Digital products and experiences represent the cornerstones of growth for companies in 2025. They offer the chance to build products that resonate with customers to drive loyalty and growth, transform internal operations, and more.

Yet European startups and other businesses that are keen to get ahead of the innovation curve have been hampered by external forces in 2024. The year was marred by a wave of complex regulations that saw major technology companies delay the launch of AI services and digital products to EU markets.

This is having a major impact on the competitiveness of European companies against global counterparts.

Commissioning independent products and digital experiences can be a costly process, but there are new approaches that European business leaders can adopt to boost the efficiency and speed of software development.

High-velocity software development puts superb new features into the hands of their customers ahead of the competition or releases code updates to fix a bug that’s affecting the usability of the product. Yet most large organizations take months to work through the process.

With an intelligent use of resources and a new approach to software engineering, companies can adopt a new mindset that champions rapid release cycles to regain ground.

The velocity challenge has many layers

On the surface, improving upon the velocity metric should be a straightforward process, solved by helping teams work in a more productive or efficient way. Productivity frameworks like Agile and Kanban have been helping developer teams excel on this front for years.

Yet developers today work within a very different landscape that has emerged alongside new digital innovations that have changed how software architectures are built and the way software products operate. As such, velocity is actually a complicated and challenging metric to improve due to the rise of new megatrends. These include the rise of cloud computing and GenAI, among others.

This means that improving velocity is a challenge with many layers. To deliver a finished product, multiple teams need to collaborate to receive optimal results.

Further, modern software development environments mean that sources of waste such as the example above are occurring at a massive scale, having a significant impact on product release cycles.

Without a data-driven approach that examines the entire product development pipeline, it’s impossible to identify all of the pain points and understand how to fix them.

Instead, the software velocity challenge needs to be solved with what I like to call, “intelligent engineering.”

This isn’t a resource problem

Intelligent engineering understands that velocity won’t be improved with more resources alone. In efforts to release a product more quickly, organizations often look to increase the number of people working on code updates or other tasks. However, this approach often fails to have the desired result, and can even exacerbate the problem further.

For instance, if an underlying bottleneck hasn’t been addressed then having more developers working on code will add to the pressure building at this weak spot.

Further, organizations may find that resources are being drained without achieving the goal of faster product releases.

Another tactic is to save time by leveraging off-the-shelf code bases that cut corners, but this is likely to have a negative impact on product quality and user experience.

With this in mind, organizations should instead adopt an approach that first identifies where problems exist and then apply relevant KPIs and process adaptations that accelerate the pace of delivery while monitoring quality standards.

Intelligent engineering provides a considered, strategic approach

Taking this approach forward into action, leaders need to begin with a data-driven approach.

At present, software management platforms are used to manage the performance of each individual team. However, leaders often lack full visibility that can leverage this information and analyze performance across the entire development pipeline.

This means that we can understand not only how well teams are performing, but also how specific KPIs impact the rate of velocity. For example, the system can pinpoint where handover times between teams are causing delays or where quality control challenges are contributing to the number of bugs in the code.

In turn, it means that managers have a clearer understanding of what actions need to be taken to solve the problem areas identified during the analysis. For instance, if quality control is affecting productivity, then an automation tool can be actioned to help the team keep pace with testing. Or if a team with a higher instance of junior developers may require the help of GenAI to help out with writing code.

It’s important to remember that the complexity that comes with modern software development means there is no single tool or one-size-fits all solution that will be guaranteed to improve on the velocity challenge.

Instead, intelligent engineering allows us to take a considered, strategic approach that constantly finds ways to fine-tune the process with subtle adjustments with high-impact outcomes. In this way, software development teams can access the tools and support they need to excel, in turn supporting the success of the organization.

Digital experiences rule the marketplace in 2025. Every company should aim to excel in the delivery of software products to keep ahead of the competition. Many leaders aren’t aware that the ability to release new features and code updates at a fast pace is both mission-critical and difficult to achieve.

By having a data-driven approach, companies can improve their velocity in the most effective way.