New research indicates that digital transformation could boost the UK economy by up to £413bn by 2030. But it is important to remember that digital transformation is not just a digitisation project. It is an on-going process that uses technology to improve the flow of data throughout an organisation. It creates an interconnected ecosystem in which accurate, readily-available data is used to inform decision-making at every level. Its ultimate aim is to boost revenue, productivity and profitability.
This flow of data makes data integration is one of the most important elements of digital transformation. Data needs to flow freely and accurately throughout the organisation and be fully available, in a centralised place, for analysis. Integration is the tool that ensures this, by connecting data from different systems and interfaces, reducing the issues caused by data silos and legacy applications.
A successful approach to data integration during a transformation
Data integration should therefore be treated as an integral part of a digital transformation plan. Data integration in digital transformation doesn’t just entail the combining of disparate systems. By planning the integration at the start of the project, it is possible to create a complete, connected platform on which to build the organisation’s new processes and systems.
How to make the data integration component successful:
- Define the integration’s objectives clearly. These can be for the implementation itself, such as project deadlines, and for the on-going integration, such as measures of the amount of data moved daily, ‘up’ time and the proportion of errors.
- Reduce potential risks by listing all possible issues, both during the project’s implementation and afterwards, alongside plans to mitigate them. Risks can include data access issues, data feed failure or poor quality data from third parties.
- Consider how the transfer of data from one system to another might potentially affect its security.
- Review all of the systems involved with the data, from extraction to every system that uses the final, consolidated output.
- Design the data integration framework thoroughly, which should include mapping the data, understanding its sources and defining the organisation’s requirements for it.
- Fully scope the data and determine the data quality rules required by the organisation.
- Create a thorough testing plan, including unit tests, integration tests and system tests.
- Ensure complete compliance with local data protection regulations.
For more detail, download our free data integration planning guide.
How data integration can benefit a digital transformation project
Performance monitoring: Data on the performance of the organisation – and of the transformation project itself – can help improve decision-making. Project managers can monitor the progress of the digital transformation, such as user uptake of new technology. Decision-makers across the organisation can then use the integrated data to analyse financial performance, customer behaviour and new opportunities.
Customer experience: An improved customer experience stems from the integration of data from multiple touchpoints during the customer journey. This data provides the organisation with a more complete view of the customer, their needs and any barriers they encounter.
Data analytics: The organisation’s data will be of better quality and more accessible after an integration, leading to improved decision-making. Comprehensive datasets will be available for use in analytics tools, including applications such as data visualisation and data storytelling.
Digital agility: The organisation will become more agile once data integration has decoupled its data from organisational silos and legacy systems. Instead, new tools can be added to the organisation’s ecosystem as required.
The data-centric transformation of the future
A real data-centric transformation would have the potential to create a new dimension of data which is not directly connected to a particular application, and therefore to the application’s database. Emerging thinking is calling this the dataware concept.
This thinking eliminates the need for application databases – and therefore data integration – by creating a data backend that feeds the applications implemented during the transformation.
A shared data backend would require all the organisation’s apps to read and write to it in real time. It also requires real-time collaboration by multiple people and multiple applications. It therefore remains an emerging technology, but has the scope in future to render data integration during a transformation obsolete.
Check out this article by Dataversity for more information on dataware.