Financial services (FS) firms are custodians of vast amounts of data which is not being used to its full potential; instead, decisions are made on instinct, with trust paid to organizational know-how and experience. Moving from data-apathetic to data-driven decision-making techniques enable organizations to take a scientific approach to making decisions. Companies with a highly data-driven approach to decision-making are three times more likely to report significant improvements in their decisions. There is a huge opportunity for FS firms to make smarter use of their data in remaining competitive and relevant. In this article, we explore what data-driven decision-making means for organizations and customers alike by improving profitability and customer value, and the common challenges that organizations must overcome to create an environment that maximizes the benefits of data.
By: Joseph Forooghian- Principal Consultant, Teddy Lee- Consultant and Iona White- Associate at Capco
A data-driven organization is one that makes decisions based on data, rather than relying on intuition (experience, instinct, and political capital). Intuitive, or gut-based, decision-making leads to overly simple and biased analysis of business problems. While most companies want to be data-driven, under a third say they are good at connecting analytics to action and we find, equate being “data-driven” to producing reports for Management rather than contextualizing and harnessing the right information to make decisions.
The first ingredient in the recipe for data-driven decision-making is making sure stakeholder needs are understood properly. This means understanding the right questions to answer and the appropriate decisions to be made, before determining how to use data to answer those questions.
Quality data, underpinned by a robust architecture and strong guidelines around data usage, progress an organization’s ability to use data effectively. Supplementing technical feasibility with an innovative and data-literate culture builds an environment which improves access, trust, and comfort in using data to answer questions. Customers and employees alike often rely on instinct and emotion to make decisions rather than relying on facts. For customers, this apathy towards data-driven decision-making could be attributed to the ease of ignoring complexity. However, we believe firms who are well placed to supply insights have a role to play in enabling the customer to be more data driven. For customers, understanding their own data needs, sourcing information, and producing insights for decision-making is time-consuming, complex, and unrealistic. When a company fulfils customer insight needs, by virtue of strong data capabilities, they spur on greater customer demand for data – driving subsequent organizational improvements. For customer and company alike, making timely decisions powered by data requires access to and trust in, and comfort in analyzing data.
There are two approaches to decision-making: gut-based (reflexive) decision-making and the more logical, data-based (reflective) approach. Whilst a gut-based decision can feel more natural, its ease is owed to the lack of challenge from external sources. Employing the scientific rigor of data-based decision-making, which requires intent and awareness to implement, leads to better decisions that are shielded from bias. Biases, moods, and emotions all weigh heavily on decisions, producing sub-optimal results.
Asking The Right Question…
Making data-driven decisions does not mean ignoring the person behind the data; individuals still need to ask the right questions and should maintain an awareness of and remedy unconscious bias, such as personal experience, while doing so. Asking the right question can be the difference between finding out the answer to your problem and finding out the answer to your question – they may not be the same thing. Empowering business leaders with a better understanding of their issues helps leaders ask right questions and supports the production of meaningful insights. Asking a different question of the same data will always produce different results.
Data-Driven Decision-Making
94 percent of people recognize that using data to make decisions helps them perform their job better, yet only around half of decisions are made using data. Explicitly leaving data out of the decision-making process is often a result of being uncomfortable using data, mistrusting data sources and being under an illusion of understanding the data at hand. Providing readily available and trustworthy data to data-literate individuals supports the move from outright rejection and apathy towards the active inclusion of data in decision-making.
Trust in data’s comprehensiveness and quality is supported by a transparent and proactive approach to data management and sound data architecture principles. Providing access to trusted data encourages the cultural shift towards the daily use of data and supports data skill development through practice. Improving individual comfort through teaching how data should be specified, prepared, and analyzed promotes a culture which actively uses data for decision-making.
A data-driven organization is founded on a resilient architecture, controlled data pipelines and privacy & ethics by design. Data management should be actively embedded, and scalability enabled through the use of reusable data assets for analytics. Active measures should be continuously taken to improve employee and customer data literacy.
A Recipe For Data-Driven Decision-Making
Data-driven decision-making is the process of translating needs into questions, which are then assessed to produce insights and decisions that are underpinned by trusted data. This can be boiled down into a recipe to service both customers and internal business stakeholders. This universal recipe can be used across the organization to produce insights and decisions which are underpinned by trusted data.
- Understand Stakeholder/ Customer Needs
- Define Data driven Response
- Identify, Source and Prepare data
- Design and Implement Product
- Provide insights to Stakeholders/ Customers
- Obtain feedback on Effectiveness of Insights
Conclusion
The unique, companion-style relationship dynamic FS firms often have with their clients has long placed them in a trusted position to enable customer growth and security. Financial institutions have an opportunity to take a step towards actively supporting client decisions through providing data-driven insights. Achieving this step change is becoming part of any FS organization’s core offering and is a natural outcome of those firm’s access to large data sets.
Meeting expectations of data and insight provision – whether for internal or customer decision-making – will be a cyclical investment which requires focus on operations, technologies, culture, and ethics. Once a decision maker’s expectations are met, expectations will be further increased. When managed with a long-term, customer-centric outlook, this cycle produces sustainable innovation.