In preparation for the NSF Smart Service Systems Virtual Forum, here are some questions and responses:
1. What do we mean by smart service systems?
Smart service systems benefit customers and providers.
Service providers try to compete for customers by (1) improving existing offerings to customers, (2) innovating new types of offerings, (3) evolving their portfolio of offerings, (4) changing their relationships to suppliers and others in the ecosystem.
“Smart” refers to improvement in key performance indicators over time (e.g., productivity indicators, quality indicators, compliance indicators, sustainability indicators, resilience indicators, etc.). “Smart” often implies increasing system capabilities over time, that overcome system constraints. An important constraint in many service systems is the trade-off between productivity and quality…. often the way to break out of that constraint requires new technology, information systems, and customer skills for self-service… for example, a bank’s ATM (automatic teller machines) systems introduced in the 1970’s improved both productivity and quality indicators for customer to withdrawn their money day or night. However, it required customers learning new skills. Retail store self-service check-out systems require even more skills for self-service.
“Service” refers to the application of knowledge (e.g., technology, organizational forms, business models, etc.) for mutual benefits, between a provider entity and customer entity (and often including other stakeholder entities, such as government agencies concerned with regulator compliance, investors concerned with return on investment, etc.). Within the service science community “service” is synonymous with “value co-creation between entities” and includes many forms of cooperation, coordination, and even mutually beneficial forms of competition.
Most service phenomena derives from division of labor between entities (service for service exchange), creating mutual dependencies between entities in vast networks of interaction and exchange. Entities apply knowledge, including technological tools, forms of organizations, to create mutual benefits that improve productivity (provider concern) and quality (customer concern) and other measures.
“Service systems” (in general) refer to dynamic configurations of resources (people, technology, information, organizations) interconnected by value propositions internally and externally to other service systems. A bus stop may have structure for passengers to wait for the bus and stay dry, often they are in disrepair – however, many cities lease access to that resource to advertising agencies – and get a new revenue stream to support public transportation, as well maintenance service. Adding display screens for ads, makes them “smart” in some ways, and may require cameras for extra security.
“Service systems” (specifically) have been evolved and designed for all aspects of business and society – transportation, water & waste, agriculture and manufacturing (servitization, such as Rolls-Royce “Power-by-the-hour”), energy and electricity (“smart grids), ICT, building, retail & hospitality, finance & banking, healthcare, education, government. Types of service system entities – entities with rights and responsibility to offer service to others include – people, businesses, universities, hospitals, cities, states, nations, etc. A better taxonomy of service system entities and understanding of the distribution of types of service systems in different societies is much needed.
“Service innovations” scale the benefits of new knowledge, globally and rapidly.
2. What are the major hurdles to introduce new knowledge and innovations (e.g., technologies, organizational forms, methods of interaction, etc.) developed in academic institutions into commercial smart service systems?
Apple’s innovations have often been based on customer experience and ease-of-use. Interaction design and new business model design are aspect of smart service system design.
The lack of ability for academics to interact with real customers and evolve new knowledge and innovations limits their commercialization efforts (e.g., lean startups are often better than licensing efforts for bringing difficult-to-scale new knowledge to market). Facebook interacted with students as customers. Google interacted with faculty and students as customers. SPSS interacted with faculty and students as customers. Tools that are accessible on-line provide a platform for academics to reach more customers. Amazon, Google, Apple, IBM/Softlayer, HP, Cisco, and many others are providing academics access to Cloud based capabilities that allow new modes of customer-provider and customer-customer, etc. interactions. The internet, the internet-of-things, and other platforms can improve academics ability to interact with customers.
a. Resources – Kickstarter and other crowd-funding sites offer ways for customers to invest in the innovations they want to see become real
b. Technology – Real tools and real data often limit academics abilities to take on real challenges
c. Policy – Privacy and protection of data is a very real concern these days, especially as cyber-security is increasingly necessary to stop criminals
d. Business Models – lean startups pivot their business models and business concepts quickly based on experiments with real customers
e. Industry Mentorships for students in course – learning to apply knowledge to take on real-world challenges is key
University four missions:
Learning – teaching: knowledge transfer
Discovery – research: knowledge creation
Engagement – entrepreneurship: knowledge application
Wholeness – citizenship: knowledge integration
3. Why are behavioral and cognitive considerations essential to further adapt technologies to be used in service systems?
Behavioral and cognitive scientists can help help understand both customers and other people inside service systems, how they interact, what incentives are required to change behaviors, etc.
a. What is the role of service science in this process?
Service science is sometimes described in the literature as the short version of service science, management, engineering, design, arts, and pubic policy (SSME+DAPP) – with the clear indication that it is an emerging transdiscipline, that borrows from many existing disciplines, but does not replace any of them.
The emerging service science community links academics, industry, and government to build the body of knowledge about the nested, networked service systems in which we all live and work. The service science community has many members who aspire to be better boundary-spanners, better T-shapes to work collaboratively on innovation teams. ISSIP.org is an umbrella professional association working on that goal.
4. What are the characteristics of successful industry-academe partnerships in service systems innovation?
One measure of success: how many mentorships are created to allow students to engage with industry mentors working on real-world challenges, where the application of knowledge that faculty have inspired the students to learn about is encouraged. Because real-world challenges do not respect discipline boundaries, and require engineers, managers, social scientists, and arts and humanities working together to engage a customer with a prototype solution – these teams are more likely to create viable service system innovations.
Industry and government provides platforms, tools, data, challenges and the academy provides multidisciplinary student teams and faculty guides to create viable solutions to challenges that can be tried out in the real-world with real-customers either as startups (some based on industry provided platforms) or as compelling proof-of-concepts that build the personal brands of students and prepare them to be T-shaped adaptive innovators, ready to hit-the-ground running in industry jobs.
5. What is your take on the new BIC solicitation? What do you expect will come up from this?
Fabulous solicitation. Will impact both human capital and close knowledge gaps.
Human capital: I expect students working on new startup ideas will come out of this, leveraging some existing industry platforms and creating some new platforms. Better prepared students and graduates – more T-shaped adaptive innovators who can be better prepared to be in both start-ups or other industry positions on leading edge service offerings.
Knowledge gaps: Many knowledge gaps exist related to understanding service systems, and how to scale the benefits of new knowledge, globally and rapidly – new technologies, new organizational forms, new business models, new skills in people, etc.