Globelynx: Cutting delivery lead times by 60% with agile and operational insight
The challenge
Globelynx had long delivery timelines, inconsistent coordination, and little operational insight. Teams could not prioritise effectively, and decisions across Operations, Partnerships, and Client Management lacked actionable data.
What we did
We introduced iterative planning, stand-ups, and retrospectives across 16 client deliveries and one internal change project, coordinated timelines and dependencies, renegotiated supplier engagements to cut cost and improve performance, and continuously collated operational data into trends leadership could act on.
// run against The Tenhaw Way, published in full and free to adopt without engaging us
The outcome
Within six months delivery lead times fell by 60%, client satisfaction rose, supplier relationships strengthened, and data-driven insight let teams make sharper strategic decisions, positioning Globelynx for scalable growth.
Limits, and what is withheld
What transfers is the habit of baselining a process before claiming an improvement to it, and of counting the running cost of a change rather than only the cost of building it. What does not transfer is anything agentic. This was agile delivery, supplier negotiation and operational reporting, with no AI in it at all.
Why a buyer usually lands on this one
Written for the person arriving mid-programme with a question.
You cannot claim an improvement you never baselined
The 60% on this page is quotable because there was a measured before. Iterative planning, stand-ups and retrospectives across 16 client deliveries produced comparable data, and the reduction was measured against it.
This is the most common gap in the AI business cases we are shown. A firm proposes to automate a process it has never timed, then proposes to report the saving. Our audit exists partly to close that, because the cheapest week of an agentic programme is the one spent measuring the process you are about to change.
Cost is never only the model
The £100k of supplier savings here came from renegotiating engagements rather than from anything technical. It is on this page because AI programmes routinely present a build cost and omit the running one: inference, the vendor contracts around it, the reviewers you now need, and the tooling nobody cancelled.
An AI delivery partner that has never had to defend a supplier line in a profit and loss account will not spot that, and it is usually where the business case quietly fails in year two.
What this engagement does not claim
The same caveats the case studies hub carries, narrowed to this engagement so nothing here is a surprise to your analyst.
- 01
Not an AI engagement.
Agile delivery, supplier negotiation and operational reporting. No models, no agents.
- 02
The 60% is our measurement of our own work.
It was measured with the client from their delivery data over six months, and it has not been independently audited.
Other engagements
Sector first, because that is the next question. All twelve are on the hub, grouped into the two we would call AI work and the ten we would not.
Landing the Discovery+ launch on a CEO-set deadline
6, development teams on the launch, one of them the visual rebrand team James ran
Making a pandemic-era app team predictable, and trusted again
2, squads: Mobile App and Integration
Turning three merged teams into one delivery unit through workflow design
3, merged teams aligned
See how we did it
A real engagement walked through by the person who led it, then the same method applied to yours.
- The ways of working, published in full and free to adopt without hiring us.
- The target operating model James co-led at HSBC: designed and piloted for 500 teams, with global rollout due in 2026 and not yet rolled out.
- The AI build inside a live London specialty insurer: a working proof of concept, month by month, with the client anonymised to a market.
Everything the call covers about our work is already published on this site. What it adds is the person who did that work, and your own situation put through the same method.
The 30-minute discovery call starts with your problem. This one starts with our work.
Pick a time on cal.comWant the same thing, in your organisation?
A 30-minute call with James Rooney. We will tell you which parts of this we have done before and which we would be doing for the first time, and you will leave with a rough scope either way.
most start with a fixed-price AI Readiness Audit · £30k–£90k · 6–8 weeks
Calendar not loading? Open it on cal.com or email hello@tenhaw.com.