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Service science intro 20110606 v1
 

Service science intro 20110606 v1

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an introduction to service science that provides the basics of: service system thinking, service system dynamics, service system re-design examples, and tries to answer the "why questions" - end notes ...

an introduction to service science that provides the basics of: service system thinking, service system dynamics, service system re-design examples, and tries to answer the "why questions" - end notes include the birth of service science, discussion of advanced manufacturing, outsourcing, sustainability, as well as ways to learn more about service science

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  • Reference content from this presentation as: Spohrer, JC (2011) Introduction to Service Science. To Educational Policy Thinkers. June 29 th , 2011, Washington, DC Permission to redistribute granted upon request to spohrer@us.ibm.com
  • Service systems are the fundamental abstraction of service science. The ABC’s of service-systems thinking are: A is the Service Provider, B is the Service Customer, and C is the Service Target For example, in College as a Service (CaaS), A might be a college, B an undergraduate student, and C dimensions of the student that will be transformed, such as specific skills and competences, certifications, and post-family social relationships, including help finding a good job
  • How might a service scientist approach the problem of creating service innovations to continuously improve college courses, year over year, when required competencies and job roles are forever changing? For example: Computer Science 2003-2005 (dramatic drop in enrollment, student quality, faculty motivation, and future employer satisfaction with grads) http://www.cra.org/uploads/documents/resources/taulbee/CRA_Taulbee_2009-2010_Results.pdf First, service scientists learn about problems, opportunities, and boundaries by interviewing stakeholders. Next, they create a formal model of the service system, including a table of all stakeholder interactions, what technologies and organizations mediate those interactions, and who owns, does not own, or aspires to own the perceived problems, opportunities, and boundary zones. Service scientists create designs to scale the capacity of service systems, up and down, and continuously improve upon multiple stakeholder measure For example, given the three problems… • Each year 20% of faculty activities should be converted to upfront e-learning that students must pass to enroll in the class. Year over year, this will ensure the capability of students entering the classroom increases slightly. The new service system, an augmentation, is required to engage faculty and other stakeholders to identify the 20% of the classroom activity to be freed up, and embed these curricular components into the e-learning certification system. • Half the freed-up faculty time should be replaced with new course material designed to better meet the needs of industry. The second added service system will engage industry and faculty to create the needed curriculum changes, such as description of specific on-the-job challenges and responsibilities faced by practitioners. • Half the freed-up faculty time should be replaced with new course material designed to meet the needs of the faculty for more intellectually stimulating content and meaningful work experience, such as the top research problems they are working on and why.
  • There are many opportunities for educational institutions to specialize. Better tuned competence of individuals allows graduates to hit the ground running and better fill roles in business and societal institutions…. Better general education will allow more rapid learning of an arbitrary area of specialization, and create a more flexible labor force… All service systems transform something – perhaps the location, availability, and configuration of materials (flow of things), or perhaps people and what they do (people’s activities), or perhaps the rules of the game, constraints and consequences (governance). How to visualize service science? The systems-disciplines matrix… SSMED or service science, for short, provides a transdisciplinary framework for organizing student learning around 13 systems areas and 13 specialized academic discipline areas. We have already discussed the 13 systems areas, and the three groups (flows, human activity, and governing)… the discipline areas are organized into four areas that deal with stakeholders, resources, change, and value creation. If we have time, I have included some back-up slides that describes service science in the next level of detail. However, to understand the transdisciplinary framework, one just needs to appreciate that discipline areas such as marketing, operations, public policy, strategy, psychology, industrial engineering, computer science, organizational science, economics, statistics, and others can be applied to any of the 13 types of systems. Service science provides a transdisciplinary framework to organize problem sets and exercises that help students in any of these disciplines become better T-shaped professionals, and ready for teamwork on multidisciplinary teams working to improve any type of service system. As existing disciplines graduate more students who are T-shaped, and have exposure to service science, the world becomes better prepared to solve grand challenge problems and create smarter systems that deliver modern service. Especially, where students have had the opportunity to work as part of an urban innovation center that links their university with real-world problems in their urban environment – they will have important experiences to help them contribute to solving grand challenge problems. ================================================ SSMED (Service Science, Management, Engineering and Design) Systems change over their life cycle… what is inside become outside and vice versa In the course of the lifecycle… systems are merged and divested (fusion and fission) systems are insourced and outsourced (leased/contracted relations) systems are input and output (owner ship relations) SSMED standard should ensure people know 13 systems and 13 disciplines/professions (the key is knowing them all to the right level to be able to communicate and problem-solve effectively) Multidisciplinary teams – solve problems that require discipline knowledge Interdisciplinary teams – solve harder problems, because they create new knowledge in between disciplines Transdisciplinary teams – solve very hard problems, because the people know discipline and system knowledge Ross Dawson says “Collaboration drives everything” in his talk about the future of universities… https://deimos.apple.com/WebObjects/Core.woa/BrowsePrivately/griffith.edu.au.3684852440
