Yondr: Turning erratic global delivery into something the business could plan around
The challenge
Yondr's global digital teams delivered inconsistently, so the business could not plan beyond a quarter. That unpredictability was most damaging in the UK and USA, where reliable delivery was critical to scaling data centre operations.
What we did
We introduced accurate Story Point estimation, adjusted post-completion to reflect real capacity, and embedded the agile ceremonies that were missing: retrospectives, planning, and active backlog management. The work ran remotely across three regions, reinforced with on-site workshops.
// run against The Tenhaw Way, published in full and free to adopt without engaging us
The outcome
Within three months development teams were producing consistent output every sprint. By six months that predictability had reached support and security teams, and the business could finally plan holistically.
Limits, and what is withheld
What transfers is the baseline. You cannot state an automation improvement in a system whose human throughput nobody can currently state to within a factor of two, and this is the work of getting to that number. Predictability is a precondition for automation rather than evidence of it, which is why this work comes first.
Why a buyer usually lands on this one
Written for the person arriving mid-programme with a question.
Predictability is a precondition, not a nice-to-have
You cannot safely introduce agents into a system whose human delivery you cannot yet measure. The measurement is the baseline every later claim about automation is measured against. Without it, a 30% improvement is an anecdote.
It is also the answer to the request we hear most often, which is from a business that wants to scale AI agents across teams whose current throughput nobody can state to within a factor of two.
Data centres, and the regime that now applies to them
Yondr builds and operates data centres, which the EU names as digital infrastructure under NIS2. An operator in scope carries management-body accountability for risk measures, incident reporting on short clocks, and supply-chain security obligations reaching the vendors inside the facility.
NIS2 post-dates this engagement, and our work covered the UK, US and Singapore operations rather than an EU compliance programme. This is a description of what the regime asks of an operator today, not work we delivered. What is relevant is where it bites: reporting an incident within a 24-hour initial clock is a delivery-capability question before it is a legal one, because it depends on whether support, security and development teams share a cadence and a single view of the work. That is precisely what the six months described here produced.
Your context will differ from this one. Thirty minutes is enough to say by how much.
Talk it throughWhat 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, and not a compliance engagement.
Agile delivery and predictability work across three regions. We did not deliver a NIS2 readiness programme and we claim no NIS2 expertise.
- 02
The regions were not equally weighted.
The work ran remotely across the UK, USA and Singapore, reinforced with on-site workshops. The UK and USA were where unpredictability was most damaging and where most of the effort landed.
If you want to know whether we have done your version of this, ask on the call and we will answer plainly.
Talk it throughOther 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.
Standing up the delivery engine behind a £40bn hydrogen business case
£40bn, business case underpinned
Roughly a year of stalled work, rebuilt as a working proof of concept in two weeks
12 months → 2 weeks, prior build effort rebuilt as a working proof of concept
Landing the Discovery+ launch on a CEO-set deadline
6, development teams on the launch, one of them the visual rebrand team James ran
Or skip the reading and ask which of these is closest to your problem.
Talk it throughSee 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 · £44,000 · 4 weeks · working prototypes
Calendar not loading? Open it on cal.com or email hello@tenhaw.com.
Questions about this engagement
What did Tenhaw do for Yondr?
A six-month engagement to make Yondr's global digital delivery predictable enough to plan around. Teams across the UK, USA and Singapore were delivering erratically. We introduced Story Point estimation recalibrated against real capacity, and we embedded the agile ceremonies that were missing: retrospectives, planning and active backlog management. Within three months the development teams were producing consistent output every sprint, and by six months that predictability had reached the support and security teams too. Yondr could plan beyond a single quarter for the first time.
Why could Yondr not plan beyond a single quarter?
Because its global digital teams delivered inconsistently, and you cannot plan around output you cannot predict. The unpredictability was most damaging in the UK and USA, where reliable delivery was critical to scaling data centre operations. Nobody could say with confidence what a team would finish in a sprint, so any commitment beyond the current quarter was a guess. Fixing that was the whole engagement. Once output became consistent sprint after sprint, the planning horizon extended with it, first for development and then across support and security.
How long does it take to make erratic delivery predictable?
Three months at Yondr to get the development teams producing consistent output every sprint. Six months for that predictability to reach the support and security teams. That is a realistic shape. Estimation only becomes accurate once it has been recalibrated against a few completed sprints, and ceremonies like retrospectives and backlog management compound rather than pay off instantly. Anyone promising a predictable delivery organisation in a fortnight is describing a report, not a change in how the teams actually work.
Can delivery coaching work remotely across time zones?
Yes. The Yondr engagement ran remotely across the UK, USA and Singapore, with on-site workshops where being in the room helped. Three regions made remote-first a necessity. It worked because everything the method relies on is a visible artefact. Estimates get corrected against completed work. Backlogs are managed in the open where anyone can see them, and every ceremony leaves behind an output the whole team can read. Within three months of working that way, the development teams across those regions were producing consistent output every sprint.
Why fix delivery predictability before bringing in AI?
