Nobody enjoys performing monotonous transactional tasks, and we all want intelligent robots to do them for us.
MEDIA 7: You are a firm believer that intelligent automation could bring about the next industrial revolution. Could you please tell us a little bit about this?
PASCAL BORNET: We have been through two automation revolutions in the past. The first automation revolution was agricultural, where horses and mechanical infrastructure such as tractors replaced manual labor. Shortly after came the industrial revolution, where robots were introduced to manufacturing plants for cheaper and faster production processes. And now there is a new revolution - a new automation revolution - which is the one of intelligence: Industry 4.0.
Today, 80% of the workforce are called knowledge workers, who are people like you and me, creating value with our brains and intelligence. This new revolution is about automating this intelligence. For instance, everyday tasks such as logistics, copying and pasting information, sending emails, entering data from paper invoiced into a computer, and others, are repetitive activities that no one likes to do. When intelligent robots perform these tasks instead of us, it leaves us with the time to focus on more value-added activities such as building relationships with our teammates, clients, and suppliers, ideating and creating strategies and practicing critical thinking. Yes, this is the new automation revolution, and it is different. Most workforces are now using intelligence to create value. Knowledge workers are now depending on intelligent Automation to make their work more exciting and the world of work a thriving environment.
M7: Intelligent Automation is still relatively new in the market today, and there's a lot of excitement around this topic. Thanks to you, we now have the first guidebook on the subject, "Intelligent Automation – Learn How to Harness Artificial Intelligence to Boost Business and Make Our World More Human." Could you please give us a little preview of this book?
PB: I have worked with firms such as EY and McKinsey, helping build their Intelligent Automation practices. I have also worked with several corporate clients, helping them design and implement their Intelligent Automation transformation. Throughout my work, I was asked the same set of questions repeatedly:
What is Intelligent Automation?
What benefits can I get from IA?
Where should I start with my IA transformation?
What use cases do we have?
What are the leading practices?
How to make sure that I succeed in such a transformation?
What is the highest impact for me?
There were a lot of misconceptions as well, such as robots taking my job and managers and c-level executives saying, "Oh, I'm just going to buy technology, robotic process automation, or machine learning platform and everything will work. The vendor tells me there is no or limited training required. So I buy it and buy licenses and, and I'm done."
Miscommunication and the need for more information and education are why I wrote this book with Ian Barkin, founder of the first consulting company in Intelligent Automation, Symphony, and Jochen Wirtz, a professor of service marketing at the National University of Singapore. Service marketing is one industry that uses the most of IA.
There are four main parts of the book. The first part talks about the premise of intelligent Automation. Here, we talk about why our world needs Intelligent Automation-
IA can impact productivity, improving its efficiency by 20% to 60%.
IA can bring better products and services faster and cheaper to clients.
Improves employee experience
Our research has identified that one-third of the transactional and predictable activities performed by knowledge workers can be automated. The remaining third of the tasks can be augmented by technology.
However, scheduling meetings and emails are some tasks that can be tedious, and we often don't do them too well simply because we are human and no one taught us to do them well. The way to solve this is by using virtual assistance or a virtual coach that can help us make sure that we make the best use of our time—for instance, not inviting people who are not necessary for a meeting.
I think of a doctor who can recognize a tumor quickly by looking at an x-ray. It's like becoming superhumans with the superpower to identify and analyze millions of data in just a few seconds and getting key trends and insights from it as we do with machine learning.
Intelligent Automation can also save lives by helping speed up clinical trials and supporting patient relationships with research. As a result, IA has the power to save more than 10 million lives every year. It can also help you save money by allocating it better. For example, trillions of dollars are lost on frauds and accidents. IA can help avoid these situations.
IA also helps reduce human error ultimately. You can also monitor what the technology has done and when. IA can also double our global budget for health and education. The second part of the book talks about the framework for Intelligent Automation and how to build it. Here, we talk about four key capabilities:
Thinking and learning
By combining those different capabilities supported by technology, you can automate the most complex use cases. The third section explains critical success factors, typical challenges in IA transformations, and leading practices for a successful transformation.
