Service Science: The New Essential in Business

• Business education remains largely based on a product-centric, industrial-era mindset, even though services, not products, now dominate the global economy.
• Service science is based on fundamentally different managerial logic than manufacturing science, emphasizing value co-creation, adaptive systems, and often technologically mediated customer experiences.
• Integrating this mindset into business curricula, in ways that reflect the reality of today’s economy, requires schools to rethink course content, pedagogical methods, faculty roles, and institutional support.

 
Business schools were shaped by the manufacturing economy of the late 19th and early 20th centuries, with curricula built around physical goods, efficiency, and linear value chains. Much of that industrial logic still defines business education today, even though the world our graduates enter has changed fundamentally.

Across nearly every region, value creation and employment are now driven primarily by the delivery of services rather than the production of goods. Advances in data, analytics, artificial intelligence (AI), and digital platforms are transforming how services are designed, delivered, and experienced. In what is often described as the Cognitive Age, value increasingly emerges from the design and orchestration of systems that integrate people, processes, data, and smart computers.

Such orchestration gives rise to what is often called collaborative intelligence. How well our students understand this concept will depend on how well we prepare them to lead in an economy transformed by technology.

Why Service Science—and Why Now?

I base this argument on two emerging trends in today’s global workforce.

The rise of the service economy. The economic evidence for this trend is clear. World Bank data show that services now account for more than 60 percent of global gross domestic product—and nearly 70 percent in high-income economies.

Labor trends mirror this shift. According to the International Labour Organization, services employ more than half of the global workforce and more than 70 percent in advanced economies.

The misalignment between this reality and most business curricula became clear to me when I began teaching Operations Management in our MBA program at the University of Washington’s Milgard School of Business in Tacoma. All my students were employed in service organizations, in sectors such as healthcare, finance, logistics, retail, public, and information technology (IT). Yet, in prior years, the course had relied on a traditional operations textbook built largely around product-centric topics such as manufacturing strategy, new product development, facility layout, warehousing, inventory, transportation, scheduling, supply chains, and waterfall project management.

This experience reinforced what I have observed through more than two decades of research and industry engagement: Service thinking differs fundamentally from product thinking, in that the managerial mindset must necessarily shift from a linear “make, market, sell, and deliver” logic to a cyclical “listen, learn, design, make, and adapt” approach. For managers with this mindset, value is co-created through interaction rather than transferred through output.

Organizations need talent with the capabilities to understand customer needs, articulate user stories, design customer journeys, and manage value co-creation across human and technological actors.

Transformation through digital technologies. The second trend is that much of today’s economic activity is being increasingly mediated, orchestrated, and scaled through IT, AI, cloud computing, data management, analytics, and connected platforms.

Banking, for instance, is now experienced through digital interfaces and real-time decision engines. Healthcare relies on analytics to manage patient flow and predict risk. Retail, logistics, transportation, education, hospitality, and entertainment operate through platforms that blend human and algorithmic inputs.

These changes reflect a deeper shift in customer expectations and innovation logic. The economy has moved from selling products to solving problems. Customers seek outcomes, personalization, and ongoing engagement rather than one-time transactions.

In fact, in many industries, the first “product” customers encounter is a digital service layer delivered through software. This layer often augments or replaces a physical offering, adopting what is called service-dominant logic. As this trend strengthens, organizations need talent with the capabilities to understand customer needs, articulate user stories, design customer journeys, and manage value co-creation across human and technological actors.

Filling the Educational Gap

These trends led me to develop a new course, Service Operations Management. Perhaps not surprisingly, as I planned the course’s content, I encountered a clear gap in available teaching resources: Only two textbooks on the field existed, both outdated.

I decided to forgo using static textbooks, instead building the course around relevant contemporary case studies and research. This approach allows the curriculum to evolve with industry practice and prepares students to work in digital, data-driven environments.

The course follows this general trajectory:

An introduction to a new way of thinking. I begin the course by establishing how services differ fundamentally from products. Early on, students learn to view services as complex adaptive systems shaped by interactions among people, processes, technologies, and shared information.

We discuss core characteristics such as intangibility, perishability, and the inseparability of production and consumption. This discussion provides the conceptual foundation for understanding why traditional product-centric frameworks often fail in service contexts.

An examination of strategic vision and design. Next, students explore how organizations articulate value through tools such as the value proposition canvas. In addition, they learn the importance of understanding customer needs and pains, as well as how interactions between value shops, value chains, and value networks help organizations deliver services at time, space, and scale.

At this stage, I also introduce methods such as service blueprinting. Here, my objective is to help students visualize front-stage and back-stage processes and align operational decisions with customer experience, including managing operational bottlenecks on multi-market platforms.

Students learn to assess trade-offs between automation and human involvement and to create processes that are scalable, resilient, explainable, adaptable, and customizable.

Hands-on practice in areas such as quality, pricing, and demand management. Students practice using the survey tool SERVQUAL, explore value-based pricing strategies that account for capacity constraints and demand variability, and learn approaches to forecasting and demand management based on different service levels. They also use data collection methods, analytics, and smart machines to reshape interactions, decision-making processes, and customer expectations.

