Following his participation in the Tech Startup Launchpad at DATAx Singapore last month, we took some time to catch up with Botbot.AI founder Wong Hong Ting to discuss his views and advice on data leadership within Asia's technology sphere, and hear his thoughts on the challenges facing companies navigating the blossoming Asian startup scene.
Botbot.AI, an enterprise automation company with offices in Singapore, Indonesia and Vietnam, uses chatbots as an interface for enabling the ground-up collection of data, which helps to facilitate the eventual automation of repetitive decisions made within enterprises today by using.
In a wide-ranging discussion, Wong Hong Ting discusses the hurdles technology companies face in Asia, such as heavy regulation and the perceived lack of local customer interaction, while offering his views on how the democratization of data science tools and increasing citizen data science skills can help to drive success for data teams and their leaders.
DATAx: What are the main challenges facing startups in Asia today?
Wong Hong Ting: The ambivalence toward the adoption of technology is a phenomenal challenge. While everyone embraces the fact that technology is critical to advancements in each industry, which is evidenced by the sheer number of corporates investing in innovation teams, there is a "kiasu" or an "afraid to lose" mindset rooted deep in Asian cultures which becomes a hindrance during the trial of new technology within organizations.
While there may be teething pains in the beginning, we must come to realize that solutions, when fully rolled out and implemented across multiple iterations, will ultimately impact and disrupt the individual, company and industry.
Specifically, this issue is seen most severely in regulatory slowdowns, especially in fintech, medtech and heavy industries. Since their origin, they have been heavily regulated (and for good reason), but few regulatory bodies embrace innovation with understanding and receptivity.
On the clientele front, there is a clear lack of customer champions. Unlike in the US, where customers are very happy to act as references to other (even competing) enterprises, in Singapore, customers tend to be conservative with their feedback and rarely allow for testimonials to be made public.
The manifestation of these issues can be seen in startups with great original products closing down due to the seeming "lack of product market fit", or through adjustments made to the product that, in the short run will help to attract customers, may not ultimately be beneficial to the growth of the product versus a competitor's product in the US, Europe or China.
DATAx: What makes Singapore stand out as a location to establish and build up a tech startup?
WHT: First of all, it's the fastest place to get a private limited company up and running, even if you are from abroad.
Singapore is also a great place to access ASEAN talents and global customers, all from one safe, clean city. Regulatory frameworks here are also friendly to investors, giving startups more reach in terms of attracting investors from across the globe of all mandates and fund sizes.
DATAx: What does leadership in the data world mean to you and what advice would you offer someone entering a data leadership role working within the Asian tech space?
WHT: Organizations have begun to understand that data can serve as a critical decision-making resource that drives business at a strategic level. From reporting to the chief technology officer (CTO), we now see many chief data officer (CDO) positions being filled by some of the brightest minds in data, even as Asian CDOs faces new issues, which are similar to what chief innovation officers faced five years or so ago. These include those in the realm of attaining buy-in, justifying and managing a data budget, and juggling data strategy with business intelligence.
Looking closer at these hurdles, in terms of getting buy-in on the significance of data from shareholders, the board and management, right down to the boots on the ground, is a huge feat. To enable systematic data collection to be conducted at every level and its impact felt by everyone in the organization, leaders in data roles often find themselves having to convince hundreds of people in every undertaking. Most crucially, organizational buy-in consequently affects how well they can obtain, justify and manage a data budget.
Leading up from that, the one characteristic we've found most impressive of the best data leaders is their ability to manage their data strategy (including communications both internally and externally), data governance, standards, controls, definitions, architecture, tools and technologies against business intelligence, reporting capabilities, advanced analytics and, last but not least, collaboration with external organizations to audit and validate internal data. The delicate balance between data strategy and business intelligence is ultimately the catalyst of success for data teams and leaders within organizations.
DATAx: What key trends, in respect to data science, do you see your industry embracing over the coming 12 months?
WHT: Three years into the hype of everyone adding AI to their products or services, the novelty is beginning to wear off. Many of the organizations we have co-created products and services with have finally collected sufficient data to gain direct benefits from having a tool such as ours. Qualitative data, in our case, can finally be used to generate deep and meaningful insights for previously data-deprived departments such as human resources (HR) or procurement.
Chat was previously a game played by the 'big boys', but in the last couple of years, with people warming up to chatbots as a reliable medium of transaction, we have collected quality datasets that have allowed us to get into new hyperlocal languages and behaviors, such as how employees talk to their HR or legal departments differently in different countries.
Our hope is that when combined with the democratization of data science tools and the proportional increase in citizen data science skills, more organizations will derive benefits from the new insights we can acquire from prior datasets, and even more organizations will begin undertaking data journeys of their own, even in functions such as HR, accounts and legal.