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Data maturity models: how to build your data capability

Effective use of data is more important than ever in the current economic landscape. Nikhil Asthana outlines a four-step model to help you review and develop your current capabilities to meet your long-term goals. 

With increased economic pressure due to COVID-19 and Brexit, many firms are leveraging data to improve customer engagement, drive new business, identify cost savings and improve the control environment. To achieve these goals, a successful data capability typically consists of two strands: defensive and offensive use of data – with both important for a mature model.

Defensive approaches include identifying cost savings, mitigating risks, such as financial crime, and maintaining regulatory compliance, such as supporting the LIBOR transition. Offensive approaches include identifying emerging customer trends, improving client insight and developing new business relationships. 

Historically, data capabilities have focused on good data management to support defensive capabilities, but a more-mature data capability will give rise to more offensive approaches, support digital transformation and help monetise your information.  

Using the four-step data maturity model 

As with any long-term planning, having a clear vision of the target end-state and how your data can actively support your business is vital. The data maturity model below depicts what good looks like and provides a roadmap of how to get there. Using four key delivery elements, you can review and develop your current capabilities to meet your long-term goals.  

Diagram depicting the four-step data maturity model

1 Data foundation capabilities 

Effective data management can be the limiting factor for your data capability so it’s important to get the basics right. Assessing existing data management processes, including identifying and remediating legacy quality issues, can improve data integrity and mitigate the risks. Further training and awareness programmes can also build data literacy, helping to identify new use cases and maximise the value of your data to support business goals. 

A mature data capability, however, looks beyond data management, and can add significant business and monetary value. To build maturity, setting the risk appetite is the best place to start, establishing expectations and embedding an appropriate control environment. New capabilities that sit under the chief data officer (CDO) may also need further resourcing and more funding in line with its growing remit. Reviewing your legacy platforms, potential data migration plans, cloud or on-premises storage and embedding good data ethics is also essential for long-term success.  

2 Ecosystem and enterprise    

As the data capability becomes a more valuable business function, it’s important to consider its integration and interaction within your wider enterprise and beyond.  

Without internal stakeholder buy-in, your data capability won't be effective or add value to your recovery efforts. Consider how your organisation is actively helping your data culture and data capability to grow. Support from all relevant business, with clear ownership and accountability, will help develop and implement new use cases and turn good data management into a competitive advantage. Embedding new data approaches may require changes to the firm’s operating model, processes and policies (including the data policy), with a potential impact on the firm’s technology and business architecture.  

It's also important to consider interconnectivity with the broader data ecosystem, including leveraging external data, data partnerships and platforms. Drawing on all available market data can help track emerging trends and customer expectations, helping you innovate and grow with client needs.  

3 Enabling capabilities 

The role of the CDO is expanding from data management and governance, technology and architecture capabilities to supporting a forward-looking, data-driven organisation. This includes managing legacy information in data stores and data lakes, mitigating cyber risks, and overseeing data privacy and protection, including the General Data Protection Regulation (GDPR).

Data science is also a key growth area for CDOs, including analytics and visualisation, giving rise to change programmes in line with new use cases.  

4 Data monetisation and value creation  

The CDO is responsible for developing new data use cases for value creation in keeping with your business ambitions and long-term goals. New use cases can identify areas to leverage data for better decision making or operational processes. With the changing business landscape, this will help you identify emerging opportunities, creating new revenue streams to support economic recovery. When creating value and monetising data, good data management is essential to protect the integrity of the underlying data and to make sure the right information is available at the right time.  

Looking beyond data management 

Data management is a common challenge for firms across all sectors and can limit your data capabilities. It can hold businesses back and prevent them from reaching their potential. As 2020 draws to a close and firms focus on economic recovery, closing these gaps to make the most of your available resources and maximise every opportunity is key for the road ahead.