Jim Spohrer, (spohrer@us.ibm) Director, Almaden Services Research

1. Why the world needs more systems thinkersfocused on service systems--- or ---Beyond computer science: The emergence of service science Services Sciences, Management, and Engineering (SSME)Networked Information (Systems, Services, Solutions) Sciences, Management, and Engineering (NIS3SME) Jim Spohrer, (spohrer@us.ibm.com) Director, Almaden Services Research Title slide

2. Today’s Talk • The world needs more multidisciplinary systems thinkers • Accelerating rate of change and globally connected social, political, economic, business, and technology systems • Unfortunately, without systems thinking, unintended consequences to actions all too often result • In government policy, business strategy, and academic research, what is the optimal ratio of specialists to systems thinkers in this new age of rapid change and global interconnectedness? • Focused on service systems evolution and design • Government, business, academic collaboration ready to focus on services • Service sector dominates global economies, and the world is a big, rapidly changing, and highly interconnected service system • All stakeholders (government, business, and academics) want systematic service innovations to predictably improve productivity and quality • Why this matters to IBM? Now more than 50% services revenue, and on demand e-business and business performance transformation services require new ratio of specialists to systems thinkers (service scientists)

3. Problem Need more system thinkers The Systems View of the World: A Holistic Vision for Our Time by: Ervin Laszlo How We Got Here : A Slightly Irreverent History of Technology and Marketsby Andy Kessler

4. Sterman’s Business Dynamics • “Accelerating economic, technological, social, and environmental change challenge managers and policy makers to learn at increasing rates, while at the same time the complexity of the systems in which we live are growing. Many of the problems we now face arise from unanticipated side effects of our own past actions.” • Dynamic complexity arises because systems are: • Dynamic, tightly coupled, governed by feedback, nonlinear, history dependent, self organizing, adaptive, counterintuitive, policy resistant, and characterized by trade-offs • How rapid is the change and are there any patterns in how humans deal with complexity… how do people invest their time? Business Dynamics: Systems Thinking and Modeling for a Complex Worldby John Sterman

5. Information Energy [ ] [ ] Energy Time Useful info Time Max Max A: Building and using tools and relationships (organizations) to achieve goals. (human activities change over time as we develop and use new capabilities) Q: How do people invest their time? Humans as Informavore (George A. Miller, 1983) Source: Pirolli (2002) George

6. Building tools & organizations – accelerating growth of capabilities Global Brain: The Evolution of Mass Mind from the Big Bang to the 21st Centuryby Howard Bloom Nonzero : The Logic of Human Destiny by Robert Wright

7. Coevolution of Institutions, Disciplines, Professions, Application(governance, exploration, exploitation, diffusion of innovation)

8. Reductionism (specialists) & Integration (systems thinkers):Plus a much prettier picture than my coevolution table! Rita Colwell, Former Director National Science Foundation (NSF)

9. Human Activities: Sociotechnical System Evolution Estimated world (pre-1800) and then U.S. Labor Percentages by Sector Estimations based on Porat, M. (1977) Info Economy: Definitions and Measurement The Company of Strangers : A Natural History of Economic Lifeby Paul Seabright The Pursuit of Organizational Intelligence, by James G. MarchExploitation vs exploration

10. Human Population: Sociotechnical System Evolution Rise of the modern managerial firm Effects of Agriculture, Colonial Expansion & Economics, Scientific Method, Industrialization & Politics, Education, Healthcare & Information Technologies, etc. Shadows in the Sun, by Wade Davis “Ethnosphere. sum total of all the thoughts, beliefs, myths, and institutions brought into being by the human imagination” The Visible Hand: The Managerial Revolution in American Businessby Alfred Dupont Chandler

11. Systematic Innovation: Invest & Get Predictable Results • Moore’s Law – Scaling down helped propel Computer Science • Scale-down of transistor size every few years results in better economics of digital logic (faster and denser logic for computation and storage) • Algorithmic complexity theory is a well developed theory of algorithm scaling in time and space complexity • Surowiecki’s Law – Scaling up may help propel Service Science • Scale-up in number of service interactions every few years may result in better economics of service logic (higher productivity and quality) • Wisdom of the crowds – laws of large numbers – Amazon’s recommendation system gets better with use/scale; E-bay’s reputation system; Google’s relevancy rank • The more people that use a service the easier it is to make improvements – capture experiences, analyze experience, redesign based on frequency • What is the optimal pacing to give innovators (service providers and clients) the best return on investment for participating in coproduction relationships? The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nationsby James Surowiecki

