Problems, and what happened next.

Problem

A private automotive experience with nothing in place: no format, no suppliers under contract, no run of show. Forty guests expecting a manufacturer-level standard, and a fleet, an instructor team and a full programme to assemble around them.

What I did

Took ownership end to end — the concept and the programme, supplier selection and negotiation, fleet and instructor coordination, logistics and accommodation, the run of show, and direction on site for the whole event.

Result

Delivered as promised, with fifteen instructors and the full fleet running to schedule across the programme. The format became repeatable rather than a one-off.

Problem

Quotes were built by hand across spreadsheets and documents. Each one took around an hour, pricing drifted between people, and nothing connected to the CRM — so commercial follow-up depended on someone remembering.

What I did

Redesigned the commercial process first, then built the system around it: a dedicated quoting tool with structured pricing, generated documents, and a direct link to the CRM so every quote sits against its contact.

Result

A quote now takes fifteen to twenty minutes instead of an hour, pricing is consistent whoever builds it, and follow-up is tracked rather than remembered.

Problem

Years of customer data spread across spreadsheets, mailboxes and individual habits. Duplicates everywhere, no shared definition of a customer, and no reliable way to know who had been contacted about what.

What I did

Defined the data model the business actually needed, cleaned and deduplicated the history, migrated it into HubSpot, and set up the properties, pipelines and workflows the team works in day to day.

Result

Ten thousand contacts in one structured system, with commercial history that can be searched, segmented and acted on instead of guessed at.

Problem

The knowledge needed to answer a client properly — products, pricing logic, past deals, what is and isn't possible — lived with two or three experienced people. Everyone else queued behind them.

What I did

Collected and structured that internal knowledge, then built an AI-assisted resource on top of it so anyone on the team could get an accurate answer directly, with the source behind it.

Result

Answers that used to require one specific person are available to the whole team, and the experienced people spend their time on the cases that genuinely need them.

Problem

A fleet operating with no operational data. Engine behaviour, usage and condition were only known through what drivers reported after the fact.

What I did

Built a telemetry system from the vehicle up — an onboard unit reading the CAN bus, sending data to a server, and a dashboard making it readable — then deployed it across the fleet.

Result

From no instrumented vehicles to thirty reporting continuously, with usage and engine data in one place instead of arriving after the fact.