As they do this work, they assess trade-offs between automation and human involvement from operational, ethical, and experiential perspectives. Finally, they learn to create processes that are scalable, resilient, explainable, adaptable, and customizable, even under uncertain circumstances.

Learning to Co-Create Processes

In my course, students are introduced to the idea of value co-creation. That value emerges from interactions between providers and recipients; it is not merely embedded in outputs. Design science complements this perspective by placing customer experience at the center of innovation. Students analyze customer journeys, use cases, and rapidly changing customer pains and gains to design services that deliver meaningful outcomes.

To translate theory into practice, I assign a hands-on project in which students conduct an audit of a local organization to design a new or improved service offering. The project gives them practical experience applying frameworks and templates while working with real constraints that affect actual stakeholders.

Students consistently report that this project changes how they see organizations, because they learn that operational efficiency alone does not guarantee success. Adoption, trust, and experience matter just as much.

I have seen similar mindset shifts in undergraduate and graduate courses that I developed in management, accounting, marketing, supply chain, and IT. Students learn to prioritize customer needs and adoption, as well as respond to dynamic changes in customer usage.

As they do, they come to realize that a technically flawless system still fails if users do not integrate it into their work or daily lives.

A related insight emerged when I taught a project management course in our Online MBA program. The course was originally built around waterfall methodologies for product development. I redesigned the course to focus on service design and delivery, integrating agile project management with customer-experience-driven product management practices.

The redesigned course emphasizes that even in roles that focus on project management, the work increasingly centers on understanding business needs, customer expectations, user stories, design thinking, and value co-creation across cross-functional teams. Students recognize that modern product management is fundamentally a form of service leadership.

Developing ‘T-Shaped’ Analytical Thinkers

To help students develop as analytical thinkers and innovators who can adapt to ambiguity, I deliberately structured the project management course to include hands-on projects with organizations. For example, one assignment requires students to create a “knowledge object,” which is a structured tutorial designed to teach others a specific concept or practice. This reinforces the idea that learning deepens through teaching and reflection.

To support this work, I incorporated open educational resources from nonprofit professional organizations such as the International Society of Service Innovation Professionals (ISSIP) and the Linux Foundation. These entities provide timely, practice-oriented materials on emerging technologies and innovation.

I have observed the gap that my class and these resources are designed to fill in industry. Many IT organizations employ “IT product managers” who are responsible for defining strategy and designing roadmaps for technology-enabled services. These professionals are often graduates of MBA, marketing, or management programs who have limited exposure to service science, design science, or deep technical systems thinking. As a result, they frequently rely on traditional product lifecycle models that struggle in dynamic, service-intensive environments. In my view, this mismatch contributes directly to high rates of IT project and technology adoption failure.

As AI moves organizations toward greater automation and augmentation, success depends not only on our graduates understanding how to apply new technology, but also on their ability to shift their mindsets and behaviors in ways that align with today’s markets. This transformation is a journey that requires building academic communities capable of supporting change.

Managers and leaders need to know how to ensure that algorithmic decisions stay fair, transparent, and accountable.

Individuals who thrive in these communities are those who can combine analytical rigor with empathy, curiosity, and a willingness to collaborate. They are entrepreneurial, growth-oriented problem-solvers and digital workers who learn quickly from failure and seek opportunities in uncertainty. I refer to these individuals as T-shaped analytical thinkers and adaptive innovators. Cultivating their capabilities has become a central objective of my teaching.

Most competencies that define service science are managerial and ethical. As AI and data-driven systems become embedded in front-stage and back-stage processes, managers and leaders must decide which tasks remain human and which can be automated. They need to know how to ensure that algorithmic decisions stay fair, transparent, and accountable.

Service science provides a structured way to make these judgments by connecting technology choices to human outcomes.

Implications for Business Education and Faculty

As business education adapts for agility, relevance, and societal impact, faculty must be empowered to thrive as educators and scholars. The service-oriented growth we see in the global economy calls for faculty to demonstrate the same mindsets that we expect students to adopt—mindsets based on co-creation, curiosity, interdisciplinary thinking, adaptability, resilience, and an appreciation for systems.

This shift expands our role as faculty. Teaching service science requires faculty to develop interdisciplinary fluency, engage with industry, and design learning environments where knowledge is co-created with practitioners and students. Business schools must invest in faculty development that builds interdisciplinary fluency and connects marketing with machine learning, operations with behavioral science, information systems with ethics, and strategy with design thinking.

Schools also need to invest in and teach the use of digital tools and build partnerships with organizations where the innovation of services and experiences is unfolding in real time. When faculty thrive in these expanded roles, students gain richer learning experiences and business schools enhance their societal impact.

Service science is not a niche. It is the conceptual backbone of modern value creation. Fortunately, it’s also the natural home for the digital, analytical, and AI-focused content that business schools are working to integrate.