In it’s report, The Data Revolution, Nesta observes that UK data-driven firms are 10% more productive than those who aren’t.
Implementing a data strategy can bolster and unify transparency, reporting and data management standards across an organisation. The ability to easily share data to common standards vastly improves the digital experience for all employees of an organisation, as well as its customers and will support seamless cross-departmental communication and collaboration.
Now, more than ever, organisations need to ensure employees, customers and other stakeholders have up-to-date information that they trust in order to make good, timely decisions.
In the absence of a data strategy, each team and department within an organisation might be developing its data systems in isolation. They risk building internal networks and data-sharing protocols — but without the means to ensure that they’ll support inter-departmental exchange. The longer this divergent progress continues, the greater the challenge of aligning data operations when the organisation does start carving out a data strategy. Every day that is delayed, the task of implementing a data strategy grows a little greater.
Build a data strategy focused on business value
The key elements of a data strategy
The starting point is an organisation’s business strategy: data leaders should pick out their overarching goals, and identify the datasets and capabilities required to realise them.
Not all data is created equal and you cannot do everything: therefore, organisations must concentrate on the datasets most essential to strengthening services, improving connections and building processing capabilities. This latter piece is key to success; by bringing together existing datasets and building links to other offices’ or departments’ resources, many organisations would have a clearer picture of how their operations work in practice — and thus how to improve them.
Next, develop your approach to five key topics:
• Data architecture: How and where data is held, and the standards governing language, definitions and formats. These standards ensure that datasets are compatible and can easily be combined for analysis or use in service delivery.
• Data integration: This covers the standards and protocols required to transfer information between different systems and organisations easily and securely.
• Data quality: The standards used to evaluate a dataset across dimensions including accuracy, validity and timeliness, and to record how it’s been gathered, handled and processed.
• Master data management: Governs the organisation’s approach to developing a ‘golden record’ for critical data points, such as employee name or location. By eliminating duplicates, capturing the best available information and sharing it across the system, this process underpins data managers’ ability to combine datasets and build services around users’ needs.
• Data governance: Concerns the allocation of responsibilities and accountabilities.
These are the core elements of an effective strategy, but they are not sufficient on their own.
A strategy can present great ideas on all these fronts, while collapsing at the implementation stage: successful delivery depends on excellent stakeholder engagement throughout the development process — the leaders and teams who will implement the strategy must play a key role in designing it. The strategy must also be able to adapt to local needs and have the potential to help staff across the organisation realise their own goals.
The three considerations of data: standardise data, data strategy and data culture
The key principles in developing a data strategy
Another essential principle is that of flexibility. Most strategies will include a path to introducing central standards, buying frameworks, shared tools and performance metrics — and these have huge value in promoting interoperability and exchange, cutting costs and monitoring progress. But every large organisation has its own priorities, and departments need enough autonomy to apply central processes in ways that support their core mission and recognise their unique delivery environment.
The time is now
Producing and implementing an organisation-wide data strategy is a big task, but the longer it is delayed, the more problems we are storing up for the future.
Without central direction, organisations will remain faltering and divergent and if departments do develop their own systems independently, the task of retro-engineering them to promote compatibility and exchange will grow ever greater.
With organisations of all shapes and sizes undergoing so much disruption as a result of Covid-19, leaders should leverage data to dramatically boost collaboration and operational efficiency, minimise duplication, strip out routine tasks, all whilst improving employees’ tools and roles.
