improvements.

Beyond cost savings, the increased efficiency allows teams to focus on higher-value activities, such as innovation, strategic planning, and enhancing service delivery.

Additionally, AI can be used to automate the discovery and mapping of the legacy estate, understand legacy data, and help derive a modernisation roadmap. AI enables government organisations to do more with their existing resources, driving continuous improvement and fostering a culture of innovation. This not only improves productivity but also enhances the overall quality of public services.

Machine learning (ML) algorithms can analyse vast amounts of data to identify patterns and predict potential system failures before they occur. While this predictive maintenance can be applied to legacy systems as a temporary measure, it serves as a valuable tool to improve performance and reliability before a full modernisation.

For example, ML can analyse logs from legacy on-premise database systems to predict performance degradation, enabling proactive (but likely manual) scaling within the constraints of the on-prem solution.

This approach can save considerable time and resources by addressing issues proactively rather than reactively. Additionally, AI can assist in optimising workflows by identifying bottlenecks and suggesting improvements, ensuring that the transition to modern systems is as smooth and efficient as possible.

Challenges in transitioning from legacy systems

Transitioning from legacy systems to modern digital infrastructure presents several challenges, including:

  • Complexity of legacy systems: Legacy systems are often deeply integrated with various internal and external applications, making the transition complex. These systems may have been in place for decades, often using differing technologies and languages. 

    For example, some old JVM-based applications might be tightly coupled with more modern Web 2.0 technologies, creating a tangled web of dependencies. Untangling this web requires a deep understanding of both the old and new systems, as well as careful planning to ensure that nothing is overlooked. Often the lack of consistent and accurate documentation compounds this complexity, making it even more challenging to understand the full scope of dependencies and integrations. 

    Additionally, the absence of comprehensive, trusted test suites can be a significant barrier. Without reliable tests, there is a constant fear of breaking something, which makes teams hesitant to make necessary changes.

  • Data migration: Migrating substantial amounts of data from legacy systems to new platforms requires meticulous planning, execution, and verification to avoid data loss or corruption. 

    Ensuring data integrity is paramount, and verification processes are essential to confirm that no data has been lost or corrupted during the migration. This involves thorough testing and validation to ensure that the migrated data matches the original data accurately. 

    This process often involves data cleansing, where outdated or irrelevant data is removed, and data transformation, where data is converted into a format compatible with the new system.

  • User adaptation: Ensuring that end-users can efficiently adapt to new systems involves extensive training and support. Users who are accustomed to old systems may resist change, especially if they perceive the new systems as more complex or less intuitive or intended to replace them. 

    This resistance can be mitigated through effective change management strategies, including clear communication, training programs, and ongoing support, are essential to help users transition smoothly.
  • Cost and resource allocation: The transition process can be resource-intensive, requiring significant investment in terms of time, money, and effort. Government organisations often operate under tight budgets, and securing the necessary funding for modernisation projects can be challenging. 

    Additionally, the transition process can divert resources from other critical projects, making it essential to carefully manage and prioritise resources.

Solutions for overcoming transition challenges

To address these challenges, several strategies can be employed:

  • Quantitative analysis of existing systems: Conducting a rapid and quantitative analysis of the current state of legacy systems helps narrow down options for innovation and change. AI plays a crucial role in making this process easier by:
  • Efficiency - Automating data collection and analysis, saving time.
  • Accuracy - Reducing human error in assessing complex legacy environments.
  • Actionable insights - Providing clear, prioritised recommendations for modernisation.
  • Strategic focus - Freeing up resources for addressing more complex and impactful modernisation tasks.

This approach enables the identification of easy and quick wins that free up resources for more complex modernisation tasks. By understanding the strengths and weaknesses of the existing systems, organisations can develop a targeted modernisation strategy that maximises impact while minimising disruption.

  • Enterprise Agile approach: Using Enterprise Agile as the delivery approach ensures transparency and predictable/reliable on-time delivery of transitions. This method involves acting collaboratively and openly with stakeholders to ensure no disruption of services for users. 

    Agile methodologies emphasise iterative development, where projects are broken down into smaller, manageable tasks that can be completed in short cycles. This approach allows for continuous feedback and adjustments, ensuring that the project stays on track and meets the changing needs of all stakeholders.

  • Intelligent automation: Integrating AI and RPA to automate business processes reduces the strain on legacy systems and enhances operational efficiency. For example, developing web applications using platforms like Microsoft PowerApps can streamline operations and significantly improve efficiency. This approach democratises the automation of business processes, allowing non-developers to create and manage applications. 

    While a dedicated development team may not be necessary, establishing a Power Platform Center of Excellence can provide governance, best practices, and support. This ensures that the organisation can effectively leverage the platform's capabilities while maintaining control and consistency. 

    Intelligent automation can also help bridge the gap between legacy and modern systems, allowing them to coexist and interact seamlessly during the transition period.

  • Cloud migration: Migrating services to the cloud provides scalability, resilience, and cost-efficiency. Extensive experience in cloud migrations, such as transitioning complex application estates with many dependencies and integrations, can result in cost savings and improved service delivery. 

    Cloud platforms offer flexible, on-demand resources that can scale up or down as needed, ensuring that Government organisations can handle varying workloads without overprovisioning resources offering cost savings and providing sustainable solutions. 

    Additionally, cloud providers invest billions in security, offering advanced security features and compliance certifications to meet stringent regulatory requirements. These platforms are secure by design and default, providing robust protection against threats. BJSS Landing Zones can further enhance this security by offering a secure, scalable, and compliant foundation for cloud environments, ensuring that government organisations can confidently transition to the cloud while maintaining the highest security standards.