12. Approach Focus on service systems

13. Propositions • Government policy should more highly prioritize multidisciplinary services research and education centers. • Industry, academics, and government need to work more closely together to articulate the need and the potential national and global benefits. • Government needs to improve their productivity and quality of service • Businesses should be investing more to make innovation in services more systematic. • Vast quantities of service data are generated by the business world every day, and yet precious little is being leveraged by research institutions. • Businesses need to transform and improve productivity and quality of service • Academic silos should be bridged. • There is an opportunity at the intersection of social sciences, business schools, science & engineering schools (1) to create a unified theory of service system evolution, management, and design, and (2) to graduate professionals that better meet the needs of society (highly interconnected, rapidly changing). • Education needs to improve productivity and quality of service

14. Definitions • Service Science, short for Services Sciences, Management, and Engineering (SSME) • Definition 1: The application of scientific, management, and engineering disciplines to tasks that one organization beneficially performs for and with another (‘services’) • Make productivity, quality, performance, compliance, growth, and learning improvements more predictable in work sharing and risk sharing (coproduction) relationships. • Science is a way to create knowledge • Engineering is a way to apply knowledge and create new value • Business Model is a way to apply knowledge and capture value • Management improves the process of creating and capturing value.

15. Terms & Definitions • Service Science, short for Services Sciences, Management, and Engineering (SSME) • Definition 1: The application of scientific, management, and engineering disciplines to tasks that one organization beneficially performs for and with another (‘services’) • Make productivity, quality, performance, compliance, growth, and learning improvements more predictable in work sharing and risk sharing (coproduction) relationships. • Definition 2: The study of service systems. • Evolution & Design: Services systems evolve in difficult to predict ways because of naturally emergent and rationally designed path dependent interactions between economic entities, acting in the roles of clients and providers coproducing value. • Interactions & Value Coproduction: Service systems are made up of large numbers of interacting clients and providers coproducing value. Each economic entity is both a client and a provider. Service system dynamics are driven by the constantly shifting value of knowledge distributed among people, organizations, technological artifacts (culture), and embedded in networks or ecosystems of relationships amongst them. • Specialization & Coordination: One mechanism for creating value is specialization of clients and providers, which results in the need for coordination via markets, organizational hierarchies, and other mechanisms. Specialization creates efficiency. Efficiency creates profits and leisure. Profits and Leisure create investment (profits to innovation) and new demand (leisure to new aspirations).

16. Why IBM cares about services… • Preamble: IBM Research – what you know and may not know • Problem: Motivation and Definitions • Importance: Economic Growth & Need for Service Innovations • Approach: Academic-Industry-Government Collaboration • Progress: Events, Relationships, References, Investments • Next Steps: Challenges and Obstacles

17. IBM Research Worldwide

18. What Physicists Do At IBM Research… This achievement is a major milestone toward creating a microscope that can make three-dimensional images of molecules with atomic resolution

19. IBM Computer Scientists build bigger, faster computers Blue Gene, as its name suggests, is aimed at the drug-development market. Scientists hope eventually to model how proteins fold – a process that is important in designing drugs that can block cancer cells and other diseases. 70.72 teraflops on 11/2004 183.5 teraflops on 3/2004 (Linpack benchmark)

20. What you may not know… IBM helped start computer science; not out of altruism, but to meet a business need Now IBM is working with academics and government to establish Service Science The biggest costs were in changing the organization. One way to think about these changes is to treat the Organizational costs as an investment in a new asset. Firms make investments over time in developing anew process, rebuilding their staff or designing a new organizational structure, and the benefits from these Investments are realized over a long period of time.” Eric Brynjolfsson, “Beyond the Productivity Paradox”

21. Service Science: Why Now? IBM’s perspective

22. 2004 IBM Annual Report: 2x Productivity Increase leads to 60% Gross Profit Margins for Services source: ftp://ftp.software.ibm.com/annualreport/2004/2004_ibm_financials.pdf

