Anna Choi is the Head of Digitalisation, Asia Pacific at Schindler Group. Having driven digital transformation for multinationals, she is experienced in setting digital strategy, and harnessing the power of IoT and AI to define future of business with a focus on customer experience. She has also been recognised with several leadership awards in the digital field and featured in TED talk, startup events and various global tech conferences.
Can you tell us about your career progression into your current role?
I was trained as a scientist, then I started off working as a business generalist across different functions and gradually developed my domain know-hows on Smart City Technology, in particular automation and digitalisation for smart infrastructure, integrated mobility, energy efficiency and smart healthcare. I am currently the Head of Digitalisation for Asia Pacific at Schindler Group, looking after 16 markets across APAC.
Can you tell us a bit more about Schindler Group and your particular role?
Schindler Group is one of the world’s leading providers of elevators, escalators, and moving walks, alongside maintenance and modernisation services for these products. The Group has over 1,000 branch offices in more than 100 countries, with production sites and R&D facilities in the US, Brazil, Europe, China and India.
As the Head of Digitalisation, my responsibilities include digitalising our services, bringing in innovative digital products and leveraging technology to advance the whole value chain of installation, maintenance, repair and modernisation. I also look into business processes and cross-functional operations and bring in new technologies to add value and increase employee engagement.
How is your company utilising Artificial Intelligence and what real-world problems is it solving?
One of the use cases is to connect assets (elevators and escalators) with IoT devices, define different parameters, monitor them and apply AI for predictive maintenance - bringing tangible values to customers.
Let’s say if we could collect forty million messages per day with more than ten thousand symptoms, such data from a globally connected portfolio would be a good basis for our data scientists to focus on. They can build algorithms to look into patterns and insights, and together with our inhouse knowledge and technical expertise, help us detect and predict anomalies, in turn making traditional services adaptive and enabling predictive maintenance.
By doing so, we’re reducing downtime and allowing data-driven decisions to be made, ultimately enhancing customer experience and overall satisfaction.
What is the biggest challenge you have faced with data in your current role?
We are very fortunate to have started looking into data many years ago and have created different systems and platforms to enable data to flow from one source of origin into the big data lake.
The biggest challenge is racing against time, more specifically how we can leverage the data we have and apply it to different use cases at speed. The data pool we have is enormous, so identifying our priorities and what use cases to focus on then becomes a big challenge. With plenty of exciting times ahead, we’ll have to be fast enough to adapt and make use of our data to create impacts.
Working across 16 different markets, have you noticed any similarities or differences between them in terms of understanding the value of data and data readiness?
Many markets in Asia Pacific understand the value of data, most likely because our customers are also undergoing digital transformation themselves – be it automating their ERP systems, or synchronising, harmonising and neutralising their platforms to centralise data from data warehouses into data lakes and apply in various business scenarios.
Singapore and Hong Kong markets are particularly advanced in this aspect. Many organisations see it as a necessity to review their long-term data strategy, reconsidering what it means by data collection, storage and advanced analytics, as well as figuring out how data can be utilised in different corporate functions and business scenarios. Not to mention, some key areas like cybersecurity and data protection are imperative when growing data pools and adopting advanced analytics.
What do you think would be the next frontier for digital transformation in IoT/Smart City projects?
This is constantly discussed, and industries already reached a certain level of maturity on the product side, with embedded systems, wireless sensor networks, home & building automation, etc.
What’s next would be the move from planning to implementation, from piloting to scaling up for multiple sites, cities and countries. It is the time to realise the business impacts it can bring in terms of productivity, efficiency and new values creation.
Organisations will have to consider the qualitative (customer satisfaction, customer/user engagement, new value creation) and quantitative (productivity, efficiency, ROI) business impacts at scale, which us technology providers will have to evaluate and demonstrate.
What advice would you give to companies looking to invest in Artificial Intelligence and data?
Having helped three multinational companies drive digital transformation, I’ve noticed it’s not always about the tech, but much rather the people. Having people who are passionate and who can communicate the ideas across to stakeholders truly makes all the difference. It’s also important to have the right mindset, to stay open-minded and allow the team to innovate and collaborate and for the culture to thrive. Last but not least, having engagement and commitment from the top management will help drive AI and data implementation within companies.
Looking to the future, how do you see Artificial Intelligence/digital disruption realised in cities?
It’s a topic close to my heart and I’d love to see different technologies play a role in connecting communities and cities. There’s a lot of technology out there already, what it comes down to is how we can connect all these modular technologies to create a bigger impact. I envision that cities would be well-connected in the future when AI adoption matures.
It’s forecasted that 68% of the population will be living in urban areas by 2050, a likely result from digitalisation with AI playing a significant role in:
reducing carbon emission
creating clean and renewable energy and sharing through smart grid
providing clean water supply and a better leakage detection
alleviating traffic congestion with autonomous vehicle, smart parking and connected mobility
improving waste management
providing smart and affordable healthcare e.g. using robots as companions and in training Alzheimer patients, AI aided medical diagnosis
leading to higher transparency in data and information for citizens to make better informed decisions
blossoming of new and diversified industries