Continuous improvement and user engagement

A continuous improvement and optimisation methodology, can identify and eliminate non-value-adding tasks, optimise operations, and standardise processes across all functions. This methodology ensures that all processes are aligned with strategic goals, optimised for maximum efficiency, and digitised where possible.

Continuous improvement is not a one-time effort but an ongoing process that requires regular monitoring, feedback, and adjustments to ensure that systems remain efficient and effective.

User engagement is also a critical component of successful modernisation. By conducting extensive user research and iterative testing, following user-centred design principles, new systems can be made user-friendly and meet the specific needs of the user base.

Adhering to the standards and guidelines set by the Government Digital Service ensures that the systems are not only user-centric but also compliant with best practices in digital service delivery. This thorough approach to user engagement reduces the learning curve and enhances overall satisfaction.

Engaging users early and often in the development process helps ensure that the final product meets their needs and expectations. This can involve user interviews, surveys, usability testing, and pilot programs to gather feedback and make necessary adjustments.

Real-life examples of successful modernisation

While the challenges of modernising legacy systems can seem daunting, many government organisations have started to successfully navigate this process and have reaped significant benefits. For instance, the UK government has undertaken several high-profile modernisation projects that demonstrate the potential of AI and digital transformation.

One notable example is the modernisation of the NHS e-Referral Service (e-RS). This project involved replacing an aging legacy system with a modern, cloud-based solution that improved efficiency and user satisfaction.

The new system streamlined the referral process, reduced administrative burdens, and provided better visibility into patient care pathways. By leveraging AI and automation, the NHS was able to manage a higher volume of referrals with greater accuracy and speed. After the migration e-RS served 85,000 active users with 400 dynamic weight web pages a second. At peak load, 20,000 patient units can now be accommodated. The service has replaced paper-based referrals, slashing the time to process a referral by 75% and reducing missed appointments by half.

The National Audit Office estimates that these improvements are saving secondary care providers over £50.5m every year.

You can access the BJSS case study here.

Another example is the digitisation of the Driver Examination Service for the Driver and Vehicle Standards Agency (DVSA). This project involved transforming an 85-year-old paper-based system into a modern, digital solution that improved efficiency and user satisfaction.

The new system streamlined the examination process, reduced administrative burdens, and saved the DVSA $500,000 annually. By adopting a cloud-first strategy, BJSS enhanced cost-efficiency and provided the DVSA with a robust, future-ready solution.

You can access the BJSS case study here 

Summary

The modernisation of legacy systems in government services is a complex but essential undertaking to improve productivity and service delivery. AI plays a crucial role in accelerating this transition by automating routine tasks, enhancing efficiency, and providing intelligent automation.

Despite the challenges involved, strategies such as quantitative analysis, agile methodologies, intelligent automation, and cloud migration can significantly ease the transition process.

By reimagining back-office processes and leveraging AI-driven solutions, government organisations can reduce the strain on legacy systems and ensure a smooth transition to modern digital infrastructure. This transformation paves the way for a more efficient and responsive public sector, benefiting both the Government organisations and the citizens they serve.

The journey to modernise legacy systems is not without its hurdles, but with the right strategies and technologies in place, government departments, agencies and public bodies can overcome these challenges and build a future-ready digital infrastructure.

The key is to approach modernisation as a continuous process of improvement, with a focus on user engagement, intelligent automation, and strategic resource allocation. By doing so, government services can not only meet the demands of today but also be prepared for the challenges of tomorrow.

Ready to transform your legacy systems and embrace the future of digital government? Explore BJSS's G-Cloud services here to discover how we can help you navigate the complexities of modernisation with our expert solutions and innovative technologies. Let’s build a future-ready digital infrastructure together!

This blog is part 1 of a 10-part series by Chris Wilson, BJSS’ Government Client Principal. Look out for part 2 “Building Digital Skills in Government”

Topics in this series:

  1. Transforming legacy systems for the future
    How AI accelerates legcy modernisation in public services.
  2. Building digital skills in Government
    Upskilling civil servants in digital, data, and technology (DDaT) skills.
  3. Citizen-centric digital services
    Enhancing citizen engagement through user-centred design and accessibility audits.
  4. The role of cloud in Government transformation
    Benefits and challenges of migrating government services to the cloud.
  5. Sustainable IT solutions for Government
    Implementing green software development and carbon tracking tools to meet sustainability goals.
  6. Cyber security in the public sector
    The importance of robust cyber security measures in protecting government data and services.
  7. Maximising ROI in government IT projects
    Demonstrating return on investment for obtaining funding approvals.
  8. Harnessing data for public good
    Leveraging big data and analytics to improve public services and policymaking.
  9. Digital inclusion: Bridging the gap
    Ensuring equitable access to digital services for all citizens.
  10. Public-private partnerships for digital innovation
    Collaborating with private sector partners to drive digital transformation in government.

    Join us on this journey as we uncover the strategies and technologies that are shaping the future of government services.

About the author

Chris Wilson is a seasoned professional with over 25 years of experience in IT and digital transformation. Currently serving as the Government Client Principal at BJSS, Chris excels in helping public sector technology leaders to solve complex problems and build innovative digital products.

He is dedicated to delivering user-centric, data-driven solutions that break free from legacy technology constraints. Chris is known for his ability to cultivate strategic relationships, drive digital innovation, and achieve significant improvements in efficiency and effectiveness for his clients.

With a strong background in client relationship management and digital transformation strategies, Chris is a trusted partner for senior stakeholders in the public sector.

Follow Chris on LinkedIn.