NEEDS ADVISORY
One dashboard hire can't cover what a modern data platform actually needs
US-based logistics business • multibillion-dollar turnover • ongoing engagement
Problem
Recruiting and keeping the full mix of skills a data platform needs
Trigger
Losing a key staff member exposed a critical knowledge gap
Outcome
A trusted operating partner, with flexible project-based resource
Delivery
Initial build, then ongoing embedded operation
Their world
The client is a large, US-based logistics business with multibillion-dollar turnover, and had struggled for some time to keep a stable data platform service running. The trigger was the loss of a key member of staff — exposing how much of the system's operation depended on one person's knowledge, and how little of it was documented or shared.
Recruitment was hard to get right: the people conducting interviews weren't specialists themselves, and couldn't properly assess whether a candidate was suitable. Certifications helped, but weren't enough on their own — the role needed not just knowledge of a particular piece of software, but the judgement to apply it properly, and an understanding of the business context it had to work within. In practice, the team ended up staffed mostly with dashboard developers, and the platform grew to match — a set of point-to-point solutions built entirely inside dashboard tools — which pushed up the cost of maintaining it and lengthened how long it took to fix problems when they surfaced.
Staff who were hired and trained tended to leave quickly for better offers elsewhere, citing stress and a lack of career options within the business. Outsourcing to a large provider felt risky too: the business worried it would be too small a client to be a priority, and would lose control over the service it received.
The business was coming to realise that running a modern data platform properly needs a genuinely broad mix of skills — operational management, engineering, dashboard development, data pipelines, testing, cloud platforms, security, business analysis and solution architecture, and increasingly AI and data science — alongside people who understand the business well enough to work with end users without being either too technical or too detached. It also needs cover for leave and sickness, and availability in the small hours when overnight data loads fail. No single hire, or even a small in-house team, was ever going to cover all of that consistently.
Underneath all of it sat a harder question: whether the business could actually get a modern data platform off the ground at all, or whether it was destined to stay stuck in first gear — never quite able to build what it genuinely needed.
What we did
1
Designed a proper, layered approach to the data
We began by helping the business build out a new use case: designing a better way of bringing data through the platform, rather than building it point to point inside the dashboard tool. That meant separating raw data, cleaned data and data ready for use into distinct stages — the beginnings of a proper layered approach — and moving off an ageing database technology onto a more modern, cloud-native platform we evaluated and helped them adopt.
2
Helped clarify what the business actually needed
Building the new platform alongside them helped clarify management's thinking on what the business actually needed going forward, moving the conversation on from uncertainty to a concrete direction.
3
Took on running the system as a trusted operating partner
At the end of that initial piece of work, we were asked to help operate the system we'd just built, working alongside the client's own in-house team. Over time, as we became more embedded in running it day to day, we took on more responsibility as a trusted operating partner.
4
Stayed embedded, scaling support as the platform grew
That ongoing closeness kept us in touch with the organisation and its data, and meant we could add extra resource on a project-by-project basis whenever the business needed to extend the platform's functionality or scope.
What we did
We began by helping the business build out a new use case: designing a better way of bringing data through the platform, rather than building it point to point inside the dashboard tool. That meant separating raw data, cleaned data and data ready for use into distinct stages — the beginnings of a proper layered approach — and moving off an ageing database technology onto a more modern, cloud-native platform we evaluated and helped them adopt.
Building the new platform alongside them helped clarify management's thinking on what the business actually needed going forward, moving the conversation on from uncertainty to a concrete direction.
At the end of that initial piece of work, we were asked to help operate the system we'd just built, working alongside the client's own in-house team. Over time, as we became more embedded in running it day to day, we took on more responsibility as a trusted operating partner.
That ongoing closeness kept us in touch with the organisation and its data, and meant we could add extra resource on a project-by-project basis whenever the business needed to extend the platform's functionality or scope.
The Impact
PLATFORM CONFIDENCE
Doubt the platform was maintainable or operable long-term
Confidence the system is maintainable, operable and reliably run
SERVICE COVERAGE
No cover for extended hours, leave or overnight incidents
Extended-hours support, with bugs resolved and the system kept running
USER ADOPTION
Limited take-up of the platform's own tools
Active signposting drove wider use of the system among end users
SKILLS COVERAGE
No single hire could cover the full skill set the platform needed
Fractional access to the full range of specialist skills, as and when needed
COST & HEADCOUNT
Would have needed a much larger team to cover all skills and hours
Avoided the cost of a larger in-house team and the extra headcount to cover leave and extended hours
"Once we realised how difficult it would be to run this properly ourselves, the decision was easy — they already knew our data and had built much of the system, so we had a trusted provider we could rely on for good support from day one. That's paid off: our own team can now focus on developing the dashboards our business actually needs, trusting that there's good quality data behind the scenes to support it. It's also given us the platform to move forward with AI query engines and a more modern approach to analytics."
Why this matters
For a business of this scale, a data platform isn't optional — but building and keeping in-house the full range of specialist skills it needs, indefinitely, is a hard way to try. The risk isn't just cost; it's fragility — a platform held together by whichever skills happen to be in the building at the time, with no guarantee they'll still be there next year. This client now has confidence the platform is properly maintainable and operable, service that covers the hours the business actually runs on, and fractional access to the full range of specialist skills — without carrying the cost and headcount of a much larger in-house team.