Neel Arya, Director, KPMG in the UK
Stan Lepeak, Global Research Director, KPMG LLP Advisory
This is the third in a five-part series (read Part 1 and Part 2 here) on the importance of improved data analytics among retail banks.?
Adjusting operating models and capabilities in order to better develop mutually beneficial partnerships across the business
There is, in most cases, a clear disconnect between the analytics department and the business within banks.? It is essential that this change. Customer insight and analytics teams should develop new skills and a new approach in order to deliver meaningful value. In doing so, they can inevitably build a stronger working relationship with the business.
It is clear that in the future, customer insight and analytics teams will look very different from the way they look today. There is little doubt that the relationship between the business and customer insight and analytics teams must evolve, and more must be done to enable the analytical insights from big data to be adopted and acted on.
Many retail banks suffer from an evident ?clash of cultures? between the business and analytics where the business relies on its experience dealing with people, and the analyst relies on logic and academic methodologies.? One banking analytics leader admitted that ?they call us data nerds.? The reality is that customer insight and analytics professionals will need to evolve from ?data nerds? into analytically literate business people. To see proof of this, examine the cards business within retail banks; experience here points to the fact that the analyst of the future will need to be a hybrid of both the analytical and business worlds.
However, embedding teams of analysts into each product group is not a long-term solution. Already, the somewhat fragmented structure in most customer insight and analytics teams has resulted in squandered business benefits (such as cost savings and improved insight). As a result,? insight and analytics teams will increasingly start to move towards a centralized-decentralized model where skills are centralized (thus offering scale and access to a wider array of services under one roof), while analytical ?business partners? are decentralized and remain close to the business, interoperating between the? hub and their business clients. ?Among other benefits, this can enable greater focus on capability building by developing analysts? business understanding and strengthening communications skills within the business partners, while simultaneously enhancing knowledge sharing and creating more dynamic career paths.
What will emerge are analytics business partners with deep insight into the needs of the business and strong analytical knowledge, who can face off to internal customers. This new breed of analytics professionals can harness their capabilities to both translate the business? requirements to the central insight and analytics team and, simultaneously, work with the business to identify opportunities where analytics can add further value.
Besides the clear cost benefits that come from employing a centralized-decentralized model, this approach can create a hub of innovation, ?where the creation of new models and the dissemination of leading practices, leads to enhanced customer revenues, profitability, loyalty, and advocacy.
Read the full report, ?Time to grow up, Perspectives on customer insight and analytics in retail banking.?
For more from KPMG on this topic, visit the?KPMG Shared Services and Outsourcing Institute.
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