From data silos to actionable insights: Innovating within legacy constraints for the digital enterprise
MARKET VIEW REPORT
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Setting the Foundation:
Data Governance and Quality
The path to extracting value from organisational data begins not with technology, but with establishing robust governance frameworks and clear data standards. Our research reveals that successful organisations focus first on building strong foundations before attempting more complex data initiatives.
The Governance Imperative
Nikos Balanis from CFC emphasises this fundamental truth: "Building a data platform without an established governance framework is particularly challenging – it's like trying to play by rules that haven't been fully written yet." This insight reflects a common theme across our interviews - the need to establish clear governance structures before pursuing broader data initiatives.
James Maunder of Unite Students shares their approach: "We've put a fair bit of effort into defining both our business data model and the definitions of our master data elements. Simple principles like having very active data stewards or data custodians - we prefer not to talk about data ownership, because data ownership confers a degree of 'it's my data, not your data'."
The value of spatial context emerges clearly in asset management scenarios. Asif Aziz of Cadent Gas explains: "When we can visualise data points geospatially, we identify patterns that wouldn't be apparent in a list format. The ability to layer different data sets, such as ground conditions with asset data, has enabled us to draw powerful connections and identify high-risk areas more effectively."
When we can visualise data points geospatially, we identify patterns that wouldn't be apparent in a list format. The ability to layer different data sets, such as ground conditions with asset data, has enabled us to draw powerful connections and identify high-risk areas more effectively.
Asif Aziz
Head of Asset Investment and Data at Cadent
Quality Through Standards
At Cadent Gas, Asif Aziz describes their systematic approach: "Our central asset data team is conducting an analysis of our asset data by class to evaluate quality and completeness. They've implemented data quality scorecards that help us understand where to prioritise our improvement efforts."
The importance of standardisation emerges repeatedly in our research. Stephen Warner from Arriva explains: "The rail industry works off some very basic standard principles of reference data. We've got a standard reference data for the name of a station, and the ID of a station head codes, trains, etc. Building up that framework of reference data to start with allows you that when you're bringing in a new data set, you can find a hook."
This focus on steady progress rather than dramatic change characterises successful approaches to data governance. These organisations recognise that establishing strong foundations through clear governance, consistent standards, and engaged stakeholders creates the platform for more sophisticated data initiatives.
The rail industry works off some very basic standard principles of reference data. We've got a standard reference data for the name of a station, and the ID of a station head codes, trains, etc. Building up that framework of reference data to start with allows you that when you're bringing in a new data set, you can find a hook.
Stephen Warner
Head of Business Intelligence at Arriva Group's UK Trains Division
Measuring Progress
The importance of tracking outcomes emerges as another crucial element. As Nikos Balanis from CFC notes: "We track the benefits of every new implementation. For each piece of work, we document the expected outcomes and benefits. It's become an integral part of our process."
This systematic approach to measuring and documenting progress helps organisations maintain momentum while demonstrating value to stakeholders. It creates a virtuous cycle where successful outcomes build support for further investment in data quality and governance initiatives.
We track the benefits of every new implementation. For each piece of work, we document the expected outcomes and benefits. It's become an integral part of our process.
Nikos Balanis
Head of Data Platform at CFC
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