Boost productivity and efficiency: A strategic guide to legacy software modernisation

This guide explores the essential steps and advantages of legacy software modernisation, including why outsourcing this process is a smart move.

In this guide, we will cover:

• The importance of software in modern business role and for improving productivity and operational efficiency
• What constitutes legacy software and the modernisation process
• Key signs that indicate it's time to upgrade your legacy systems
• Examples of legacy systems
• How AI is impacting on software modernisation
• The advantages of outsourcing legacy software modernisation to specialised teams
• Questions answered by our technical director

What is legacy software and legacy software modernisation?

What is legacy software?

Legacy software refers to outdated or no longer supported systems that have become difficult to maintain and integrate with new technologies. Common legacy systems include those written in languages like PHP and COBOL, or those built on old platforms like Windows XP or Lotus Notes. While these systems may still function, they can significantly hinder performance, security, and scalability.

What is legacy software modernisation?

Modernising legacy software means upgrading, refactoring, or re-platforming these systems to meet current business requirements. This process can involve updating programming languages, migrating to the cloud, or redesigning the software architecture. The goal is to improve performance, security, and scalability while lowering long-term maintenance costs.

When to choose modernisation vs. transformation?

When updating software functionality and deliverables, businesses face two key approaches: modernisation of legacy software and transformation to move the business to entirely new systems and processes. Both strategies for updating systems offer pros and cons, but differ in scope, process, and impact - it is important to consider if legacy systems modernisation is right or if a fuller systems transformation is required:

Choose modernisation:

If the legacy system still meets your core business needs but requires performance, security, or integration improvements. It's a good choice for businesses looking to extend the life of their system without large-scale disruption or cost.

Choose transformation:

If your business goals have outgrown the capabilities of your current system, or if you want to fully leverage new technologies and future-proof your operations. Transformation is ideal for businesses looking for long-term innovation and scalability.

Each approach has its place, depending on your business objectives, budget, and the existing state of your systems. For many, starting with a gradual modernisation and moving to full transformation when needed can strike the right balance between cost and innovation.

When to modernise software: 6 signs you need legacy software modernisation

1. Increased maintenance costs:

   The rising cost of maintaining older systems is a clear sign that modernisation is needed. Legacy software typically requires more specialised knowledge, which is both expensive and hard to come by.

2. Poor integration capabilities:

   In today's digital landscape, software must be able to integrate seamlessly with other systems. Legacy software often struggles to do this, creating operational bottlenecks.

3. Performance and scalability issues:

   If your software can't handle the growing demands of your business, such as increased data loads or a higher number of users, it's time for an upgrade.

4. Security vulnerabilities:

   With cyber threats increasing, older systems often lack the necessary defences, putting your business data at significant risk.

5. User complaints:

   When employees or customers report dissatisfaction with a system's usability, it's likely that the software is hindering their productivity.

6. Vendor support is discontinued:

   Once vendor support ends, businesses are left vulnerable and must either build expensive custom solutions or modernise the software to keep operations running smoothly.

AI plays an increasingly valuable role in legacy system modernisation by improving the efficiency, accuracy, and speed of the modernisation process. Here are key areas where AI can assist:

How is AI is impacting legacy software modernisation?

AI is now playing a critical role in making legacy software modernisation more efficient, less risky, and faster. By automating many of the time-consuming and error-prone aspects of modernisation, AI helps businesses unlock the full potential of their legacy systems while minimising disruption and cost. As AI applications and possibilities evolve, its role in legacy system modernisation will now replace developers but it will grow and offering more advanced support. Some of the applications we are currently seeing include:

What is The Role of AI in deciding legacy systems modernisation strategies?

AI can assist in determining the best approach to modernising a legacy system. By using machine learning to analyse a system's architecture, performance, and security, AI tools can help provide data that leads to recommendations on whether to refactor, replatform, or rebuild the system. AI helps businesses to access data and make data-driven decisions.

Automated code analysis and refactoring

AI can help in analysing legacy codebases, which are often large, complex, and poorly documented. Machine learning algorithms can be used to automatically detect inefficient or redundant code, making suggestions for optimisation quicker for developers. AI tools can be configured to refactor this code, updating it for modern architectures without altering the system's core functionality. This saves significant time and reduces the risk of human error.

For example, AI can be tasked with identifying which parts of the system can be modularised, making it easier to migrate to a microservices architecture — a common modernisation strategy.

Data migration and integration

AI-powered tools can be helpful in facilitating the often challenging task of migrating data from legacy systems to modern platforms. AI can be modelled to automate the process of mapping and transferring data while ensuring compatibility and preventing data loss. These AI tools can also be set to detect inconsistencies or gaps in the data, making the migration smoother.

Machine Learning is also used to support data integration by helping legacy systems connect with modern cloud-based solutions, improving the seamless data flow between old and new platforms.

Predictive maintenance and performance monitoring

AI can also be useful where there is a need to monitor the performance of legacy systems in real-time, an AI model that uses predictive analytics can be developed to identify potential issues before they become critical. By analysing historical system data, Predictive AI can foresee potential system failures or performance bottlenecks, allowing IT teams and developers to address problems proactively, reducing downtime and increasing system reliability.

For example, a predictive AI tool could flag security vulnerabilities in a legacy system that may not have been patched due to outdated protocols, enabling teams to prioritise necessary updates.

AI-driven testing and quality assurance

AI tools can be developed and deployed to automate testing, for testing during the modernisation process, automating and accelerating the testing phases. Machine learning algorithms can create test cases, run simulations, and identify bugs or performance issues more efficiently than traditional methods. This ensures that the modernised system functions optimally and securely, reducing the time spent in manual testing.

AI for Legacy code documentation

Many legacy systems suffer from poor or non-existent documentation, which complicates the modernisation process. Predictive AI processes can be used to analyse existing codebases and generate documentation for developers to review. This documentation can help software developers better understand the system, making it easier to modernise or upgrade.

Why outsource legacy software modernisation?

Access to specialised expertise

Outsourcing allows businesses to access teams with deep experience in legacy system upgrades. Experts familiar with platforms like PHP or COBOL can ensure a smooth transition while mitigating risks.

Faster time-to-market

External teams have the resources and skills needed to complete modernisation projects more efficiently, reducing delays and keeping your business agile.

Cost-effectiveness

Hiring a specialised outsourcing partner can be more cost-effective than training or hiring in-house staff for a temporary project. Outsourcing offers flexible pricing models, which can significantly reduce overhead costs.

Reduced risk

By partnering with experienced outsourcing teams, businesses can mitigate risks related to data migration, system downtime, and cybersecurity.

Focus on core competencies

Outsourcing allows your internal teams to focus on strategic business initiatives rather than being bogged down by complex technical tasks.

Scalability and flexibility

Outsourcing partners can scale their services to meet the demands of the project, ensuring that modernisation doesn't interfere with your day-to-day operations.