National Center for The Middle Market | Blending Human + Machine
Co-Authors Paul Daugherty and Jim Wilson Describe How AI Will Change the Way We Work
Paul Daugherty and Jim Wilson, co-authors of Human + Machine: Reimagining Work in the Age of AI and executives at global consulting firm Accenture, may know more about artificial intelligence (AI) and how it applies to the business world than anybody else in the world. Their timely book is an eye-opening, thought-provoking, and accessible analysis of how AI is changing the way all companies do business today and tomorrow. The NCMM spoke with both authors recently by phone, discussing the massive impact AI will be having on middle market companies in particular.
What tasks are machines/AI well suited to performing, and what tasks will remain in the hands of humans?
Paul Daugherty: The research says that humans are really good at innovating, leading other people, at creating, at judging, at emphasizing broad areas of improvisation when it comes to common sense. Machines, on the other hand, are really good at narrower modes of thought and action, such as data crunching or adapting based on pattern recognition from data. What is missing from the AI conversation are the collaborative tasks where humans help machines and machines help humans. We call this blended space “the missing middle” in our book.
There are six repeatable roles where people and machines collaborate and perform tasks. These are not only tasks but also whole new job categories. For example, one new job is called “international road course tester”: a person who works for Daimler goes around to different regions in the world and trains autonomous vehicles about why driving rules are different in different places parts of the world.
What kind of process transformation should Middle Market company leaders be making now to accommodate this “blended” future of AI?
Paul Daugherty: We talk in the book about”the third wave” of process transformation. We’re moving from automating the physical labor of last century to re-engineering, which was about the knowledge worker. Over the last 20 years, this new concept of re-imagining the way you do business and re-imagining business processes has emerged, and that’s the third wave we’re now in.
So middle market companies need to look at it how they can re-think and transform the way they do business, using the unique characteristics of artificial intelligence. The book explains five characteristics needed to re-imagine processes for this third wave. The five are are speed. You’ve got to leverage AI to do things faster. Flexibility, to get more agile with processes. Scale, to go from individual processes to serving lots of customers quickly. Decisions at the edge which is pushing decision-making to the employees at the organization’s edge, so being more efficient and more responsive in real time. Then finally personalizing the processes. Those are the kinds of changes that will allow middle market companies to differentiate themselves from their competitors and do things in new ways, rather than just adding a little bit of AI or predictive analytics and trying to slightly improve.
How can middle market companies create the foundation to make these necessary changes you’re describing?
Jim Wilson: In the book we describe five core principles that follow the acronym M-E-L-D-S. So M is for the “mindset” to reimagine the business, then E is “experimentation,” R is responsible “leadership,” D is the “data” and data supply chain, and finally S is new “skills.” I’ll just mention the first principle: it’s so important to have the mindset to re-imagine work and processes around human and machine collaboration. Companies that focus on collaboration rather than simply automating old processes, can create two to six times better outcomes than those just focused on either human or machine. It’s not either/or. It’s getting the best from both.
Can you offer a real-world example of this blending of human and machine?
Jim Wilson: Look at GE Predix, the digital twin concept for predictive maintenance of industrial equipment. Basically, a technician used to have to go to the equipment with a checklist to maintain it. Contrast that to the re-imagined way with the digital twin where a technician interacts with an AI-enabled virtual model of the equipment. Because of the internet of things and sensor technology, that technician can see the real-time characteristics of the equipment at all times, and can make decisions in real time about what to do to maintain it.
You’re going from a tedious, checklist-driven, inefficient process to a real-time process that’s personalized to the piece of equipment. The technician can make significant business decisions in real-time guided by information in a much more effective, responsive, and more rapid manner. That’s a good example that encapsulates a lot of the benefits we see in this new, blended way of operating.
How is AI changing other business areas, like warehouse management and supply chain management?
Paul Daugherty: When it comes to warehouse and distribution centers, there’s been a tremendous impact from physical robots that the public is very familiar with. Robots zoom around doing a variety of things, stocking and picking and such. The even bigger impact is when you start applying other layers of artificial intelligence. Maybe how to use video analytics when you receive returned goods and then can quickly understand exactly what to do with those returned goods.
Think about logistics operations having much better predictive information on the nature of your demand and your stock, in order to link up with all the sources and suppliers you have to ensure you’re really optimizing your whole supply chain. AI gives middle market companies a vast amount of data and offers much better solutions to both predict and better operate their supply chain networks.
So when middle market company leaders examine their own business processes, how might they identify the “low hanging fruit” that’s ripe for picking in terms of implementing or using AI?
Jim Wilson: t’s a process whereby you’re feeling for pain points in any of those areas Paul mentioned earlier: flexibility, speed, scale, decision making and personalization. For example, one consumer products manufacturer we know was able to re-imagine it’s recruiting process and get unprecedented levels of scale that it hadn’t been able to achieve before. This company brought AI into the interviewing process to perform the first couple of rounds of interviews, using facial and voice analysis. For an interview candidate, it was almost like doing a Skype call, only with a robot asking the questions.
Then for those later rounds of interviews, human recruiters would take over, leveraging human judgment to get a better feel for a candidate’s cultural fit. As a result of that human and machine collaboration, the company was able to double their number of job candidates and triple the number of schools they were able to recruit from. They speeded up the time to hire from four months down to four weeks. Really incredible results in a core strategic area.
What will differentiate the winners and the losers in this new “blended” world you’re describing?
Paul Daugherty: There are three areas middle market company leaders should keep in mind: innovation, people and trust. If I had just one area to invest in AI, I’d say invest in people, because people are going to be what gives you the innovation. People are essential in driving your business and in “partnering” with AI. Of course, investing in the technology is critical. Then the third point is trust, build trust in your employees, trust with your consumers, trust with your regulators: Getting those human things right is essential for adapting to the emergence of AI.