  • High school drop out rates in cities can be high… by increasing focus on system of systems in all grade levels, especially STEM discussions of how to study and then propose solutions to local community challenges – there is evidence that exemplar programs increase the diversity and desire of students to go onto college in STEM areas, and then go on to jobs that use these skills to improve systems…. A number of NAE studies as well as NMC study on challenge-based learning provide encouraging information – also IBM has a Smater Learning white paper which confirms some of these findings. http://www.ibm.com/ibm/ideasfromibm/us/smartplanet/topics/educationtechnology/20090601/index1.shtml See Challenge-Based Learning: http://www.nmc.org/news/nmc/nmc-study-confirms-effectiveness-challenge-based-learning Smarter Planet University Jam Final report at: https://www.ibm.com/developerworks/university/smartplanet_jam/ Awards given to top participants, e.g., faculty and students… Prizes as Incentives for Public-Private Partnerships In recent years, there has been a renaissance in “incentive prizes” – which reward contestants for achieving a specific future goal. http://blog.ostp.gov/2009/06/17/prizes-as-incentives-for-public-private-partnerships/comment-page-2/ crowd-sourcing the world.... see http:// www.itsa.org /challenge/ WE are smarter than ME, i.e. and a diversified, independent, decentralized community can outperform even the greatest of experts. This challenge is open to entrepreneurs, commuters, transportation experts, researchers, universities, students, scholars, scientists and citizens from all fields around the globe. All ideas will be reviewed discussed and rated by an open global community, to determine the best and most creative ideas to effectively solve the consequences of traffic congestion. The winner will be announced during the 16th World Congress on Intelligent Transportation Systems in Stockholm, Sweden, September 21 - 25, 2009, and will receive a cash a of $50,000 USD , as well as development and implementation support to pursue turning the ideas into real-world solutions. Ideas will be reviewed, discussed and rated by an open global community. The public will determine the best and most creative ideas to effectively solve the consequences of traffic congestion. The winner will be chosen by the community. For the next 60 days the community (which anyone can join ) will review and rate all submissions on 5 criteria. On August 1st, the top 9 solutions will be announced. These 9 will then submit more information including a slideshow, a video and founder bios. Based on this information, the participating community members can decide who they each want to back. Each member allocates points they have earned through what is known as a predictive market. The overall winner is the solution that receives the most backing. This challenge truly is: for the people, by the people, and decided by the people.
  • Part of IBM’s approach to the second problem is T-shaped people and service science…. What is the skills goal? T-shaped professional, ready for T-eamwork… T-shaped people are ready for T-eamwork – they are excellent communicators, with real world experience, and deep (or specialized) in at least one discipline and systems area, but with good team work skills interacting with others who are deep in other disciplines and systems areas. Also, T-shaped professionals also make excellent entrepreneurs, able to innovate with others to create new technology, business, and societal innovations. T-shaped people are adaptive innovators, and well prepared for life-long learning in case they need to become deep in some new area… they are better prepared than I-shaped people, who lack the breadth. Therefore, IBM and other public and private organizations are looking to hire more of this new kind of skills and experience profile – one that is both broad and deep.. These organizations have been collaborating with universities around the world to establish a new area of study known as service science, management, engineering, and design (SSMED) – to prepare computer scientists, MBAs, industrial engineers, operations research, management of information systems, systems engineers, and students of many other discipline areas – to understand better how to work on multidisciplinary teams and attack the grand challenge problems associated with improving service systems…
  • Technology is used by providers to perform more and more of the routine manual, cognitive, and transactional work Jobs Change: Individual Competencies & Institutional Roles
  • http://www.bls.gov/emp/ep_chart_001.htm http://theeconomiccollapseblog.com/archives/student-loan-debt-hell-21-statistics-that-will-make-you-think-twice-about-going-to-college Posted below are 21 statistics about college tuition, student loan debt and the quality of college education in the United States.... #1 Since 1978, the cost of college tuition in the United States has gone up by over 900 percent . #2 In 2010, the average college graduate had accumulated approximately $25,000 in student loan debt by graduation day. #3 Approximately two-thirds of all college students graduate with student loans . #4 Americans have accumulated well over $900 billion in student loan debt. That figure is higher than the total amount of credit card debt in the United States. #5 The typical U.S. college student spends less than 30 hours a week on academics. #6 According to very extensive research detailed in a new book entitled "Academically Adrift: Limited Learning on College Campuses", 45 percent of U.S. college students exhibit "no significant gains in learning" after two years in college. #7 Today, college students spend approximately 50% less time studying than U.S. college students did just a few decades ago. #8 35% of U.S. college students spend 5 hours or less studying per week. #9 50% of U.S. college students have never taken a class where they had to write more than 20 pages. #10 32% of U.S. college