Because you cannot state an automation improvement in a system whose human throughput nobody can currently state to within a factor of two. If a team's output swings unpredictably, any claim that AI made it faster is unmeasurable. The Yondr engagement is what getting to that baseline looks like. Consistent sprint output within three months, and support and security on the same footing by six. The payoff does not wait for the AI either. For the first time the business could plan holistically, where before it had never seen past the current quarter.
Our estimates are always wrong. How do we fix that?
Adjust the estimate after the work is done. That one habit turns estimation from optimism into measurement. Most teams estimate, deliver something different, then never close the loop, so the next estimate inherits the same error. At Yondr we recalibrated Story Points post-completion to reflect the capacity each team had actually demonstrated, and that feedback loop is a large part of why development output became consistent within three months. The aim is not better guessing. It is that the numbers you plan with start to describe the team you actually have.
Can support and security teams become predictable too?
They can. At Yondr predictability started with the development teams, who reached consistent sprint output within three months, and by six months it had reached support and security too. The mechanics do not change with the function. Make the work visible. Correct the estimates against what actually got completed, and hold planning and retrospectives on a regular beat. Extending it beyond engineering mattered because a business plans across all of its functions, and predictable development sitting next to unpredictable support still leaves leadership guessing. Only once all three were predictable could Yondr plan holistically.
Was the Yondr work delivered by Tenhaw itself?
Yondr is one of the engagements delivered under the Tenhaw banner, alongside Anglo American, Greggs, Colart, Tecknuovo and Globelynx. Several engagements from that period predate the company's incorporation and were delivered by James Rooney personally on contract. On a call we will walk you through which is which. We say so plainly because a track record is only evidence if you can check it. The same person led the work either way, and this case study describes what was done and what changed.
Do agile ceremonies actually make delivery more predictable?
They do when they are the missing feedback loops. Ritual on its own changes nothing. Yondr's teams had no retrospectives and no planning, and nobody was actively managing the backlog. Putting those back alongside honest Story Point estimation took the development teams to consistent output every sprint within three months. The ceremony itself is not the point. What each one adds is a place where the plan meets what actually happened and gets corrected. Teams that hold the meetings without making the corrections get the cost of the ceremonies and none of the predictability.
Why does sprint predictability matter to a data centre business?
Reliable digital delivery in the UK and USA was critical to Yondr scaling its data centre operations, and that is where the unpredictability hurt most. When digital output is erratic, the operational side of the business cannot commit to anything that depends on it. Development output became consistent, support and security followed, and Yondr could plan holistically at last. For a business like that, predictable software delivery is an operational dependency, not an engineering nicety.
Do you fix delivery one region at a time or everywhere at once?
Everywhere at once. We staged the order of functions and left geography out of it. At Yondr the work ran across the UK, USA and Singapore in parallel, remotely with on-site workshops where they earned the travel, because the erratic delivery was one problem, not three local ones. Development teams went first and hit consistent output every sprint within three months. Support and security followed and had the same predictability by six. Fixing one region at a time would have left leadership planning around whichever region was furthest behind, and Yondr needed reliable delivery in the UK and USA to scale its data centre operations.
Why not just hire an agile coach instead of a consultancy?
If one team needs its ceremonies run properly, a coach is the cheaper and better answer, and we will tell you so. Yondr's problem was a size larger. The business could not plan beyond a quarter because digital teams in the UK, USA and Singapore delivered inconsistently, and reliable delivery in the UK and USA was critical to scaling data centre operations. The work meant recalibrating estimation against demonstrated capacity, embedding the ceremonies that were absent, then carrying the same discipline into support and security so leadership could plan across functions rather than one team at a time. Development output was consistent every sprint within three months.
Won't teams inflate their Story Points once you measure output?
They will if you use points to rank people. At Yondr the correction ran the other way. Estimates were adjusted after completion to reflect the capacity each team had actually demonstrated, so an optimistic estimate gets corrected by the next sprint's evidence instead of rewarded. Points are a planning unit, not a performance measure. The test of the whole exercise was a business one. Could Yondr commit beyond the current quarter? Within three months the development teams were producing consistent output every sprint, and by six months support and security had the same. Use the number to judge individuals and you lose both the trust and the data.
What happens if our priorities keep changing mid-sprint?
Predictability dies, and no estimation method survives it. Active backlog management was one of the ceremonies missing at Yondr, and putting it back gives reprioritisation somewhere to land. The backlog gets reordered in planning, so a sprint that has been committed can finish and produce a number worth learning from. Without that, every sprint is a different experiment and the average tells you nothing. That discipline is a large part of why Yondr's development teams reached consistent output every sprint within three months, and why the same approach held later for support and security.
How do you tell a real delivery improvement from one good quarter?
By whether it repeats sprint after sprint, and by whether anyone outside engineering can plan on it. At Yondr the development teams held consistent output every sprint from month three. The same result held as the approach reached support and security by month six, and the business started planning holistically instead of a quarter at a time. One strong quarter is noise, usually a team that pushed hard or got lucky with scope. On live engagements we report value monthly for the same reason, and a month that delivers nothing measurable is reported as a failed month.