Robots, Dreamy Businesses, and the Future of Work
Gavin Jackson is senior vice president and managing director EMEA at UiPath.
I recall a quote from my former boss, Jeff Bezos, who said, “Bet on dreamy businesses that have an unlimited upside. These dreamy businesses have 4 characteristics: 1) Customers love them. 2) They grow to very large sizes. 3) They have strong returns on capital. 4) They can endure for decades.”
When you look at the composite parts of Amazon, these characteristics endure and have become wildly successful, but nonetheless, they were once ‘bets.’ So, deciding to embark on a new adventure outside of Amazon is a bold bet and one that wasn’t taken lightly.
As a privilege of my job leading Amazon Web Services (AWS) in the region, I had close proximity to the challenges large enterprises and governments face in serving their customers and citizens in the manner they expect in the digital age.
I had equally close proximity to the ‘new kids on the block’ and their insurgent mentality. These newcomers are born-digital with native characteristics like a voracious appetite for harvesting value from data, a loathing of wasted capital, and time spent on undifferentiating tasks combined with an obsession to put their energy into the customer experience. In short, they have a cloud-first, ‘automation first,’ customer-first mindset.
My experience with larger enterprises and governments tells me that these characteristics are a simple articulation of what they want to achieve too, the larger organizations just call it “digital transformation.” A common tenet that customers cite for digital transformation strategy is to “use technology and platforms to remove the undifferentiated heavy lifting from humans to enable them to focus on innovating for customers.”
This is where my former team at AWS (other cloud platforms are available) had been successful over the past decade — helping customers remove the undifferentiated heavy lifting of procuring and managing technology infrastructure, so they could innovate faster for customers. The parallel I’m drawing here is that cloud platforms have helped customers free up time and accelerate innovation by helping them implement a cloud-first operating principle. But the same is true for all work, not just DevOps and IT Ops. What if you could remove undifferentiated heavy lifting of all work in all functions? How much more innovation and customer focus could we achieve?
Enter the world of intelligent automation.
According to McKinsey & Company, “Companies that deploy intelligent automation technologies can realize substantial performance gains and take the lead in their industries, even as their efforts contribute to economy-level increases in productivity.”
This speaks to every human worker in every field of work. Imagine just how innovative, data-centric, customer-centric, productive, progressive and happy we could be. Imagine the same principals applied at home, with robotic assistants managing the household administration, working on your behalf to save money, make money, file tax returns, order repeat prescriptions, or manage your communications. Work and home life could be a lot more rewarding if a company existed in the world to satisfy those needs.
So, when making my bold bet, (thanks to the Amazon culture of customer-obsession) I had the luxury of reducing the odds by really listening to customers and understanding what they really, really want. Customers of all sizes loathe waste. Companies in any industry want more of their precious human and financial capital to be dispersed in the process of innovation for their customers.
Every worker in every company and industry knows they expend several hours of work every day that is not contributing to the process of innovation or differentiating in any way, and yet we all know we must do it.
Every company seeks the path of least resistance. Increasingly, that path is led by software and data. And in every case, the path between the worker and the software and data is the user interface (UI).
And so, I have bet on UiPath.
I admit it…I’m a nerdy Marvel fan and my favorite character is Tony Stark (Iron Man). We all long for a world where we have access to an intelligent assistant that can carry the heavy lifting required to simply give us intelligence on command. A reaction to our action. Or better, a (pro)action. Tasks that get carried out where we don’t even have to ask.
If Iron Man were real in today’s technology paradigm, I can imagine Tony Stark flying over an enemy compound in his suit and commanding J.A.R.V.I.S. (the artificial intelligence computer) “give me a readout on the number of bad guys, the composition of the compound walls, and the probability of a successful mission.” Sounds compelling.
Then, I can imagine J.A.R.V.I.S. responding, “Sir, I am searching all the satellite systems and gathering the plans for the compound to determine the composition of the walls. It’s going to take a while. I need to ask the systems guys of at least 12 systems to run queries. Two of them are on vacation. One system is older than our oldest engineer and we probably shouldn’t mess with that. It’s currently number 62 in their queue. I found the drawings, but my machine learning (ML) algorithm doesn’t understand the image. So, I can’t give you any intelligence on that. As for the probability of success — I’ll get back to you.”
As incredible as this narrative sounds, it’s not too far away from real-world scenarios. Asking simple business questions does not render simple or immediate business answers. Processes are manual, systems are disparate, and data sources are plentiful. The amount of human effort in the undifferentiating part of integrating elements to get to an outcome is vast and leaves only a small amount of time for real insight and business outcomes.
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