On October 17, the National Academy of Engineering (NAE) conducted an online forum on Service Systems Engineering in the Era of Human-Centered AI. “With AI advances poised to drive service system productivity and quality - similar to the way previous generations of technology revolutionized agriculture and manufacturing productivity and quality - it is time to take stock for industry-academic-and-government stakeholders on this important topic,” wrote the NAE in its website.
The agenda included an opening keynote by retired IBM executive Nick Donofrio. It was followed by four panels on various aspects of service systems, and concluded with an open discussion of the way forward. I was a member of the panel on Evolving Engineering Education. In my prepared remarks, I reflected on the current state of service science and related sociotechnical systems. Let me share my remarks, slightly edited for clarity.
Service Science, Management and Engineering (SSME) is an initiative launched in IBM’s Almaden Research Lab in the early 2000s in partnership with a number of universities as an interdisciplinary field of study aimed at applying science, technology and innovation to the service sector of the economy. The service sector is the largest in most economies around the world. At the time, services already accounted for over 70% of GDP and jobs in advanced economies, as well as an increasing portion of the revenues of many companies, including close to 60% of IBM’s revenues.
Over the next decade, I worked closely with service science leaders, both in IBM and in the wider research community to help define this emerging discipline. I tried to explain what service science was about in seminars to academic and business audiences, and I’ve written a number of entries on the topic in my blog.
My remarks at the NAE Forum were focused on a few key questions: Why is service science such a nebulous, hard to describe topic?; what progress have we made in the twenty years since service science was first launched?; and, what are some of the major future challenges?
Despite being such a large portion of GDP and jobs around the world, the intrinsic nature of services remains vague, - hidden from view in plain sight as if they were a kind of dark matter. It’s easier to define the services sector by what it doesn’t include: it’s not agriculture or fishing, and it’s not manufacturing, construction or mining. Just about every other job is in services.
What is a service? “A service is anything sold in trade that cannot be dropped on your foot,” is one of the most succinct definitions I’ve seen, attributed to The Economist. I particularly like the practical definition of services by INSEAD professor James Teboul in his 2006 book Service is Front Stage: We’re All in Services … More or Less:
Every organization consists of front stage and back stage activities. Services deal with the front stage interactions while manufacturing and production deal with back stage operations. High quality and competitive costs are the key objectives of back stage activities, achieved through specialization, standardization and automation. People are prominent in front stage activities. Achieving a superior customer experience is one of the top objectives of such people-oriented activities, often as a collaboration between the providers and consumers of services.
I often explained what services are about by contrasting the key difference between innovation in the industrial economy of the 19th and 20th centuries and innovation in the emerging 21st century service economy.
R&D in the industrial economy was mostly focused on natural and engineered physical objects. Thanks to major advances in science and engineering over the past two centuries, we can now build highly complex physical objects like airplanes, bridges and microprocessors. While continuing to advance such work, our next challenge is to now apply R&D to market-facing, human-based organizational systems, such as companies, industries, economies, governments, and cities.
Complex physical objects consist of huge numbers of physical component that behave as designed unless something is wrong. That makes it possible to predict the overall behavior of the complex object under widely varying conditions. On the other hand, people, their assorted interactions, and the services they perform for each other are the key components of complex organizational systems. People and services exhibit a high degree of variance that makes such systems intrinsically unpredictable, and thus require new approaches to their design and operation.
Furthermore, the bulk of the R&D in the industrial sector of the economy takes place in labs and factories, and there is a significant time lag between the development of new technologies and products and their subsequent deployment in the marketplace.
Not so with services. The bulk of the innovation in services takes place in the marketplace, in a time and place much closer to where the services are deployed. It’s hard to envision an environment where new ideas for services are developed far from the actual marketplace and the individuals and organizations who consume them.
Sometime in 2016 I had an interesting conversation with analysts from an IT research organization who were preparing a report on the state of service science. They noted that we were hearing quite a bit less about service science in those days compared to 5 or 10 years earlier. Was it because we had become tired of the subject and moved on to other areas of innovation?
I told them that, in my opinion, the applications of science and engineering to services were so well accepted by now that they were no longer a topic of debate. The battle had been won. The technologies, methods and concepts once pioneered in service science were now part of a number of mainstream academic disciplines. Services were now front and center in some of the most prominent areas in computer science and IT, including AI, cloud computing, and design thinking.
For example, in their recent book Service in the AI Era, Jim Spohrer, Paul Maglio, Stephen Vargo, and Marcus Warg wrote that “Service is quickly becoming the central concept of our time, as service offerings become infused with advanced technologies like artificial intelligence (AI) and scale to new levels of quality, productivity, compliance, and sustainable innovation.
Throughout history, scientific revolutions have been launched when new tools make possible new measurements and observations, e.g., the telescope, the microscope, spectrometers, DNA sequencers. Our new big data tools have now been ushering an information-based scientific revolution, helping us extract insights from the huge amounts of data we’ve been collecting by applying tried-and-true scientific methods, that is, empirical and measurable evidence subject to testable explanations and predictions.
We’ve long been applying scientific methods in the natural sciences and engineering. But given our newfound ability to gather valuable data on almost any area of interest, we can now bring out tried-and-true scientific methods to people-centric disciplines, like the social sciences and the humanities. We can now better understand and make predictions in complex, service-oriented systems like healthcare, business organizations, government agencies and cities.
Cloud computing is another prominent example. I think of cloud computing as being essentially the Internet of Services. Data centers have now become the production plants of cloud-based services, requiring major advances in productivity and quality to be able to support the explosive demand for mass customized information and services of all kinds. Software and applications are increasingly delivered as industrial-scale online services, while the internet and wireless networks connect more and more devices to such offerings.
Finally, given that services are all about people-oriented interactions, service technologies play a major role in design thinking. It’s much easier to appreciate the role of design when it comes to physical objects: cars, bridges, buildings, dresses, shoes, jewelry, smartphones, laptops, and so on. But, it’s considerably harder to appreciate its importance when it comes to more abstract entities like services, systems, information and organizations. Yet, such service-based systems account for the bulk of the growing complexity in our daily lives. Design thinking aims to make our interactions with complex products and institutions as intuitive and appealing as possible.
Let’s conclude by remembering that we’ve been applying science, technology, and innovation to the agriculture and industrial sectors of the economy for over two hundred years, - ever since the advent of the Industrial Revolution, - while service science is just a couple of decades old. We still have much to learn on how to best apply science, technology, and innovation to our fast growing service-oriented economy.
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