The last part of the book is about societal impacts of IA. We talk about job losses and job opportunities and explain why job losses will not be the case. We present how to make sure that this doesn't happen by reviewing the way we educate our kids, focusing on those competencies that technology can't reach for them at the moment. Think here of creativity and critical thinking relationship. Another imperative is sharing the wealth created by these technologies. Economists have found out that the additional wealth created by this technology is not shared equally among the people, and our view is that we can't leave people behind with evolutions. It is essential to share this wealth equally with everyone for this to progress.
The main difficulty that most businesses are dealing with nowadays is scaling transformations.
M7: What are some of the biggest challenges involved with IA transformations? How can businesses overcome them?
PB: More than 50% of companies worldwide have started their IAA journey already, but according to Deloitte, only 15% of them have been able to scale. I have been able to implement IA transformations across more than two or three functions or divisions. The biggest issue that most companies face today is scaling these transformations.
To scale these transformations, we've identified five critical initiatives for companies. The first one is about putting your people in the center of an IA transformation because IA is by people for people. So education, change management, information, incentivization and empowerment must be implemented to ensure that your people are in the center. I mean, the transformation cannot work without the people.
The second is about ensuring management sponsorship because these transformations bring structural changes to the company. The changes touch upon the organization, the processes, and the current IT landscape and often require financial and resource investment. I've never seen a company succeed in such a transformation without having a key sponsor from the management.
The third is about combining different capabilities or IAA technologies to create synergies to automate the most complex end-to-end processes. Unfortunately, many companies limit their transformations to a single function or activity, or on an isolated technology like robotic process automation or machine learning, instead of having a broader vision for an end-to-end process transformation. By combining these different technologies, we can create synergies to increase impact.
The fourth is about democratizing Intelligent Automation by getting some low-code technologies that let everyone in the company participate in implementing Intelligent Automation because those specific technologies don't require any skills in coding or programming. These are user-friendly technologies with drag and drop features that most people can use.
As more people in the company participate in the implementation, the faster and broader you will move. But the essential part, in my view, is the futuristic mindset that these transformations enable in everyone in the company, which has the power to make them improve their work environment. It empowers them and gives them a role in the transformation, making them actors in it, thereby changing the company's mindset towards more automation and digitalization.
The fifth is to leverage technologies that help to implement IA faster. It's actually very ironic because most digital transformations today are highly manual and human resource intensive. So here it's about using technology to help us implement these transformations faster. And those technologies, for example, machine learning, allow data scientists to build models more quickly through process discovery or process mining that helps identify use cases to be automated. All these technologies have increased the speed and scope of a transformation by 20 – 50 percent, based on my experience.
Most of the digital transformations today are extremely manual and human resource intensive.
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M7: Could you please share with our readers a use case of an IA transformation that you headed?
PB: One process that all companies accomplish is a process that we call procure to pay, which is about buying goods or services from suppliers, receiving, and paying them. It is an end-to-end process. So we start with the selection of vendors based on historical data of the performance of these vendors, and for these, we often use machine learning.
And very often here, we leverage some workflow platforms that will help route the purchase orders internally in the company to get the proper approvals before sending them to vendors. Then we receive and process the invoices from the vendors, and here, we use natural language processing. If those invoices arrive in paper or PDF, we have to extract the correct information from those invoices and then process them into transactional systems.
And finally, it is time to pay the vendors. Again, this is a very transactional, repetitive task that can be automated using, for example, using robotic process automation. That's why you're seeing the end-to-end process get wholly automated using various technologies working together. So at the end of the day, you can automate 95% of such a process, and the remaining 5% are exceptions. So, for example, if you received an invoice in Japanese and didn't have the necessary technology to support this, you'll need someone for the task.