White Jaguar car with Jaguar logo on bonnet

Jaguar Land Rover |

Automotive

Can diagnostics software move to the web? An independent review for Jaguar Land Rover

JLR wanted to run its diagnostics software through the web rather than on individual machines. Before committing to a major build. They asked Box UK whether that was possible and what it would take.

In short

Jaguar Land Rover’s technicians use Symptom Driven Diagnostics (SDD) software to find vehicle faults. JLR wanted to deliver it through the web, and needed to know whether the existing software could be adapted, and the cost and timescale involved.

  • Workshops showed the software was stable, but years of additions had left a complex architecture.
  • Box UK’s technical consultants reviewed the code line by line.
  • UX consultants evaluated usability and built a prototype of an improved interface.
  • JLR received a roadmap showing how SDD could be scaled across territories.
  • The review gave JLR an independent basis for deciding whether to rearchitect.

Customer background

Jaguar Land Rover builds premium vehicles sold worldwide. Its dealer and service technicians use JLR’s diagnostic software (SDD for older models, Pathfinder for newer ones) to find and fix faults consistently, wherever the vehicle is serviced.

The challenge

JLR wanted to make SDD more accessible by delivering it through the web rather than requiring installation on individual machines. That could be a significant development project, so before starting, JLR needed to know whether the current software could be repurposed, and what it would cost and how long it would take.

Our approach

Workshops with JLR stakeholders showed the software was stable but had grown over time to meet different teams’ needs, leaving a complex underlying architecture.

Our technical consultants reviewed the code line by line to assess its structure and suitability for web delivery. At the same time, our UX consultants ran workshops to evaluate the software’s usability, and built a prototype showing how it could be developed further.

What we delivered

  • A technical assessment of the code and architecture.
  • A usability evaluation and a prototype of an improved interface.
  • A roadmap showing how SDD could be scaled across territories while keeping a consistent, high-quality experience for technicians.

The outcome

JLR gained an independent, evidence-based view of whether to rearchitect SDD for web delivery before committing budget to a major build, plus a validated roadmap if it chose to go ahead. Box UK went on to provide agile coaching to JLR teams.

Frequently asked questions

How do you decide whether to rebuild or adapt existing software?

Review the code and architecture against the new requirement before committing. For JLR, a line-by-line code review showed what adapting SDD for web delivery would involve.

What’s involved in moving desktop software to the web?

Assessing whether the architecture can be separated into a web-deliverable front end and services, what needs rewriting, and how usability will change.

Why combine a code review with a usability review?

Because a technically sound plan that ignores how people use the software can still fail. JLR’s review covered both.

What this means

for your organisation

If you’re thinking about moving installed software to the web, or scaling it to new markets, the first question is whether what you have can get you there. Answering it properly before committing budget can save a lot of money, whichever way the answer goes.

If that’s a decision in front of you, send us a few lines about the software. We’ll tell you what a review would need to cover.

Client

Jaguar Land Rover (JLR)

Sector

Automotive

Talk to one of our digital experts

Tom Houdmont

Chief Technology Officer

Do you have an idea or a project you need support with?

Tom is CTO at Box UK, with 12 years’ experience helping clients deliver ambitious digital products. His background spans Solution Architecture, Front End Development and AI adoption, with particular expertise in high-traffic websites that perform reliably at scale and in embedding AI into delivery practice.

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