students have never taken a class where they had to read more than 40 pages in a week. #11 U.S. college students spend 24% of their time sleeping, 51% of their time socializing and 7% of their time studying. #12 Federal statistics reveal that only 36 percent of the full-time students who began college in 2001 received a bachelor's degree within four years. #13 Nearly half of all the graduate science students enrolled at colleges and universities in the United States are foreigners. #14 According to the Economic Policy Institute, the unemployment rate for college graduates younger than 25 years old was 9.3 percent in 2010. #15 One-third of all college graduates end up taking jobs that don't even require college degrees. #16 In the United States today, over 18,000 parking lot attendants have college degrees. #17 In the United States today, 317,000 waiters and waitresses have college degrees. #18 In the United States today, approximately 365,000 cashiers have college degrees. #19 In the United States today, 24.5 percent of all retail salespersons have a college degree. #20 Once they get out into the "real world", 70% of college graduates wish that they had spent more time preparing for the "real world" while they were still in school. #21 Approximately 14 percent of all students that graduate with student loan debt end up defaulting within 3 years of making their first student loan payment.
  • Why service scientists are interested in universities…. They are in many ways the service system of most central importance to other service systems… Graph based on data from Source: http://www.arwu.org/ARWUAnalysis2009.jsp Analysis: Antonio Fischetto and Giovanna Lella (URome, Italy) students visiting IBM Almaden Dynamic graphy based on Swiss students work: http://www.upload-it.fr/files/1513639149/graph.html US is still “off the chart” – China projected to be “off the chart” in less than 10 years: US % of WW Top-Ranked Universities: 30,3 % US % of WW GDP: 23,3 % Correlating Nation’s (2004) % of WW GDP to % of WW Top-Ranked Universities US is literally “off the chart” – but including US make high correlation even higher: US % of WW Top-Ranked Universities: 33,865 % US % of WW GDP: 28,365 %
  • We all know that economists have been reporting on the growth of the service economy for the last century…
  • What you may not know is that manufacturing companies are also seeing a growth in service revenue… from financing to maintenance to customer support services, because of the growing complexity of products…
  • So top universities around the world are starting service science related programs to study service and service system, and get better at service innovation… including government, healthcare, and education…
  • Service science was included in IBM’s 100 Icons of Progress selected by IBM’s CEO Sam Palmisano to help celebrate the IBM Centennial and 100 years of innovation leadership for business and society. SSME stands for Service Science Management and Engineering. You may also see SSME+D, where the D is for Design of service innovations.
  • If you haven’t seen it look for high tech car factory video …
  • We also know that some people have questioned the sharp distinction that economists have made, and instead prefer the notion of product-service system…. Also, more and more product businesses, those in both manufacturing, mining, agriculture, are increasingly part of value networks and service chains that require thinking about service innovation. All businesses have both a front-stage (direct customer contact) and a back-stage (no-direct customer contact)… so the distinction between product businesses and service businesses is disappearing, and more and more people talk about product-service-systems or service-system-entities. The point is simply that as more of the world lives in cities, and as more product businesses see themselves as product-service-systems, the trend towards service is inexorable, and cannot be ignored in research and education. Academia has begun to study service both from a front-stage customer-interaction focus as well as a back-stage operational efficiciency focus. Service innovation and design impact both front-stage and back-stage, because when value chains and networks form, front-stage and back-stage are relative terms. The focus is on people, their capabilities (skills and competencies), their tools, and who and what they interact with most in value creation networks. Human-Capabilities-Tools- and-Interactions in Value Creation Networks Managers and Engineers from both Service and Product Businesses seeking to improve their business performance Academic Researchers from many disciplines and schools seeking funding, data sets, and access for both empirical studies and action research (design and interventions) to advance scientific knowledge and publish results in top journals Policy Makers and Concerned Citizens seeking to improve the performance of their governments and societal institutions Quality-of-Life including Quality of service to customers Quality of jobs to employees Quality of investment opportunities to stakeholders Sustainable Innovation People, Planet,Profits Should We, Can We, May We, Will We Surprisingly to some, the service science community includes managers and engineers from both service busineses and product businesses. Service businesses can learn a lot about operational efficiency from product businesses, and product businesses can learn a lot about customer value from service businesses. This is because as Harvard’s Theordore Leavitt observed in his famous 1974 paper, all businesses include some amount of front stage activities (direct customer contact) and some amount of back stage activities (no direct customer contact). In traditional service firms, the front stage dominates and in traditional product companies the back stage dominates, in terms of number of employees. In addition to Managers and Engineers from both Service and Produce Businesses, the service science commnuity also includes academic researchers from many disciplines and schools, including engineering schools, management schools, social science schools, and information schools. Furthermore, the service science community is not restricted to for-profit businesses and academics, the community also include government policy makers and concerned citizens seeking to improve the performance of government institutions and diverse types of non-profit organizations.
