Contribution of machines in performing tasks, represented by underlying technologies like big data/predictive analytics, Artificial Intelligence (AI), Robotics, Internet of Things (IoT), etc is growing and expected to accelerate. Where would this shift leave the human as job losses would be a natural outcome of this major change?
Human-machine contribution to total task hours would change from 79% vs 21%, in 2018, to 58% vs 42% respectively by 2022 according to World Economic Forum’s Future of Jobs Report 2018. According to a Bain & Company report, Foxconn China replaced 60,000 workers, which is 55% of the workforce, in a year with robots in just one factory.
COVID-19 would accelerate automation as disruption would be minimal due to less dependency on the human.
COVID-19 had relatively less impact on semiconductor fabs as the operations are highly automated with AGVs and robots.Existing jobs will be augmented with technology and new jobs will emerge creating more opportunities. Reskilling and upskilling need creates execution risk to the transition, but we need to adapt.
Two critical new-age skills needed would be innovation and active learning at all levels of an organization, more importantly at the periphery/edges.
You cannot switch on the innovation ‘button’ to make people innovate, no amount of idea generation drives, hackathons, etc will make people embrace innovation at all levels if the organization’s culture is not aligned.
Story of Shiva, a cashier at a cafeteria at Cisco office in Bangalore can be used as a case in point to demonstrate how a human performing a job that is highly susceptible to automation can survive and thrive in the future.
Strongly recommend you to go through this interesting video about Shiva created by Crestpoint Consultants with help from a few Cisco employees. Shiva speaks in Kannada but the video is subtitled in English.
Shiva serves 25 customers in 35 seconds that is 1.4 seconds per customer for cash collection, providing a receipt and tendering change!
He achieves this performance by carefully observing:
- What typically customer orders (demand pattern)?
- Typical bills produced by customers (transaction pattern).
Shiva prepares his cash counter with a set of exact changes based on his observation and keeps everything ready before his first customer comes in for lunch. He is no queuing theory expert nor does he a data scientist. I believe what makes Shiva innovate is empathy and compassion towards his customers.
Empathy towards customers and drive to act is a foundational aspect of the culture needed to create an organization that innovates and learns at all levels, more importantly at the edges comprising of foot soldiers like Shiva
Microsoft under Satya Nadella made empathy as part of the core cultural value so does LinkedIn under Jeff Weiner. I hope other organizations would seriously look into this and act.
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