How better operational data can future proof operations and improve decision making

Banking operational teams have a persistent data problem – they are sitting on vast quantities of data, but generating insights from it to make critical decisions has frequently proved elusive. In my career spanning more than 30 years in banking operations, I’ve witnessed first-hand the challenges this creates and the ongoing struggle for ops teams to get a better handle on their data.

The challenges of unlocking actionable data

A combination of factors has contributed to this issue. First, banks often depend on sprawling legacy systems and fragmented infrastructure where data is usually processed in batches at the end of the day, making it impossible to get real-time insights operations leaders need. Second, operations teams don’t always have the necessary data and analytical skills to drive more informed decision making. A third more recent challenge is the rise of hybrid working and managing teams who are both remote and in the office.

All of that has made it very challenging to capture and extract data and pull it together in an integrated, insightful way that can lead to better analysis and decision intelligence.

In an environment where operations leaders are under increased pressure to do more with less, those data-driven insights are crucial for ops teams to allocate and scale resources more efficiently while understanding and improving the end-to-end customer experience.

In one of my recent roles, we had to deal with the launch and implementation of two UK government coronavirus loan schemes. We knew this would create a temporary spike in volume. Therefore, we needed to understand current team capacity and capability so we could either make a business case for hiring more people or cross-training existing staff to build scale quickly, none of which can be done efficiently without access to reliable data insights.

It is not just about cost either. Advances in technology and digitization through the use of bots, machine learning, and AI mean it is increasingly important for data to be integrated and presented in a way that gives a 'helicopter' view of operations. This enables leaders and ops managers to drill into relevant detail in a timely manner so they can plan more effectively and better manage resources while also transforming operations for the future and ensuring you are building the right skill set.

Improving decision intelligence

Those organizations that aren't embracing data-led insights into their decision making will miss opportunities to drive improved performance and operational resilience.

To get on the right path, operations leaders must ensure data is a key consideration for organizations when moving from legacy systems to new technology by stressing the importance of high-quality, integrated, and timely data. This will ensure they get the data insights they need, helping drive process efficiencies and streamlining the operations function.

While operations staff don't need to be data scientists, they do need to use data in an informed and unemotional way. Therefore, operations leaders must also invest in training and development so those skills are present across teams while also taking advantage of advanced AI to provide more prescriptive insights (and potentially reducing resource needs).

Ultimately this can help improve decision intelligence for workforce management, moving away from an emotion-led decision-making environment to one that is entirely data driven. This will lead to more streamlined and efficiently run operational teams that are more resilient to future industry opportunities and challenges.