  • What are the largest and smallest service system entities that have the problem of interconnected systems? Holistic Service Systems like nations, states, cities, and universities – are all system of systems dealing with flows, development, and governance. =============\\ Nations (~100) States/Provinces (~1000) Cities/Regions (~10,000) Educational Institutions (~100,000) Healthcare Institutions (~100,000) Other Enterprises (~10,000,000) Largest 2000 >50% GDP WW Families/Households (~1B) Persons (~10B) Balance/Improve Quality of Life, generation after generation GDP/Capita Quality of Service Customer Experience Quality of Jobs Employee Experience Quality of Investment-Opportunities Owner Experience Entrepreneurial Experience Sustainability GDP/Energy-Unit % Fossil % Renewable GDP/Mass-Unit % New Inputs % Recycled Inputs
  • There are many books to help teach aspects of service science, service system thinking, and stakeholder analysis Service Science Reading List – Many textbooks and reference-textbooks included: http://www.cob.sjsu.edu/ssme/refmenu.asp
  • In the Handbook of Service Science, and other publications, we have layed out the conceptual foundations of service science – the first approximation of terms we believe every service scientist should know… The world view is that of an ecology of service-system-entities. Ecology is the study of the populations of entities, and their interactions with each other and the environment Types of Service System Entities, Interactions, and Outcomes is what a service scientist studies. Service systems include: Person, Family/Household, Business, Citiy, Nation, University, Hospital, Call-Center, Data-Center, etc. – any legal entity that can own property and be sued We see that Resources (People, Technology, Information, Organizations) and Stakeholder (Customers, Providers, Authorities, Competitors) are part of the conceptual framework for service science.
  • In publications, we have also talked about foundational premises of service science, such as service system entities configure four type of resourves… Four key types of resources: People – example, a doctor or a nurse Technology – example, a computer or car, but can also be the environment, such as an agricultural-field or a coal-mine Organizations – example, IBM or a university like MIT or a government like the national government of Germany Shared Information – example, could be language, laws, measures, etc. Physicists resolve disputes about what is physical and non-physical Judges resolve disputes about rights, within their jurisdictions
  • Service system entities calculate value from multiple stakeholder perspectives Four Key Stakeholder Perspectives: P = Provider C = Customer A = Authority S = Substitute (Competitor)
  • Service system entities reconfigure access rights to resources by mutually agreed to value propositions Four key types of access rights: Owned Outright – buying a car or a house Leased/Contract – renting a car or hotel room Shared Access – most roads, the air, and common-pool-resources Privileged Access – your thoughts, governors access to the governor’s mansion, marriage, childbirth (follows from nature or roles)
  • Service system entities interact to create ten types of outcomes, which elaborates game theories four outcomes of a two player game, to reflect that even two players games take place in the context of four primary stakeholders – the customer, the provider, the authority, and the competitors. Normative – service systems judge each other and have expectations about expected and desired behaviors… (sometimes formalized as laws) The purpose of Service Systems is Value-Cocreation (North’s economic institutions, Barnard’s cooperative systems, Trist’s sociotechnical systems, Engelbart’s augmentation systems, Normann’s value creation systems, Malone’s coordination science, Flores, Williamson TCE/NIE/Contracting, etc.) Provider and client interact to co-create value Value is achieving desired change or the prevention/undoing of unwanted change Changes can be physical, mental, or social Value is in the eye of the beholder, and may include complex subjective intangibles, bartered – knowledge intensive trust matters transaction costs matter Boundary of service experience in space and time may be complex Service is value coproduction, or finding win-win interactions between a provide and a customer. If service is value coproduction, what is a service system? The simplest service system is a person (consumes and produces services), a business enterprise is also a service system (consumes and produces services), and a nation can be viewed as a service system (produces and consumes services). ------------------ Depending on time scale and outcome, both war and investment can be a lose-lose encounter.
