While financial firms in Europe and the US have made great strides in advancing their analytics maturity, Australasian FSIs are falling behind their global counterparts, says ASB’s chief data and analytics officer, Anthony Branda, ultimately hampering their ability to leverage data assets and deliver a competitive advantage for their businesses.
By building an “integrated business-linked intelligence function” across ASB, Branda hopes to narrow the bank’s maturity gap over a designated three-year timeline.
Since joining the Kiwi lender a little over a year ago, Branda has ushered in a three-fold growth in ASB’s analytics team, from 60 to 200 professionals, as well as a wider transformation program to embed data-driven decision-making across all parts of the enterprise.
Speaking at the Future of Financial Services, Auckland 2021 virtual conference, Branda, a veteran analytics chief previously serving at Citi North America and RBS Americas, observed that, despite the growing number of dedicated C-level positions for data and analytics across Australasia, there is still a disconnect between business chiefs and their heads of data.
While in “many other markets” CAOs report directly to CEOs, in New Zealand, he notes, this is far from the norm.
“One of the big things in my career has been really helping to get businesses out of the thinking that the analytics function is an area you turn to just to get a number,” Branda said.
“We really want to be proactive in planning with the business and making sure that we’re not so much of a shared service, but we’re actually plugged in as a strategic enabler and a partner.”
Instilling a proactive approach to analytics
ASB’s analytics overhaul involves building out an “integrated analytics function” to plan analytics strategies alongside business units, enabling more data-driven decision making.
According to Branda, the new function acts as a ‘hybrid’ – structured in a way that is both centralised and decentralised – having data infrastructure and customer interactions (plus CRM) at its core, and supplemented by growth in insights and next-generation analytics capabilities.
Crucially, the bank has also drawn up a ‘citizen data science’ framework, embedding data visualisation tools for business units – including marketing, customer, finance, and product teams – to independently draw out relevant insights using self-service analytics.
However, he cautioned against the tendency for business owners to create dashboards that are “generic”, which do not dig deep enough to draw any real insights or recommendations from the numbers they are shown.
“You want to take it to the next level and say, ‘What are some of the recommendations [coming] off these dashboards? What’s the story?’”, he explained.
As a result, Branda emphasises the importance of data literacy and education, ensuring business units understand the breadth of analytics deliverables they can ask for.
To date, a bank-wide education and training initiative has been rolled out, with all staff required to take a data fundamentals course – an important step, Branda notes, apart from knowledge-sharing and analytics planning sessions, to maximise ROI from analytics deployments.
“We have lots of interaction points [across the business], not a lot of static reporting or just sending information over. This is something that has worked out particularly well.”
Another game-changing move, according to Branda, was the creation of an ‘analytics liaison’ – a hybrid role held by individuals he refers to as ‘unicorns’, who can bridge the gap between business and technical analytics practices.
The ‘unicorns’ are individuals skilled at data storytelling, who have a good grasp of business objectives and can define business problems – all of which help business units get the best value from their analytics consumption.
Unicorns are also strategically placed to interact with ASB’s analytics centre of excellence (COE).
“When I first onboarded, there were pockets of analytics all over the place and platforms were not in the actual [analytics] practice or the COE. We’ve slowly moved everything into one unit and aligned them with different business-facing liaisons”, he explained.
On the other hand, for analytics practitioners dealing with business teams, Branda stressed the dangers of ‘weaponising’ analytics or attempting to tear down existing ways of operating.
Here, collaboration yields results. Analytics practitioners should, he says, be brought to the table to offer a particular recommendation or approach, with business heads then invited to “figure out how to apply it collaboratively”.
“It is more an agreement on a path to deploy the analytics and what we need to do next,” he added.
“Leadership with analytics is about making it very collaborative”.
Heralding the future of work
Going forward, Branda says he is excited to transform and automate much of ASB’s legacy business intelligence capability.
To achieve the coveted status of an “insights-driven business”, as promoted by the likes of McKinsey and Forrester, Branda stressed the importance of aligning data operations, engineering, and machine learning functions within analytics workflows, as well as being clear on the need for predictive versus descriptive analytics – that distinction between insights to forecast future business needs and insights to remediate past ills.
Getting these parts of the business to collaborate well, he said, is key to delivering on customers’ ‘moments of truth’.
“Make sure you’re always thinking about the future of work and what level of manual reporting versus programming skills will be required to drive a paradigm where you have automation and artificial intelligence, but you have humans and machines thinking together,” Branda said.
“Ask yourself, ‘What level of integration and collaborative thinking do you need? And this will help you figure out the resources required?’.”
In terms of upskilling staff, Branda is currently piloting a rollout of the Certified Analytics Professional (CAP) global certification among ASB’s analytics teams, regarding it as critical to uplifting skills and standards.
“In order to stay relevant, you have to be willing to cross-train, learn new skills, learn a lot about programming and changes in technology on an ongoing basis,” he said. Branda himself took a mid-career stint to pursue a doctorate in customer intelligence and marketing.
“In analytics and data science, it’s a continuous learning paradigm.”