Big Data

Our Inhibitions Against AI, Big Data Are Disappearing

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We have been talking about big data and AI for more than a decade. While adoption rates have steadily increased, many projects — especially in AI — were left listless in the proof-of-concept stages. The overarching argument was there was no justifiable use case to overhaul an infrastructure that isn’t broken. The other argument is that the market or company is not ready. 

COVID-19 eliminated these reasons. Companies now need big data-based insights to navigate a fast-evolving market landscape. AI can help companies to scale fast while maximizing the productivity of their overloaded remote workforce.

At a recent roundtable titled “How COVID-19 has pushed the importance of big data and AI,” Céline Heissat Le Cotonnec, chief data innovation officer at Bank of Singapore said it best: “[COVID-19 has shown that] digitalization is one of the few means to connect with people, so we need to rethink.”

Data-driven reset

The new mantra in town is reset. “We need to reimagine and reset and reinvent with big data,” said Rachel Ooi, managing director for Industry X.0, Accenture (Growth Markets) who moderated the discussion. 

But AI and big data will not help you overnight. Klaus Mueller, chief operating officer for Asia Pacific at Schaeffler observed that big data and AI also take time. Many companies overlook this, leading to failures and missed expectations. “It is not a short-term effort.” Instead, it is an investment. 

However, COVID-19 has gotten companies to explore new use cases fast. “It is a stress test of our dynamic systems, and a catalyst to sharpen our ideas of use cases,” said Mueller. The days of constant experimentation and wondering whether we are ready for the technology is over. 

Companies are also crystal clear about what they want these technologies to do. Pranav Bhanage, chief executive officer, India and South Asia Region, Petronas Lubricants noted that the current pandemic has driven companies to focus on cost savings and working capital. Not just for staying afloat, but to recalibrate their business models to be resilient to future shocks. AI and big data projects that can help companies achieve these will be attractive.  

“The whole concept of getting people out of the house has driven consumerism. We have now gone back to the 1900s where you do not get out of the house much. So, this is a unique opportunity to create something more sustainable,” said Bhanage. 

The split workforce

Market landscapes were not the only thing that drastically changed with COVID-19. Organizational structures have as well. 

“[COVID-19] has broken the organization into two halves: one that can work from home, and the other that needs to be at the workplace. We never looked at [an organization] in that way before,” said Bhanage.

This division makes it difficult to manage a workforce. Old management styles that saw managers supervising their workforce in the field or at work are no longer possible. Decisions based on discussions with people in a boardroom where one can observe non-verbal communications are now a thing of the past.

“So, we need all the human elements of a decision to be translated using data,” said Bhanage. This is where AI and big data analytics comes in.

However, the problem is skill sets. All staff and senior management, from the field worker to the board room director, need to get comfortable with these technologies.

For Heissat Le Cotonnec, it can be done and is a matter of a mindset shift. She noted that this shift in mindsets is already occurring within the financial services industry, and with the regulators.

“Now we have the [Monetary Authority of Singapore] telling us we need to open our systems. We would never have reached this in ‘normal’ [times],” she said.

Second life

The market is already filled with AI and big data innovations, driven by startups. The problem is that while the technology was ready, the market was not.

COVID-19 is changing this fast. For example, in engineering related industries Mueller saw renewed interest in predictive maintenance based on big data. Before it was seen as a competitive edge, but today it is about freeing the workforce to add more value to the organization and keeping them safe, while maintaining a high level of customer experience.

The emergence of telemedicine is another example. “The technology was ready, but the regulations and the lobby were another issue. We can say that the society was not ready,” Heissat Le Cotonnec said, adding that the business model of hospitals was often designed to get patients to return for doctor consultations.

Now, with COVID-19 restrictions, this is not possible. “So, telemedicine breaks through. But it has been there for some time,” she said.

As COVID-19 drags on, look out for past AI and big data-driven innovations getting a second lease on life.