At this year’s ECI Unlocked: Digital Growth Summit, our portfolio CEOs shared hard-won lessons about making the right technology investment decisions, and what they learned along the way. The fundamental question remains: when should you build, and when should you buy?
1. The competitive advantage test
Mark Eastham, CEO of Avantia, has a clear framework, and noted it’s important to check your ego at the door. “If we believe that we can create a competitive advantage by building something ourselves in contrast to buying it, then we will seriously go for it. But we are never going to build a better CRM system than Salesforce.”
For Avantia, competitive advantage lies in extracting data from systems to make real-time decisions that competitors can’t. Systems of record? Buy them. Unique decisioning capabilities? Build them.
Moneypenny’s CEO, Jesper With-Fogstrup echoes this principle. “Don’t build if somebody else has built utility. Find the best of breed and connect it together if necessary.” The important lesson he’s learned in making this approach work? Don’t build and then customise to death. Challenge every customisation you make to an off the shelf product by asking what true value it creates.
2. The AI acceleration
AI has become unavoidable. As Jesper noted, “if you’re any business right now and AI is not on your agenda, you’re probably mistaken. I can’t think of any way where you wouldn’t have it.” Not only is it important in your own business, it is becoming key to tenders, with customers explicitly asking about AI features and how they will benefit
This shift is integral to your build vs buy decision making. In many cases, the AI product you need doesn’t need to be built from the ground up, and you can white label tools and integrate them to create something distinctive. However, if you already have an AI forward organisation and data processing is core to your product, then you have a unique opportunity to build something that massively outperforms competitors. This is the case with Avantia’s Cortex – an intelligent decision-making platform for pricing and rating that it built in 2017.
This has been able to be leveraged in their self-built and unique Holmes tool, to help process live claims. In controlled tests, Holmes helped make Avantia’s fraud detection rate x6 more effective.
But, when it comes to AI in their customer service model? That isn’t where their distinctiveness lies, so there it is better to buy a standard solution, and focus your efforts on the real marginal gains.
3. Simplify requirements
Sion Lewis from Ciphr discovered how complexity can often mask the real problem, making companies feel they need to build, when in reality they can simplify their needs into what will move the needle. When he joined, the team was managing systems with hundreds of data points, making it hard to focus on what actually mattered. Sion reflected that they spent too much time focussing on internal finance department requirements rather than on delivering value to their customers.
The breakthrough came from simplification and asking the right questions. Rather than adding more tools or complexity, Ciphr focussed on streamlining their approach. This shift toward customer value over internal convenience became a guiding principle for their technology decisions.
4. The importance of organisational adoption
Implementing technology successfully requires getting your teams on board from the start. Ciphr discovered this when implementing new systems. The question isn’t build vs buy, it’s implementation vs embedding. The key wasn’t just having the right technology, but ensuring teams understood how it would help them do their jobs better.
This connects to Jesper’s principle of thinking “problem first and solution second” rather than getting excited about new tools. When you approach technology decisions this way, every department understands the purpose and aligns on the expected outcomes before you begin building.
Organisational readiness matters as much as technical capability. Before building, ensure teams understand how the solution fits their workflows and why it will make their work more effective. The best-built solution delivers no value if your teams aren’t prepared to adopt it properly.
5. Learning to fail fast
The most successful approach involves chunking large investments into smaller, measurable pieces. Rather than writing big cheques upfront, create use cases that identify which parts should be tackled first and where the most value lies.
Avantia’s team learned to never write a big cheque in a waterfall approach, and instead deliberately break everything into bite-sized pieces. When returns diminish, they slow down, switch direction, or move resources elsewhere.
Post-implementation reviews are crucial, not just asking whether tools delivered expected results but using those learnings to inform future investment decisions.
The conversation revealed there’s no universal answer to build vs buy, but there are universal principles. Focus on competitive advantage, be realistic about organisational capabilities, measure ruthlessly, and remember that technology serves people, not the other way around.
