Succeeding With Data-Driven Transformation in ASEAN
The COVID-19 pandemic has accelerated the use of public cloud and data in decision making, observed Geoff Soon, senior district manager of South Asia at Snowflake. And this perfect storm of change is happening all over ASEAN, where customers are aggressively adopting public cloud solutions specifically to do data and analytics, he said.
Soon shared this insight at a recent lunch event by CDOTrends and Snowflake in September, where a small group of executives gathered under prevailing Safe Management Measures to discuss the rapid evolution of data and the role of the cloud. What strategies and approaches have worked for Asian firms in their journey to successful digitalization and derive greater value from their data?
The scarcity of data talent
The growing scarcity of talent was among the first topics to surface. At least one participant noted that it is increasingly challenging to hire the right people and ensure they are not lured away with fantastic packages offered elsewhere in the region. “I think it is a strategic crisis. [When it comes to data science], it is all about having small highly-skilled teams, as opposed to having big teams with fewer skills,” said the participant.
Dr. Meri Rosich, chief data officer at Standard Chartered Bank, pointed to the top-notch talent coming out of the local universities. She said: “I think that there's a lot of fantastic talent coming out of the local universities. [The industry] must double up, but we also need to invest in them. We need to mentor them and get them internships, train them. We need to make an effort to bring up the next generation to help them, especially given current circumstances.”
Céline Le Cotonnec, the chief data innovation officer at the Bank of Singapore, called for continuous upskilling. “It is our role as organizations to upskill our workers. I think people should spend approximately 20 percent of their time, or one day a week, in training to upskill themselves.”
Of course, the right tools are available, too. “Python is still not available for [many] analysts. The tools that we provide to the business [should match] what they trained on for the opportunity to practice on them. Because if you send them for training on data and analytics using Python and Tableau, but you don’t have them on your tech stack, then there’s no point. You need to have an upskilling journey that is aligned with the tools found within the organization,” she said.
The power of sharing data
The problem of IT not being able to deliver in time is a real barrier, said Edison Tie, enterprise data architect at NTUC Income. Dig further, though, and a lot of it is due to the poor quality of the underlying data. He adds that this can be alleviated by sharing data and establishing a sharing network that cuts across departments.
Participants agreed that the opportunity for data sharing is enormous, though roadblocks must be overcome. Derek Lim, the senior director of Digital & Transformation at Singtel, highlighted the problem of departments or users hanging on to data.
“I can [share the] data, but when will you destroy the data? How am I assured that the data that I have shared with you is kept in line with the classification of the data? What are the security practices to be adhered to, and what sort of approvals are required for sharing the data? I think these are fundamental considerations as part of any data sharing strategy,” said Lim.
Richard Lowe, the group chief data officer at UOB, ticked off benefits to data sharing such as financial inclusion, digitalization, and improving efficiency. But meeting the criteria to implement data sharing is trickier. “From a data sharing perspective, I think it does come down to the [business] objectives. The challenge is looking for something that can be operationalized, and this is very hard. The challenge is matching the business objectives, such as detecting financial crime, and being able to measure the outcome.”
On the road to success
To succeed, organizations will need to move on from a rigid, defensive mindset where hoarding data is the norm due to fear of repercussions should something go wrong. This necessitates putting people in charge whose jobs are to ensure that data gets shared where appropriate and to maximize the value of this data.
Soon pointed to a white paper that was produced recently on data sharing for the financial services industry in Singapore. “I think as we move forward, we are going to see much clearer frameworks developed about how organizations can share data in a way that is endorsed and supported by the government. I think, as more structured guidelines on sharing data are formalized, a massive acceleration will take place.”
Finally, one suggestion offered by Le Cotonnec would be to combine the role of the chief data officer (CDO) and data protection officer (DPO) for accountability. As someone who holds this combined role at Bank of Singapore, she explained the rationale: “Otherwise, the CEO would just be fighting with the DPO who will not want to share data to get more business value out of the organization’s data. If you have one person that understands the value of data and is also the DPO, then [he or] she can be held accountable.”
Paul Mah is the editor of DSAITrends. A former system administrator, programmer, and IT lecturer, he enjoys writing both code and prose. You can reach him at [email protected].
Image credit: iStockphoto/hxdylk
