ALERT AND AGILE TOWARDS DISRUPTIVE TECHNOLOGY
Compiled by: Lee Sin Poh
Tan Tong Hai
Dr Raj Thampuran
Managing Director, A*STAR
CEO, Courts Asia
“Small is beautiful.”
This phrase sums up what Tan Tong Hai thinks local SMEs could appreciate – they might not be in possession of many assets, but this is not totally a downside, as assets may become a burden or liability. Around the world, innovations are also less about possessing assets, but using others’ assets for their purposes, such as the cases in Whatsapp, WeChat and Airbnb. The world has somehow become more “software-defined”, he said, where players of all sizes have been put on a level playing field.
“生于忧患，死于安乐” – one thrives in hardship and prishes in comfort. He quoted this Chinese saying and encouraged local SMEs to go beyond conventional ways of doing business, and embrace disruptions instead of turning a deaf ear to them. Tapping on available technologies, SMEs can take these steps: engage customers with digital technology, attract customers through omni-channel marketing approach, analyse customer behaviour through data partnership ecosystem, and optimise by digitally transforming their backend with Mobility and Cloud.
“As an open economy, fastpaced industrial evolution is a consequence of rapid changes in technological trends.”
Who could have imagined disruptive technologies like Internet of Things (IoT), big data analytics, smart robotics and adaptive automation, 3D additive manufacturing and zero-waste remanufacturing would eventually dominate today’s change?
Dr Raj Thampuran explained how these technologies would influence future industrial transformations. For instance, the healthcare industry is now focusing more on disease prevention with predictive
information, and treatment will become more personalised using the individual’s genetic information. Besides, the future of manufacturing
will not only be about making physical products, but also to add value by focusing on personalisation and customisation of products, as well as developing customer service capacity. In view of these shifts,
A*STAR also collaborates with government agencies like EDB and SPRING to help keep Singapore abreast with developments in manufacturing.
“Put your resources where it matters.”
Sound advice indeed from Terry for retailers who always face the need to change. He thus shared his observation on contemporary customer behaviour and preferences – what they like and don’t. As shown by analysis, they are most afraid of long lines and traffic; and the top in-store features that increase the likelihood of purchase are “knowledgeable sales associates” and “selfservice/ mobile checkouts”. They are also now more empowered with research ability, and want retailers to make products easier to choose.
Noting these changes in customer behaviour, Courts Asia adapted accordingly. It adopts an integrated “bricks and clicks” model – gaining both online and offline presence and enabling the click-and-collect experience; adopts category management model in store, with the belief that not all products are equal, and touch and feel still counts; provides specialised services such as repair service and trade-in bar; and ensures sale associates on the frontline are knowledgeable and approachable.
“Solve a real problem; be hyperlocal.”
Founded in Malaysia, Grab started with the vision to provide better safety assurance, as taxi users there were anxious about the misconduct of drivers. Subsequently, while expanding to Singapore, Grab discovers that call centres are hardly accessible during
peak hours, and so it rides on its edge of promising better certainty. Last but not least, in view of Jakarta’s heavy traffic conditions, where motorcycles are even more efficient than cars, Grabbike was introduced.
Grab is really focused and localised in its approach to solving problems in different landscapes. Currently the largest homegrown tech company in Southeast Asia, Grab runs its business within only 6 countries in the region, and will continue to seek improvements
here rather than expanding to other regions, according to Kell Jay. Currently, he is targeting higher efficiency by adopting data analytics, through which he expects to enable Grab to predict demand from passengers so as to allocate supply of drivers accordingly. He expects to shorten waiting time from 5 to 3 minutes when the technology is optimised.