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Why data integration is a business and CIO opportunity

With a focus an agile approach and continuous learning and improvement, data integration has proven integral to end-to-end digital transformation

Silos only get taller and stronger over time. A data silo grows and solidifies, preventing the whole organisation from accessing and benefiting from the information. As a result, the organisation lacks a comprehensive information ecosystem, and its decision-making has a flaw in it.

As we rebuild and reposition our organisations for the post-pandemic economy, it is vital that CIOs place data integration high on their busy agendas. 

The decentralisation of business functions and enterprise applications, powered by the adoption of software as a service (SaaS), has increased connectivity, but conversely also enabled more data silos to silently grow.

Yet to get the most from SaaS, organisations need integrated data that draws information from across the organisation, interconnecting with application programming interfaces (API) within the organisation and its partner network.

Without an integrated data strategy, organisations fail to maximise the opportunity of SaaS and pose a risk to the organisation through unidentified weaknesses in data security and privacy. These will lead to a reduction in data quality and, therefore, business confidence in the data. 

Poorly integrated data leads to poor customer service. In the digital economy, the customer expects you to know and have ready insight into every transaction and interaction they have had with the organisation. If a portion of a customer’s experience is locked in a silo, then the customer suffers a poor experience and is likely to churn to another provider. 

As organisations seek to embrace next-generation data-led technologies such as the internet of things (IoT), machine learning (ML), robotic process automation (RPA) and artificial intelligence (AI), the need for data integration increases. CIOs and CTOs in all vertical markets are currently being tasked with large scale digital transformations.

Typically, businesses are looking for an end-to-end transformation that improves productivity, reduces costs and, by cutting friction and touchpoints, improves the customer experience.

None of these can be delivered without an end-to-end data integration to act as the information foundations of these strategies – all of which means the CIO is instrumental in the development, implementation and continuation of data integration. 

Data integration relies on the key strengths of the IT team and the CIO. Enterprise technology is unique in its position as an interface with all areas of the business. Just as with finance, IT and the CIO have a 360-degree view of the customer, as well as the health of the entire business. This has an additional benefit for the senior leadership team and the board, as the CIO can provide a balanced and unbiased view of the entire business.

In my experience, this is a broad viewpoint, just like finance, as the IT team sees the big picture of the entire business, while our peers in other business lines have near term targets and pressures that inevitably, and necessarily, shape their view to be more personal. 

This maturing of the CIO role will also change the way data integration is carried out in organisations. In the past, data integration was always seen as a project with a set end date. This was a pitfall that often led to data integration projects failing. For data integration to succeed, it has to be a constant programme of business improvement that is iterative.

This approach to data integration thrives on balanced expectations, long-term resource commitment, regular reprioritisation, agile business partnership, and continuous learning and improvement. Data integration will therefore be business-critical and critical to the success of CIOs and their transformation agenda. 

Read more about data integration

  • Automated data integration can reduce time spent by data professionals on repetitive tasks. Learn about strategies to help implement automated data integration.
  • Maintaining data integrity through improved communication and data literacy is paramount for organizations in the enterprise seeking to ensure data quality and trust.

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