For many organisations, extracting data from legacy systems remains one of the biggest barriers to digital transformation. Legacy platforms—often decades old—hold valuable operational data, but accessing that information can be slow, costly, and error-prone. Traditional extraction methods rely on manual coding, reverse engineering, or complex data integration projects. These are effective but time-consuming and expensive. Today, artificial intelligence (AI) and generati

Extracting data from legacy systems remains one of the most critical — and often most challenging — stages in modernising an organisation’s technology infrastructure. Many organisations continue to rely on older systems built years, or even decades, ago. While these systems are often stable and deeply integrated into business processes, they can make it difficult to access or reuse the valuable data they hold. As organisations transition to cloud computing, modern database

In today’s fast-moving world, organisations must adapt or risk falling behind. But change—even when necessary—can be messy, disruptive and resisted. That’s where change management frameworks come in. These structured approaches act as a roadmap, guiding leaders and teams through the stages of change: from recognising the need, to implementing solutions, to embedding new practices. In this article, we explore what makes a change management framework “best” for your context,