By Kelly Attrill, Head of Advisory & Consulting APAC at Lab49.
Data can be both an asset and a liability. Used correctly, it can transform an organisation’s ability to unlock value and enable innovation. However, if data is mismanaged it can have catastrophic consequences. In financial services, firms recognise that the ever-increasing volume of data they handle constitutes an asset that, with the right tooling, can deliver value far offsetting the initial investment. However, in some cases, its applicability to client outcomes may be unclear, and there may be a disconnect between how a business seeks to use data and how it’s currently being managed and distributed.  To avoid this and make sure that data fulfils its potential, it’s crucial to develop and implement a robust data strategy.
Strong foundations
An effective data strategy starts with identifying business goals that will be achieved with data and defining clear operational principles for data management and usage. This includes defining what a firm can and cannot do with data and identifying which areas data can add value to the client and employee. Across the front and back offices, firms must be willing to invest not only in the technology but also in the necessary training to ensure these principles are embedded in client journeys and in the day-to-day work of the team.
A strategy that establishes a foundational set of goals and principles lays the groundwork for the development of frameworks, policies and plans across the firm’s divisions. For example, defining data usage boundaries in the data strategy enables the development of a well-defined data governance framework, ensuring the safe, ethical and compliant handling of data across an organisation.
It is crucial that the data strategy is linked directly to business goals and clear time horizons to achieve these goals. This will drive prioritisation and planning decisions and allow the organisation to monitor progress through the implementation of the strategy. Defining the right goals is important; focusing only on one dimension of the data strategy will limit potential value. With a focus on enabling AI use cases, many firms invest in uplifting and ensuring that the quality of data is correct and can be trusted across the whole landscape. On the whole, this is a good thing but it is just as important for firms to continually invest in skills and technology to unlock value. This includes training employees to understand, access, and use data assets effectively and ensuring that data management practices are integrated into their workflows.
Moreover, a data-driven strategy must be agile, supporting the entire data lifecycle and allowing firms to adopt new tools and techniques as they emerge. This agility is vital for balancing mid-term investments in technology and people with the ability to quickly implement proven or experimental technologies that enhance data management and use.
Enhancing services
To address challenges in securing stakeholder buy-in, it is essential to clearly demonstrate how a data strategy aligns with and supports direct business outcomes and client needs. By showcasing tangible benefits, such as improved product offerings and risk management, firms can build a compelling case for investment in data initiatives.
Effectively harnessing data offers significant promise for firms looking to enhance their service offering. OECD researchhas found that large firms’ investments in intangible assets like data and software—which can scale without linear cost increases—can help grow their market share.
Increasingly, data is being integrated with AI to unlock advanced capabilities. For instance, AI models can streamline risk management by quickly digesting large volumes of changing regulations, and digital lending services have sped up the time to lending approvals by using machine learning and automation to improve credit decisions.
Personalised products tailored to individual clients’ needs are another significant benefit of a data-driven strategy. For example, upgrading Customer Relationship Management (CRM) systems so client information is accessible through consistent channels in an intuitive way allows front line staff to build an understanding of client needs and enables the delivery of powerful insights that may unlock more targeted propositions and spur business growth. These can improve satisfaction and loyalty not only for existing customers but also boost new business opportunities by improving the productivity and efficiency of sales teams, supporting a more competitive commercial proposition. A data strategy that prioritises feedback loops, collecting information based on the insights and proposition value and feeding that into the next set of insights and propositions will enable firms to shift to a data-driven strategy across multiple dimensions – data-driven product, data-driven marketing, data-driven people, etc.
Given increased attention from regulators globally to appropriately manage and protect data, developing a mature data strategy is not only desirable in terms of compliance but can help firms stay competitive by protecting against financial loss and reputational harm.
Future-proofing
As technological change continues to accelerate, firms adopting a data-driven strategy are better placed to leverage that data in new ways across business lines, the product suite and the operating environment. When the focus of the strategy is on disconnecting tightly bound links between technology and vendor platforms and enabling access that is simple, secure and intuitive, the value of the firm’s data assets becomes clearer and more closely tied to business outcomes.
Fostering a culture of data literacy where the value of data-driven decision-making is promoted across the organisation can go a long way to ensuring that all stakeholders, from top management to front-line employees, understand the benefits of a data-driven approach and are equipped to adapt to new ways of working.
Investment in experimentation with AI and embedding trusted decision and insight models into the firm’s decision-making processes becomes much easier once data is more available and protected through the right governance environment. Feedback from the success of this will help drive a data-driven organisation and feed the next generation of data-driven strategy.
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