23. Multidisciplinary Nature ofPhDs in IBM’s Global Services Division (US)

24. Need for service scientists in ResearchPhDs in IBM’s Research Division (US)

25. Problem: Motivation & Definitions • Motivation • Need better trained people: Services professionals & researchers • Need more knowledge about sustainable service innovation techniques: Innovation is the key to value creation & capture, and hence the key to sustainable business advantage • Need more systematic methods for studying and creating knowledge about service systems: Investment in science & research pays in new knowledge • Example: Computer Science (coevolution of occupation, discipline, techniques, science) • Preliminary Definitions • Services: A client pays a service provider to transform the state of something, a person, product, or business (e.g., enterprise transformation), in a manner mutually shaped by both. • Service Innovation: Service innovation is a change to a service system (made up of many clients and providers interacting) that creates measurable improvement in characteristics of interest, achieved via the diffusion of technical innovation, business innovation, social innovation, demand innovation, or some combination of these factors. • Service Science: Working with academics in multiple disciplines to create a definition, draft - the study of service systems (characterized by coevolving technical-business-social change) and measures of system performance (productivity, client satisfaction), growth processes (scale, scope), and learning processes (optimization-exploitation, exploration).

26. The world is becoming a service system. Why Now? Top Ten Nations by Labor Force Size (about 50% of world labor in just 10 nations) A = Agriculture, G = Goods, S = Services 2004 2004 United States (A) Agriculture: Value from harvesting nature (G) Goods: Value from making products (S) Services: Value from enhancing the capabilities of things (customizing, distributing, etc.) and interactions between things The largest labor force migration in human history is underway, driven by urbanization, global communications, low cost labor, business growth and technology innovation. >50% (S) services, >33% (S) services

27. Why Now?: US GNP Today and in the Future From Uday Karmarkar: “Service industrialization in the global economy” Also author of HBR article: “Will you survive the services revolution?” Uday Karmarkar, IBM Faculty Award, Pro-Service Innovation Products Services 11% 30% Material 50% 9% Information

28. Definitions of Services • Deed, act, or performance (Berry, 1980) • An activity or series of activities… provided as solution to customer problems (Gronroos, 1990) • All economic activity whose output is not physical product or construction (Brian et al, 1987) • Intangible and perishable… created and used simultaneously (Sasser et al, 1978) • A time-perishable, intangible experience performed for a customer acting in the role of co-producer (Fitzsimmons, 2001) • A change in condition or state of an economic entity (or thing) caused by another (Hill, 1977) • Characterized by its nature (type of action and recipient), relationship with customer (type of delivery and relationship), decisions (customization and judgment), economics (demand and capacity), mode of delivery (customer location and nature of physical or virtual space) (Lovelock, 1983) • Deeds, processes, performances (Zeithaml & Bitner, 1996)

29. So, services are…Pay for performance in which client and provider coproduce value • High talent performance • Knowledge-intensive business services (business performance transformation services) (e.g., chef’s, concert musicians) • High support performance • Environment designed to allow average performer to provide a superior performance (average cook with great cook book and kitchen; average musician with a synthesizer) • High tech performance • Computational services (e-commerce, self service – client does work) • Even here… talent builds, maintains, upgrades, etc. the technology • Routine performance (sometime High Finance) • This is being automated, outsourced, labor arbitrage, financial arbitrage, migrated to high talent/value sectors, or otherwise being rationalized

30. Services: Client pays provider for a performance or promise of a performance. The client and provider share responsibility for coproduction of value within the boundaries of the relationship (aspire to “win-win”). • Performance: Activities that transform the state of something. • Coproduction relationship: A relationship in which goals/work responsibilities and risks/rewards are shared, with an explicit or tacit contract defining initial/intermediate/ongoing/final states/results/effort/quality levels. External factors that might impact the relationship may or may not be enumerated. Third party partners may be involved in establishing, evaluating, and working front stage or back stage in the coproduction relationship. • Front stage activities: Sometimes called the “moments of truth” in which client and provider directly interact. Pure services are mostly front stage. Variance in the front stage is largely due to the client’s requests and actions, and provides opportunities to provide higher value services. Eliminating front stage variance can lead to standards and higher quality, but may also destroy a lot of high end value creation opportunities. • Back stage activities: Both provider-side activities that do not directly involve the client, and client-side activities that do not directly involve the provider. Pure products are mostly back stage for providers (manufacturer). Six sigma is an effective method for eliminating unnecessary variance in the backstage, which leads from custom processes to standard processes. • Services vary based on how much front-stage or back-stage activities are required, how custom or standard the activities are, and how client intensive or non-client intensive the activities are. • Provider firms orchestrate or coordinate employees, partners, and clients in the coproduction of value. Some have referred to this as creating economies of coordination – simple to complex.

