For Meggy Chung, the future is all about data. And, like most self-confessed data nerds, what Barclays’ Head of Global Enterprise Data Platforms loves most about data is what you can do with it.
“I often tell people the technology part of what we do is the easiest part,” Meggy explains.
Being truly data-driven is a state of mind. It’s a culture that you need to foster across the organisation. If we get it right, it can help us to reimagine everything. To think about our products and our business in a truly outside-in, customer-centric way.
Our Enterprise Data Platform (EDP) is the technology that allows us to draw data from multiple internal and external sources, and then use it to make decisions and help customers. Using a modern cloud-based architecture, EDP enables highly scalable warehousing, analytics, and visualisation capabilities. Meggy highlights two clear use-cases where the EDP is empowering Barclays colleagues to make a step-change in how they use data.
The first concerns data on the grandest scale. “Our new ESG Hub, brings together data on our Environmental, Societal and Governance impact that we simply couldn't get hold of before.”
In order to improve ESG performance, banks need to draw upon an extremely wide range of data, from energy consumption and emissions to workplace health and safety, to diversity, equity, and inclusion.
Barclays needs metrics tied to every dimension of ESG covering our own operations and our entire value chain. That means the upstream impact of our partners and suppliers, plus the downstream impact of our client portfolio, touching on every sector of the economy, all over the world.
Unsurprisingly, there are some pretty big hurdles to overcome in gathering that data. One, it isn’t always available. A dataset like climate projections is based on a rapidly developing research area. Secondly, data is locked up in siloes across an organisation. Thirdly, the data is complex and unstructured, coming from a constantly expanding landscape of sources.
The EDP provides the infrastructure to integrate all these data sources and formats and create an ESG Data Hub. The hub will serve as the strategic ecosystem for all ESG data, creating a consistent, enterprise-wide data sourcing, processing, storage and consumption solution – we are working on incorporating Gen AI capabilities into the next iteration of the hub.
“We start by sourcing ESG data from multiple internal and external sources. Leveraging EDP capabilities, we then curate this data to create customised data products that help our people make smarter decisions in the real world,” explains Meggy.
The second use-case seems smaller in scale. From tracking the entire global economy to following the journey of a single customer. However, it’s implications for Barclays may be just as far-reaching.
Servicing 360 is a customer-centric, data-driven transformation programme. It integrates data from 26M digital sessions and 3.6M calls involving customers of our US Consumer Bank. “By mapping all these customer behaviours, we can create a real-time 360° view of the customer journey.”
One example is the Clickstream-to-Call Propensity project. “A customer was having trouble signing up for particular benefits on their airline rewards card. They went online and browsed a series of Rewards Hub pages. Our machine learning model picked up the patterns in their clickstream activities and predicted an incoming call in the next hour.”
That call came six minutes later. “We were able to route it to someone who could help with that specific issue. And we could provide the colleague with all the context and customer information they needed to get to a solution quickly.”
Servicing 360 uses the capability of real-time data and the EDP to enable a more personalised servicing strategy. If you know what the customer is trying to do, you can help them better. If thousands of customers have the same issues, you can make those journeys easier, or even create new products that meet their overall needs better. And, by being more customer-centric, we’ll support the long-term success of our business.
In both of these use cases, technology is important. But what matters most are the processes that ensure our data is accurate, consistent and continuous. And that allows us to constantly measure and maintain its integrity.
Data can help us reimagine everything. But only good data. So we are working with every area of the business to build an enterprise data fabric that is consistent in quality, with good controls, lineage and tracking.
Meanwhile, the role of data is only getting more significant. “Everyone is talking about Gen AI. But AI can only learn from the data you give it. Inaccurate or biased data leads to flawed AI. Avoiding those unintended outcomes is one of the most important roles that the human mind can play in the future.”
