Interview with Don Ong, head of innovation, Advantest at a regional automation showcase
Robotics may be known for fast, repetitive and precision work but it relies on human supervision to excel. AI and machine learning can capture data and gather intelligence from previous tasks to shorten production lines. But there is an interdependency to improve productivity and optimise business. With hyper-automation, machines can help us control operations in a much simpler way. So, will machines eventually take over one day - or will it not?
FutureCIO met with Don Ong, at a showcase on intelligent automation held in Singapore, to ask how we can embrace these developments to transform the way we work and do business. What does it mean for CIOs and how does this interlocking relationship between man and machine pave the way for new roles that humans play.
What opportunities are yet to be unlocked in the automation industry and what does it mean for us?
Don Ong: To date, our efforts have primarily concentrated on optimising internal operations – from contact centres to repair centres and logistics operations. However, with the release of a functionality module that provides a machine learning (ML) model to help streamline workload distribution, we will get better in assessing input and output data. This will determine the confidence level of the tasks assignable to two groups of inseparable workforce – digital robots and humans.
Humans may have accumulated tacit knowledge and field experience over time, but machines have the potential to be more superior at learning. With RPA being the hands and feet, and Intelligent Automation(IA) as its brain, how will the humans remain relevant?
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I envision the implementation of intelligent automation as employing a ‘Jarvis’ from the film Iron Man - or a few of them, who will act as excellent personal assistants to our employees.
This way, overall efficiency increases without the need to hire more human workers.
Firstly, is the process and task mining - humans still need to monitor the robot’s performance against manual labour. Then we evaluate how we can transfer some of those processes to the robots, what is called robotics process automation (RPA).
Secondly, as you mentioned, intelligent automation (IA) is essentially the brains of the operation. We need to add IA to the robots to build on their intelligence.
Thirdly, we need to augment the ability of the human workers.
Love it or hate it - in the grand scheme of things, robots cannot totally replace humans.
Don Ong, director and head of innovation at Advantest
Other than operating precise, repetitive work faster than humans, robots function in more ways than ever, with AI, machine learning, and other technologies. However, the strategy and direction must come from humans. I think intelligent augmentation is the way to go for now, essentially having robots complement human workers.
Film producers love to dramatise robots and machine learning overtaking human intelligence. Will this be a reality at some point?
Physicists talk about a point of singularity by 2045, which is when robots will reach human intelligence. With some scepticism, I think that at some point, robots are going to be smarter than humans.
In Asia, 70% of jobs are going to be replaced by AI, at some point. A lot of our current work can be done by both physical and software robots. Digitalisation and automation efforts are current priorities but the challenge is to tackle both areas at the same time.
Today, we’re focusing more on RPA for software automation. To us, RPA and IA solutions are business affirmation tools rather than IT integration tools that make work easier.
Programmers are wary of the source code as it could result in damages that may be time consuming to repair, so another strong benefit of RPA is that it doesn’t alter the source code. From a business perspective, business automation, software development and streamlining workflows and processes are the key priorities for us and our customers.
With RPA and IA, we could potentially tailor processes to individual customers. As a result of customised services, raising standards in customer satisfaction would give companies a competitive edge in the market.
What are some of the key industries that will embrace this?
Don Ong: While RPA was more prevalent in the financial services industry, it is not new to the market and could be applicable to all industries. From banking, hospitality, and manufacturing, as long as there are business processes in place, there is a way to automate it.
Can you comment on the adoption rate and impact of RPA amidst the pandemic?
Don Ong: There was a hiring craze for technology talent at one point during the pandemic, as it was also difficult to retain and hire foreign talents in Singapore. To this point, employing more RPA helps to plug the gaps. However, the challenge lies in how fast organisations are able to plan for it, and how well they can implement it.
In the long run, I always believe that having more human workers may not necessarily solve problems like efficiency. Having RPA as a stop-gap measure should not be a long-term plan as it will reach a point of diminishing returns.
People still have an irrational fear that humans are going to be replaced. How do you educate these people, specifically CIOs, about this?
