Bemobile

Project summary: Grid modernisation funding required us to demonstrate demand-response capability. The machine learning models existed on paper; we needed an engineering partner to build and productionise them.

We had worked with three agencies before this engagement. The comparison is not flattering to the others. What distinguished this team was a systematic approach to understanding the problem before proposing a solution — something that sounds obvious and is practiced far less often than it should be. The delivery phase ran to schedule, the codebase is clean enough that our internal engineers made positive comments during handover review, and we have not logged a critical incident in five months of live operation. We intend to use them for our next phase of work.

Project summary: Our agents were spending more time managing data across disconnected systems than managing relationships. We needed a unified platform to give them that time back.

The project brief was ambitious and we had received proposals ranging from two to five times our eventual budget from other vendors. This team came back with a proposal that was commercially realistic and technically credible — and then delivered against it. That alignment between proposal and outcome is not something I take for granted. I have been on the other side of it enough times to know it requires both honesty in the sales process and discipline in delivery. We experienced both.

Project summary: Dynamic pricing had been a manual process for years. We knew the revenue management opportunity was significant but lacked the technical capability to build the models and connect them to our booking engine.

I came into this engagement as a sceptic. We had been through a failed implementation with a previous vendor and I had high standards for what evidence of competence looked like before I would trust a partner with our core systems. This team earned that trust progressively — through the quality of the discovery documentation, the rigour of the technical proposals, the consistency of the sprint deliveries, and ultimately the stability of the production system. I no longer lead with scepticism when recommending them.

Project summary: A previous engagement had delivered something that worked in staging and struggled in production. We approached this project with greater rigour in vendor selection as a result.

Our stakeholder group included board members, clinical leads, compliance officers, and end users — each with different technical literacy and different success criteria. This team navigated that stakeholder landscape as well as any vendor I have seen. They adjusted their communication register depending on the audience without losing the substance. They managed expectations honestly throughout. And they delivered a system that each group can point to as meeting their requirements. That breadth is genuinely uncommon.

Project summary: Our engineering capacity was committed to maintaining existing systems and could not absorb a net-new build of this complexity. An external partner with the right skills was the only viable option.

What made the most difference in practice was the quality of the engineering judgment on this team. Not the ability to execute a specification — that is a baseline expectation. The ability to recognise when a specification was suboptimal, explain why, propose an alternative, and support the client in making a decision about it. That consultative dimension elevated the output beyond what the brief described and resulted in a product that is more fit for purpose than the one we had originally specified.

Project summary: Cross-agency data sharing had been blocked by incompatible systems for four years. A secure integration platform was the prerequisite for every transformation initiative in our roadmap.

What made the most difference in practice was the quality of the engineering judgment on this team. Not the ability to execute a specification — that is a baseline expectation. The ability to recognise when a specification was suboptimal, explain why, propose an alternative, and support the client in making a decision about it. That consultative dimension elevated the output beyond what the brief described and resulted in a product that is more fit for purpose than the one we had originally specified.

Project summary: A merger had left us with two incompatible student information systems. We needed a consolidation path that preserved historical data, maintained service continuity, and met accreditation requirements.

What made the most difference in practice was the quality of the engineering judgment on this team. Not the ability to execute a specification — that is a baseline expectation. The ability to recognise when a specification was suboptimal, explain why, propose an alternative, and support the client in making a decision about it. That consultative dimension elevated the output beyond what the brief described and resulted in a product that is more fit for purpose than the one we had originally specified.

Project summary: Our audience data was fragmented across eight tools with no single identity layer. Personalisation had become impossible without first solving the data foundation.

I came into this engagement as a sceptic. We had been through a failed implementation with a previous vendor and I had high standards for what evidence of competence looked like before I would trust a partner with our core systems. This team earned that trust progressively — through the quality of the discovery documentation, the rigour of the technical proposals, the consistency of the sprint deliveries, and ultimately the stability of the production system. I no longer lead with scepticism when recommending them.