31. Getting systematic about service innovations • Improve back stage provider or client productivity: Applying six sigma, process re-engineering, and other transformation activities to the back stage. Function of costs of activities, including costs of unwanted variance. • Improve front stage scope: Expanding the scope of front stage services – addressing more or better the custom requests of clients, as well as exploiting more of the unique capabilities of providers. Function of value of needs, including enabling new capabilities. • Improve coordination: Standardize processes and interactions. This can boost quality (compliance) and productivity. Function of scale, complexity, and uncertainty in the system. • Improve dynamic evolution: Continuously migrate provider-client pairs to higher value creation and capture points on an on-going basis. Function of time. • Improve capabilities of people, organizations, institutions or technologies to enter into higher value creation and capture configurations. Function of systems productive capacity – innovating new capabilities (incremental, radical, and super-radical innovations).

32. High talent performance is on the rise in the US economy 95% of all scientists are alive today. From Herzenberg, Alic, Wial (1998)

33. Tip of the hat to Henry Chesbrough, a pioneer.Henry Chesbrough, IBM Faculty Award, Services Science Pioneer

34. Why Service Science? New knowledge drives the process of systematic innovation… Knowledge sources driving service innovations… Science & Engineering (Study phenomena and create new knowledge) Business Administration and Management (Study phenomena and create new knowledge) Business Innovation Technology Innovation Demand Innovation Global Economy & Markets (Emergence of new knowledge in practice!) Social-Organizational Innovation Social Sciences (Study phenomena and create new knowledge) SSME = Service Sciences, Management, and Engineering

35. Berkeley’s new ORMS undergraduate majorRhonda Righter, IBM Faculty Awardhttp://www.ieor.berkeley.edu/AcademicPrograms/Ugrad/ORMS.pdf

37. Relationship of Service Science to Existing Academic Areas:The center balances three key factors: business value, IT process, organizational culture 1990-2004 1900-1960 Process: Information Technology 14 28 21 18 10 1 11 5 13 7 17 2 3 6 4 8 12 15 16 27 22 9 25 24 19 Capital: Business Decisions 23 People: Organizational Culture 20 26 1960-1990 Before 1900

38. NETWORKED INFORMATION SYSTEMS Networked Information Systems ORGANIZATIONS TECHNOLOGY MANAGEMENT

39. Services Related Programs (small sampling) • Center for Relationship Marketing and Service Management, Hanken, Finland • Center for Service Leadership, Arizona State University, USA • The Center for Hospitality Research, Cornell University, USA • CTF, Centrum för Tjänsteforskning (Service Research Centre), University of Karlstad, Sweden • Centre for Service Management, Cranfield School of Management, UK • Relationship Marketing, Emory University, USA • Service Management Research Programme, Nankai University, PR China • Relationship Marketing, University of Auckland, New Zealand • Center for Services Marketing, University of Maryland, USA • School of Services Management, Nanyang Polytechnic, Singapore • Fishman-Davidson Center for Service and Operations Management, Wharton, UPenn, USA • Service Management, University of Buckingham, UK • Service Engineering, Technion, Israel • Services Management, Brigham Young University, Utah • Service Management, Warwick Business School, UK • Operations Management of Services, California State University, Northridge, USA • Services Management & New Service Development, University of Texas, Austin, USA • Service Operations Management, Universidade Federal, Rio de Janeiro, Brazil • Service Operations Management, University of Calgary, Canada • Management of Services, University of Western Ontario, Canada • Service Operations Management, San Jose State University, CA, USA • Productivity Management, City University of Hong Kong • Managing Service Operations, DePaul University, USA • Service Management and Strategy, London School of Business, UK • Others at http://www.servsig.org/Syllabi/Service_Operations_Management_Syllabi.pdf