Don Ong: There are two ways that I look at this. Firstly, we have the stakeholders who will eventually decide if we are getting the budget for RPA – strategically positioning it in the right way is very important. This is why I believe that to make it happen, you need to sell it to the business owners.
Convincing the IT department may likely fail because it would be more efficient to run the script codes as per normal. But if you look at it from a business automation perspective, RPA will have a different value. Technological progress is inevitable but as a business, we need to look at the bigger picture, and park investments where it matters.
There are anxieties about this love-hate relationship between man and machine. Personally, the value lies in shifting the fear to love and a form of excitement, by positioning the technology integration as a good thing. We must assure the workforce that their jobs are intact. Essentially, they would all be like Iron Man buddying up with their own Jarvis. An open communication with everyone is important, especially empathy and transparency when people are insecure about their jobs.
How does innovation plays a part in the future of automation in Singapore or Asia Pacific? Would you say microelectronics is an example of how innovation has played such a key role?
Don Ong: Technology is ever evolving, and this is very true in the semiconductor industry. We are always looking to innovate in the field of micro-electronics, which are dependent on semiconductor materials. It’s about how we apply technology especially when we have similar tools and resources on hand, with further research and development. Ultimately, technology application can determine the success or failure of this business function.
Working with our customers on innovative technology applications enable us to address some of their biggest concerns. For example, the patented A.I. solution, adaptive probe card cleaning, helps our customers improve their yield and manufacturing costs.
Which organisations that you engage with are perhaps more resistant to transform?
Don Ong: Process automation is an area in which we are ramping up efforts in both AI and ML, focusing more attention on our ESG activities and developing an aggressive ESG plan.
While our customers are mostly related to the semiconductor industry, we find that traditional industries find it more difficult to break into new or emerging technologies like RPA and IA. Indeed, Covid-19 has accelerated the speed of automation adoption, especially with a “make or break” mindset that came along with the massive changes during the initial months of the pandemic.
Can you share some insights as to how close we are to reaching the dream of virtualizing, digitising processes and hyper-automating everything?
Don Ong: In a survey, conducted by Singapore Business Federation, found that Singapore recorded a higher proportion of businesses adopting new technologies over the past year than other countries in the APAC region. Furthermore, the survey found that about 70% of high growth businesses in Singapore plan to invest in data analytics and visualisation software. This is important to recognise as we have always been at the forefront of technology adoption.
Generally, industries in Singapore and Asia have been at the forefront of adopting advancements such as IA, AI / ML and other emerging technologies. It is important to stay ahead and become a model for shaping the future of technological growth. However, being one of the first also means you face a lot more challenges than those who may adopt the technologies and embrace IA later.
Would you consider Singapore being at the front of the race?
Don Ong: The Singapore government has been focusing a lot on digitization and automation. The more digitization and automation we implement; the more people and organisations are empowered to make more accurate and efficient decisions. This enables the customisation of products and services which will in turn give Singapore the competitive edge.
With so many players in IA driving innovation, how does Advantest differentiate itself from others?
With cloud solutions, we are doing more AI / ML through an open ecosystem. We partner with different partners to provide the latest technology platform to customers.
What are the ongoing collaborations for industry talent and attraction?
Don Ong: Recruiting the right talent is a worldwide issue today, especially for the semiconductor industry and was actually one of the key topics of discussions at SEMICON Southeast Asia 2022 held recently. Hence, we’re focusing more on training new talent for this industry – even some that are fresh out of school.
We shared some sanitised data with students so that they can build machine learning models and add value to the semiconductor ecosystem. The programme allows us to improve our platform while providing the students real-life examples in their education journey.
Recently, the collaboration with the Singapore Polytechnic saw the setting up of a testing centre. This is aimed at nurturing an adaptable talent pipeline for the semiconductor industry in Singapore.
What do you see in terms of the challenges in the next five or 10 years?
Don Ong: It is more about how we continue down this path of innovation and how we actually apply all the different technology that's available. Application and execution mean the difference between success and failure, or whether you get high returns. We face the same challenges as everyone else but in the end, it is how we apply technology and get ahead of the race that will make a difference.
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