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Creating Superior Commercial Performance in Retail Banking through Advanced Data Analytics
By Bjørn Büchmann-Slorup, Head of Portfolio Management & Pricing, Danske Bank
Figure 1: The three phases of value creation through data analytics. Source: Danske Bank
Building a Data Science Centre of Excellence to answer (part of) the disruption threat
The data foundation has been in place for many years, and like many other banks, we have solid and very successful business intelligence units, assisting the frontline with data-driven insights. We built and continuously developed this foundation throughout the first phase, which have lasted for decades. Digitalisation through e.g. Advanced Analytics, Big Data, and Machine Learning is being praised (hyped) as some of the building blocks to disrupt the incumbent banks as we know them. Hence, the natural answer to that threat is to build your own capabilities within these areas – before somebody else does it for you. Three years ago (in the second phase), we built up a Centre of Excellence (CoE) with core data-science capabilities and a full strategic mandate as a part of Strategy and Business Development.
Six Prerequisites for Success
Throughout the second phase, we established an understanding of what was required to get commercial success, and we concluded that these six prerequisites had to be in place:
1) That we had full senior management buy-in
2) That ALL problems we were looking to solve started from the customers perspective,to ensure, that the data scientists would have meaningful dialogues with our internal customers
3) That we applied the data we already had, as opposed to thinking of what might come out of working with external (or other new) data
4) That we had the ability to execute on our customer deliveries through an IT production environment
5) That our internal customers felt a true ownership of these new customer deliveries
It takes time to design everything correctly and more importantly to enable the cultural change to happen in parallel
6) That we had the ability to measure and communicate the impact of our customer deliveries
Culture Eats Strategy for Breakfast
After a few years, we had managed to establish a solid Data Science CoE, and we had seen some very successful new models, affecting the customer experience (and hence derived commercial performance) with a very positive and documented effect. However, we still felt that we not gotten a proper breakthrough and we realised that the biggest barrier to commercial impact was CULTURE. As such, this was not a surprise, and yet it all came down to prerequisite five – true ownership among our colleagues in the frontline.
Establishing Customer Portfolio Management in the Frontline Created the Next Level Breakthrough
In the third phase, we addressed the cultural barrier by creating a data-driven unit, Customer Portfolio Management (CPM), in the very frontline of the bank. The unit was placed right alongside the advisors, the call centre, and other classic units you typically find in a bank today. The purpose of this new unit is essentially to apply all the right elements of advanced data analytics (from Business Intelligence to Predictive Machine Learning Models) in a way that it supports all other units to perform in the best possible way. CPM has roughly the same goals and the same KPIs as its peers, and the key responsibility is to create full transparency of each customer’s journey through the bank. Because, understanding the individual customer journeys, allows you understand the needs of your customers and what drives commercial growth. If your customer portfolio only holds few customers, you can manage this as a human. However, when the total portfolio is say 500.000 customers, the machines need to take over. However, we only let them take over the “homework”, so our colleagues can spend time on the customers, and very likely spend their time in a more optimal way, than what they would have suggested themselves.
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The Commercial Success comes from Increased Transparency
There are many examples to highlight the value created through CPM, but these are the three key elements:
1) By linking activities to results through individual customer journeys, you get a profound transparency of what really works in terms of customer experience and commercial performance, allowing experienced and qualified colleagues to take even better decisions than they did yesterday.
2) All activities that goes to market (no matter the size or the channel) are supporting business priorities and the effect of the activities are linked directly to the forecasted performance.
3) The centralised CoE’s only have to serve one customer in the frontline, who takes full ownership of the models and other data deliveries, and in return, the CoE gets high value feedback for future development needs..
As an example, we identified a sales funnel, which was not delivering the expected value. It had been active for years, because it was considered an important growth lever. We identified the exact point in the customer journey, that was halting the performance, and our frontline colleagues made the needed changes; performance increased 160 percent after a couple of months.
With all this said, it is important to mention that Rome was not build in a day. It takes time to design everything correctly and more importantly to enable the cultural change to happen in parallel. People need to see things work (numerous times) before they change their habits, but we are moving forward and we are creating real commercial impact through advanced data analytics – and we love every minute of it!