How a high-growth fintech dealt with a major platform rewrite with 10 years of technical and commercial debt. And, more importantly, my own personal growth journey from tech leader to exec-level CTO.
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This is one of those stories about a platform rewrite that did go well. But more importantly, sharing my growth journey as a CTO from moving from a technology leader to an executive leader of the Flagstone business. In case you’re hoping to learn a lot about tackling tech debt, you may be dissapointed (and so was I). The biggest hurdle we’ve overcome was to clear what I’d call “commercial debt.” The commercial decisions that companies make in the early stage hustle phase, that are now holding back the company’s ability to scale. This is the story about rebuilding a fintech with £15 billion in assets, in the midst of its biggest growth phase, and my personal story of how I learned all the things they don’t teach you as a software engineer.
Key takeaways
- People throw everything in the technical debt bucket (and by extension product debt): The biggest risks to scaling up an organisation is “commercial debt”. The decisions you make during the hustle phase, that lead to non-scalable bespoke quirks.
- There comes a point in your growth journey as a tech org that you need to make hard decisions about the future technology. The technoloy that got you to a successful and profitable business over the past 10 years, is not going to get you to the next 10 years. How do you make that decision? How do you convince the board that this investment is worth making?
- I needed to shift my mind set from being a senior technology leader to becoming a member of the executive team, whose primary concern is business strategy and execution where technology happens to be in my portfolio of responsibility. I’ve learned a lot about who your first team is (the exect team, not the tech team), executive stakeholder management and communication. However, how do you balance the exec view, vs you actually needing to know the intricate details of some complex problems?
- Data is always the biggest problem, especially when you have been around a while and have legacy systems. A reflection on when to solve it with code vs solve it with humans.
- How do you create the business case and get buy-in for such complex and expensive projects? I’ve learned that this is very much an agile process, with discovery, iterations, phase delivery, etc. Everything we do in the normal day to day product development, but applied to what appears to be a more waterfall style project.