40. Select efforts to promote service science • Dec. 2002: Almaden Service Research established, the first IBM Research group completely dedicated to understanding service innovations from a sociotechnical systems perspective, including enterprise transformation and industry evolution(http://www.almaden.ibm.com/asr/) • March 2003: IBM-Berkeley Day: Technology… At Your Service!(http://www.eecs.berkeley.edu/IPRO/IBMday03/) • September 2003: Coevolution of Business-Technology Innovation Symposium(http://www.almaden.ibm.com/coevolution/) • April 2004: Almaden Institute: Work in the Era of the Global, Extensible Enterprise(http://www.almaden.ibm.com/institute/2004/) • May 2004: “Architecture of On Demand” Summit: Service science: A new academic discipline?(http://domino.research.ibm.com/comm/www_fs.nsf/pages/index.html) • June 2004: Paul Horn, VP IBM Research, briefs analysts on “Services as a Science” • September 2004: Chesbrough’s “A failing grade for the innovation academy” appears in the Financial Times(http://news.ft.com/cms/s/9b743b2a-0e0b-11d9-97d3-00000e2511c8,dwp_uuid=6f0b3526-07e3-11d9-9673-00000e2511c8.html) • November 2004: IBM’s GIO focuses on service sector innovations: government, healthcare, work-life balance(http://www.ibm.com/gio) • November 2004: Service Innovations for the 21st Century Workshop(http://www.almaden.ibm.com/asr/events/serviceinnovation/) • December 2004: Samuel J. Palmisano, IBM CEO, Harvard Business Review interview discusses the important role of “values” in organizational performance, “Leading Change When Business is Good”(http://harvardbusinessonline.hbsp.harvard.edu/b01/en/common/item_detail.jhtml?id=R0412C) • December 2004: IBM expands academic initiatives related to service innovations, including sponsoring Tannenbaum Institute of Enterprise Transformation at Georgia Tech. • February 2005: Chesbrough’s “Service as a Science” in Harvard Business Review Breakthrough ideas of 2005 • May, June, July, etc. Oxford, Warwick, Bentley, Penn State, etc.

41. Historical Example: Emergence of new academic discipline and systematic approach to innovation and wealth creation • Emergence of German dye industry, German mid-19th Century • Emergence of chemistry as an academic discipline • Emergence of patent protection in the new area of chemical processes and formula • Emergence of new relationships connecting firms, academic institutions, government agencies, and clients • Demonstrates needed coevolution of firms, technology, and national institutions • Took England and US over 70 years to catch up!!! Knowledge and Competitive Advantage : The Coevolution of Firms, Technology, and National Institutions by Johann Peter Murmann

42. One Policy Challenge: Beyond Technology Patents… Patenting Business, Social-Organizational, Demand Innovations Source: Robert M. Hunt “You can patent that? Are patents on software and business models good for the new economy?”

43. Service Science – Reading List • Motivation • Chesbrough (2005) Towards a new science of services. Harvard Business Review. • Chesbrough (2004) A failing grade for the innovation academy. Financial Times. • Rust (2004) A call for a wider range of services research. J. of Service Research. • Tien & Berg (2003) A case for service systems engineering. J. Sys. Science & Sys. Eng. • Rouse (2004) Embracing the enterprise. Industrial Engineer. • Karmarkar (2004) Will you survive the services revolution. Harvard Business Review. • Philosophy • Vargo & Lusch (2004) Evolving a new dominant logic for marketing. J. of Marketing. • Exemplar Model • Oliva & Sterman (2001) …Quality erosion in the services industry. J. of Management Science. • Economics • Bryson et al (2005) Service worlds. Routledge. London, UK. • Herzenberg et al (1998) New rules for a new economy. Cornell University Press. Ithaca, NY. • Technology • McAfee (2005) Will web services really transform collaboration? MIT Sloan Management Review. • Textbooks • Fitzsimmons & Fitzsimmons (2001) Service management. McGraw-Hill. New York, NY. • Sampson (2001) Understanding service businesses. John Wiley: New York, NY. • Evolution and Change: Managed, Designed, and Emergent • Khalil, Tarek (2000) Management of Technology. McGraw-Hill, New York, NY. • Nelson (2003) On the uneven evolution of human know-how. J. of Research Policy. • Agre (2004) An anthropological problem, a complex solution. J. of Human Organization. • Baba & Mejabi (1997) Socio-Technical Systems. J. of Human Factors & Industrial Egronomics.

