The Data Renaissance Man
The Renaissance was a period of immense cultural and intellectual change that swept through Europe roughly between the 14th and 17th centuries. This period saw a questioning of traditional beliefs and a rise in scientific exploration. This led to groundbreaking discoveries in astronomy, anatomy, and physics, laying the foundation for modern science. New inventions like the printing press facilitated the spread of knowledge and ideas. Additionally, advancements in shipbuilding allowed for greater exploration, leading to discoveries of new lands and cultures.
In the past
Closer to home, here in ASEAN, when we look at historical periods of cultural or economic flourishing, we look at
The Khmer Empire ruled Cambodia from the 9th to the 15th centuries, famous for its grand temples like Angkor Wat. The empire was known for its complex hydraulics system, including networks of canals and barays, or giant water reservoirs. This system enabled the formation of large-scale rice farming communities surrounding Khmer cities.
The Majapahit Empire was a powerful Javanese empire that dominated Southeast Asia from the 13th to the 15th centuries, known for its trade and cultural achievements. The Majapahit Empire rose to prominence not just on land, but also at sea. Its powerful navy, comprised of formidable warships known as jongs, granted them dominance over trade routes and control of key ports. This flourishing trade brought immense wealth and prosperity to the empire, allowing for the patronage of arts, literature, and architecture.
In the now
We have since moved into an era of economic flourishing by way of the digital economy – billions of connections every day between people, businesses, devices, and data.
With the ASEAN digital economy set to grow to USD 1 trillion by 2030, businesses are working to balance using data to create innovative products and services in the digital world while at the same time, protecting data adequately.
A new era of data-driven insights
Just like the Renaissance saw a renewed interest in classical learning and scientific inquiry, a data renaissance suggests a surge in using data to understand the world around us.
On that note, we recently had the privilege of hosting Dr. David R. Hardoon, CEO, Aboitiz Data Innovation at the AIBP office for an #AskMeAnything session. Read on below for his insights!
Hi David, we call you our resident data renaissance man. With that in mind, could you give us an introduction about yourself?
I say it very publicly, I'm a data geek. I've had the privilege of touching many, many industries from healthcare, finance, power, and so forth. It's always been situated around data. In fact, the first 10 years of, I guess, quote, unquote, my career, I was an academic. And some would say, you know, I went to the dark side (having moved out of academia into the corporate life). I had, again, the great privilege of working as a regulator. And the reason I say privilege, because it gave me the appreciation of governance. It wasn't just about understanding it, but seeing how innovation and governance are intertwined. Currently, I'm obsessed with making AI work. It might sound corny, but when you ask people and organizations if they use data and AI, almost everyone says yes. But then, if you ask if they're using it in production or making business decisions based on it, most reply that they're still experimenting or piloting it. That's what got me thinking: how can we bridge the gap and make these innovative capabilities truly useful?
We have a question from the floor and this could be a good segue into what you do currently. What is ADI's AI strategy?
Sure. Aboitiz is a Philippine conglomerate with a diversified portfolio in energy, financial services, cement, construction, and more. Aboitiz Data Innovation (ADI) is based here in Singapore. We're focused on how to not just maximize but fully capitalize on data. We've been around for decades, collecting and capturing data, but are we really using it effectively? The question is: how can we leverage data and AI to create new revenue streams, improve customer engagement, and achieve greater operational efficiency? Think of AI as a really good librarian. You tell them your problem, and they point you to the right shelf and even the specific paragraph in a book. AI can help us extract knowledge from information and use it for various purposes, from customer satisfaction to risk management.
The strategy is to use AI strategically to extract knowledge from data and use it for business value. This can be applied across Aboitiz's diverse businesses. For example, in the Philippines, where financial inclusion and sustainability are priorities, we can use AI to identify power customers who have been loyal but lack access to banking services. By combining data from different sources, we can offer them new financial products they wouldn't have qualified for before. That's the essence of what AI can do: unlock new opportunities and create entirely new services, all driven by data.
What are the biggest challenges data engineers face (in the FSI sector)?
Data Provenance: No one cares about data provenance, which is surprising because it's crucial. Data governance, data quality, data ingestion – all these things are like plumbing. No one appreciates the pipes until they leak. But without a solid data foundation, you can't get the information you need to make informed decisions or capitalize on opportunities.
Technical Debt: Sometimes building the data pipelines seems easy on paper, but then you realize you have to fix a lot of outdated infrastructure before you can move forward. This can be a big cost to justify, especially when the benefits seem specific to one application. But technical debt is real, and you have to address it eventually, regardless of the number of applications you're working on.
How do you ensure the resiliency of your services and achieve regulatory compliance?
So there's a few ways to look at this. So I think first of all, is the idea of sustainability. So let's say you want to change all the light fixtures in a building, ideally you don't have to destroy the whole building just to get this change. This concept goes beyond just data; it considers potential changes in customer feeds and system architectures. A sustainable system allows for adaptations without major disruptions, unlike inflexible systems that require significant downtime for even minor changes.
When you talk to business leaders, "Hey what do you want to do with AI?', it's going to be hard to get a clear direction or vision. Don't ask a business what they want to do with AI; they may not have the knowledge yet. Instead, focus on their current goals (e.g., increasing sales by 50%). Your job is to then show how data automation or AI can achieve those goals with concrete results, which makes AI application a lot more relevant and easy to grasp. Don't overwhelm businesses with entirely new concepts. Instead, identify areas where existing processes can be improved using available technologies. Get small, easy successes and that will pave the way for further possibilities.
On the regulatory front, regulation can't and might not keep up with AI but you can't wait for it to be broken or for problems to exist before trying to fix it. You need to have the right policies in place for handling unexpected events. This includes Business Continuity Plans (BCPs) for maintaining operations during disruptions and clear protocols for risk assessment and response. I think adaptability is the most challenging aspect. Operations teams typically excel at performing established tasks but may struggle with questioning existing norms. A dedicated team can challenge these norms and ask critical questions to ensure adaptability and continued relevance.
I hope the insights shared prove useful for you. This candid conversation is the first of many that AIBP will be facilitating across the region in the next months.
Coming up, we have
Working group on Sustainable Innovation in the Philippines, co-hosted with Vista Land and Lifescapes, Inc. (3 July)
Our flagship Conference and Exhibitions across ASEAN (16-17 Jul in Thailand, 6-7 Aug in Indonesia, 3-4 Sept in Malaysia, 17-18 Sept in the Philippines, 15-16 Oct in Vietnam)
If you're interested in getting more insights on the data journey of enterprises in the region, or would like to be a part of any of the above discussions email aibp@industry-platform.com
