Dive into data

Overcoming ingrained perceptions of how to do business while navigating immense data analytics challenges will be critical in helping financial professionals recover from the Covid-19 pandemic, an expert panel told the sixth ACCA Asia Pacific thought leadership forum.

Titled Growth Recovery Leveraging on Analytics-Driven Forward-Based Insights, the online forum, held earlier this year, attracted more than 700 attendees from countries ranging from Singapore, mainland China, Hong Kong, Vietnam, Malaysia and Brunei.

Despite the availability of powerful data analytics technologies, 81% of financial teams still use Microsoft Excel spreadsheets for their analytical needs, according to the Analytics in finance and accountancy report prepared by ACCA and Chartered Accountants Australia and New Zealand (CA ANZ).

The early adopter

Some companies started looking at their data analytics capabilities before Covid-19. Maybank Group was one, with the bank getting a head start in the early 2000s.

One of the three panellists, Siva Raj Jeyarajah, executive vice president at Maybank, told the forum: ‘That was when we started investing in a data warehouse, and there was already discussions surrounding predictive analyses. However, we decided to focus on customer profitability as a start. More recently, especially in the past six to seven years, driven by competition and market forces, there was much encouragement by the senior management for the extensive use of data analytics to give us competitive advantage.’

The company invested heavily in data analytics, including courses for staff. It also set up a data science team, operates a digital transformation and analytics programme, and recently rolled out an SME digital financing platform based on analytics.

No legacy burden

Smaller companies, such as CareVoice, a startup that’s commercialising health insurance through online channels, have also found ways to take advantage of data analytics.

CareVoice’s CFO, Luke Jones, another panellist, told the forum: ‘I am not constrained by any legacy system. I have the opportunity to set up data governance and processes from scratch. Undoing decades-old legacy systems is challenging, and that’s why Tesla, for example, is streaking ahead of other original-equipment manufacturers – it could start from a clean slate.’

The challenge in being a startup, however, is balancing constant delivery against strategy. It can be difficult to be strategic and plan things out so that it can benefit the company as it grows, Jones said.

Chinese IT company ZTE is further along the road. Wenwei Xie, deputy financial officer of ZTE’s Asia Pacific division and the third panellist at the online event, told the forum: ‘We have already started the transformation process and have a data warehouse. Many of our global finance staff are working in data analytics, but we are still engaged in the transformation process and need a little more time to figure out how to use the data warehouse more efficiently.’

The challenge in evolving also lies in changing perceptions. ‘Accountants generally still think that the data should come from someone else,’ said Maybank’s Jeyarajah. ‘But there is a grey area between getting the data, analysing the data, and transforming it into good information – to predict what the next outcome will be. That grey area is something finance professionals should target.’

Tapping the grey area could involve something simple. For example, learning an analytic application such as the R or Python programming languages can be done via a YouTube programme. Having access to a sandbox (a separate testing environment), or any platform where data can be stored and explored, is also critical, he added.

While knowing how to do statistical analysis is a crucial challenge, online classes are an easy way to build on that knowledge, according to Jeyarajah. ‘Can an old dog, or indeed anyone, learn new tricks? Of course. But it boils down to the will to learn. You must be ambitious, you must dream. But don’t just keep dreaming. Start small, start somewhere.’

For CareVoice, being more strategic and planning in between month-ends and reports is the biggest challenge. ‘We’re so busy with reporting and looking behind and doing things like variance analyses that we struggle to tell the story,’ Jones explained. ‘What can we do with that data? How can we put it into a report that’s meaningful when giving it to function heads within the business, or presenting it to the CEO, or the board of directors or analysts?’

He also stressed the importance of pinpointing business drivers and spending the time to understand them in order to find the data levels and data points needed.

Data purity

A further challenge is sifting through enormous amounts of data and ensuring its accuracy.

‘You can never run away from data issues,’ Jeyarajah said. ‘We as an organisation have trillions of data values coming in daily. When we set up our data warehouse in the early 2000s, we had a lot of data issues. We still have them, but we’ve cleaned up quite a lot. You have to set a strategic programme to capture good data or screen out the data at the ground level, as well as the entry points in the source systems and databases, and keep doing it continuously.’

ZTE’s Xie put it this way: ‘If you clean your house every day, it’s an easy job. But if you clean it yearly, the task becomes bigger.’