Analytics adoption up 78%.
NPS climbs to 9.71.
A Board-backed data strategy moved 85% of company data onto Azure Data Lake, put Power BI and Tableau in front of every team, and added a machine learning model for sales forecasting — turning scattered data into a single source of truth.
increase
year one
per month
improvement
Client
A global education provider.
Goal
The provider set out to run its first organisation-wide data transformation, embedding a data-driven culture across global teams and building predictive, prescriptive, and machine-learning capability.
The data existed. Nobody could use it consistently.
Company data sat scattered across disconnected systems, with no central source of truth and no consistent way for teams to access or trust it. Reporting was ad hoc and analytics adoption varied wildly across global teams, with no governance in place to keep data quality in check as the organisation grew.
There was no existing mandate for this kind of transformation either. It had to be built from scratch and taken to the Board for approval, all while the organisation was under pressure to keep improving financial performance in the near term.
Three constraints were non-negotiable:
- Data scattered across disconnected systems, no single source of truth
- No existing culture of analytics adoption across global teams
- Transformation had to earn its mandate against near-term financial pressure
One strategy, built from scratch and backed by the Board.
The programme started with the strategy itself: the organisation’s first enterprise-wide data strategy, taken to the Board for approval and paired with training programmes to build adoption from day one. That gave the transformation a mandate, not just a technical rollout.
A data strategy is not a migration. This one changed how the organisation makes decisions, not just where it stores data.
85% of company data moved onto Azure Data Lake, replacing the patchwork of disconnected sources with a single, scalable, secure home for it. Power BI and Tableau went in on top, giving teams self-service reporting and analytics instead of requests routed through a central team.
On top of that, a machine learning model was built to handle sales forecasting and financial planning, moving the organisation from reactive reporting towards predictive and prescriptive analytics.
One strategy, four numbers that matter.
A year in, the organisation has a single data strategy, a central data platform, and teams who actually use it: adoption up 78%, NPS at 9.71, and cloud costs down £3K a month. The Data Governance programme lifted data quality by 35% along the way, embedding the data literacy the transformation was built to create.
* Case studies reflect work undertaken by our Heads of AI either during their tenure with Head of AI or in prior roles before they were part of the Head of AI network; they are provided for illustrative purposes only and are based on conversations with our Heads of AI.
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*Case studies reflect work undertaken by our Heads of AI either during their tenure with Head of AI or in prior roles before they were part of the Head of AI network; they are provided for illustrative purposes only and are based on conversations with our Heads of AI.