44. Service Science Core Questions: How do work systems reconfigure? What role does innovation play? Can integration relationships be found across different types of work system? Human System Tool System Collaborate (incentives) Augment (tool) The choice to change work practices requires answering four key questions: - Should we? (Value) - Can we? (Technology) - May we? (Governance) - Will we? (Priorities) Help me by doing some of it for me (custom) Z 2 1 Delegate (outsource) Automate (self-service) Help me by doing all of it for me (standard) 3 4 Harness Nature (Techno-scientific models with stochastic parts) Organize People (Socio-economic models with intentional agents) Example: Call Centers Collaborate (1970) Augment (1980) Delegate (2000) Automate (2010) Technology: Voice response system Market: Lower cost geography (India) Experts: High skill people on phones Tools: Less skill with FAQ tools

45. Example Model: Oliva & Sterman (2001) Quality Erosion in Service Industry

46. Model of service businessProfitability measures for each of the 14 items below…(profits/time; time is life-span, year, quarter, month, week, day, hour, minute, second) 1 2 3 4 5 6 7 8 9 10 11 12 13 14

47. Towards Service Arts & Science… Service System Evolution (complex adaptive systems - Sociotechnical - with dynamics to create and capture value - Socioeconomic -) Science (Knowledge of what can be validated) Technology (Control) Engineering (Design of Possible) Arts (Knowledge of what can be imagined) Policy (Governance) Management (Design of Possible) • Is there a grand challenge problem worthy of both academics (a solution requires more deep knowledge and an integration across discipline silos) and businesses (a solution raises “all ships” by accelerating value creation and capture from service innovations and bestowing businesses with predictable growth advantages)? • Will the word “science” evolve in meaning to include methods for expanding knowledge about systems that are difficult or impossible to predict by their very nature – such as social-economic systems that invite “gaming” (as soon as the system becomes a little bit predictable competing dynamics are set in motion to both maintain the predictability and disrupt the predictability)?

48. Grand Challenges (per Maglio) • 1.The value of method is to enable average performers to operate like higher skill performers. But when is this possible? Under what circumstances? When is it impossible? What are tradeoffs in re-skilling people versus modifying the method? Example: An average cook might seem like an expert in a gourmet kitchen using an easy to follow cookbook. • 2. What is the optimal experience-capture to method? What is the best way to go from experience to repeatable behaviors in similar but different client situations --- and with different people executing the method? What is the tradeoff of innovation versus errors in dealing with exceptional cases and differences? How does having a supervisor or mentor that checks performance help? • 3. How can get an organization to change when times are good? According to Sam Palimisano in his HBR interview in December, it is easy to change when times are bad (witness IBM in the early 1990s), but how can we structure or encourage change when times are good but might be bad later? • 4. What grand challenge problem is worthy of both academics and businesses? Academics need a problem whose solution requires more deep knowledge and an integration across discipline silos, and businesses need a problem whose solution raises “all ships” by accelerating value creation and capture from service innovations and bestowing businesses with predictable growth advantages. • 5. Can there be a science of social-technical-economic systems, systems that by their very nature are diffciult or impossible to predict? Will the word “science” evolve in meaning to include methods for expanding knowledge about systems that are difficult or impossible to predict – such as social-economic systems that invite “gaming” (as soon as the system becomes a little bit predictable competing dynamics are set in motion to both maintain the predictability and disrupt the predictability)?

49. Work items • Establish the importance of getting more systematic about service innovation for academics, business, and government • Highlight the work of the pioneers and early champions of systematic approaches to service innovation and service science • Review of components of existing degrees requirements and course elements that should be part of a service science curriculum • Define the fundamental research questions and grand challenges that the science is seeking answers to (value if answered, methodologies and tools for answering them, etc.) • Agree on conferences, journals, and other community growth initiatives • Explore the role of government and industry, especially with respect to accessing the fundamental data on which the science will be based • Establish a feedback mechanism that surveys graduates who enter IGS to see what skills they used most and the ones they wish they had learned while in school • Discuss the many roadblocks, challenges, overwhelming political obstacles, etc. to establishing the field.

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