  • Service system entities learn to systematically exploit info & tech Add Rickets “Reaching the Goal” for Internal-External-Interaction Constraints. Explain Incremental-Radical-Super-Radical in terms of units (scientific measurement) For more on Exploitation-Exploration see below.. http://sonic.northwestern.edu/wp-content/uploads/2011/03/Keynote-Watts_Collective_Problems.pdf Lavie D & L Rosenkopf (2006) BALANCING EXPLORATION AND EXPLOITATION IN ALLIANCE FORMATION, The Academy of Management Journal, 49(4). 797-818. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.123.8271&rep=rep1&type=pdf “ Pressures for exploration. Whereas inertia drives firms’ tendencies to exploit, absorptive capacity facilitates counter pressures by furnishing the mechanism via which firms can identify the need for and direction of exploratory activities. Exploration is guided not only by inventing but also by learning from others (Huber, 1991; Levitt & March, 1988) and by employing external knowledge (March & Simon, 1958). Absorptive capacity, defined as the ability to value, assimilate, and apply external knowledge (Cohen & Levinthal, 1990), helps firms identify emerging opportunities and evaluate their prospects, thus enhancing exploration. It adjusts firms’ aspiration levels, so that they become attuned to learning opportunities and more proactive in exploring them. Indeed, prior research has demonstrated how absorptive capacity enhance organizational responsiveness and directs scientific and entrepreneurial discovery (Deeds, 2001; Rosenkopf & Nerkar, 2001). It also increases the likelihood of identifying external opportunities and can therefore lead to exploration in one or more domains of alliance formation.” For more on Run-Transform-Innovate see below… When I asked how he measures the performance and effectiveness of IBM's IT team, Hennessy pointed to its "run-to-transform" ratio. IBM's IT department is divided into three groups: a "run" organization that's responsible for keeping systems running smoothly; a "transform" team focused on business-process simplification and other business transformation; and an "innovate" unit that pursues leading-edge technology initiatives. Hennessy reports to Linda Sanford, IBM's senior VP of on-demand transformation and IT. Practicing what it preaches, IBM doesn't think of its IT organization as being merely an IT department. "We call it BT and IT," Hennessy says, giving business transformation equal billing to the software, systems, and services side of its mission. http://www.informationweek.com/blog/main/archives/2009/04/ibm_cio_turns_d.html IBM CIO's Strategy: Run, Transform, Innovate Posted by John Foley on Apr 30, 2009 11:05 AM Like other CIOs, IBM's Mark Hennessy knows that a dollar saved on data center operations is a dollar earned for business-technology innovation. IBM has moved the dial on its IT budget 10 percentage points toward innovation in recent years, and Hennessy says there are still more operational efficiencies to be gained.I sat down with Hennessy for more than an hour recently in New York to talk about how he has adapted to being a CIO. A 25-year IBM veteran, he took over as CIO about 18 months ago, having spent most of his career on the business side, in sales, marketing, finance, and, most recently, as general manager of IBM's distribution sector, which works with clients in the retail, travel, transportation, and consumer products industries. Hennessy's IT team supports the company's strategy in three broad ways: by running and optimizing IBM's internal IT operations, by working with IBM business units in support of their objectives, and by facilitating company-wide collaboration, innovation, and technology requirements across 170 countries. In times past, IBM had as many as 128 different CIOs across its businesses. These days--in support of CEO Sam Palmisano's strategy of establishing a global, integrated enterprise--it has only one, and Hennessy is it. When I asked how he measures the performance and effectiveness of IBM's IT team, Hennessy pointed to its "run-to-transform" ratio. IBM's IT department is divided into three groups: a "run" organization that's responsible for keeping systems running smoothly; a "transform" team focused on business-process simplification and other business transformation; and an "innovate" unit that pursues leading-edge technology initiatives. A few years ago, IBM was spending 73% of its IT budget on keeping systems and services running and 27% on innovation. This year, its run-to-transform ratio will hit 63%-37%. Roughly speaking, IBM is shifting an additional 2% of its IT budget from run to innovation each year, and Hennessy has every expectation that his group will continue moving the ratio in that direction. "I don't see an end in sight," he says. In fact, Hennessy says that IBM's run-to-innovation ratio has improved more this year than last. "So it's actually accelerating for us," he says. Where do the efficiencies come from? The same place other CIOs find them. Server virtualization, data center consolidation (IBM has consolidated 155 data centers down to five), energy savings, applications simplification (from 15,000 apps to 4,500 apps), end user productivity, organizational collaboration, shifting skills globally, and business-process simplification. IBM has internal IT projects underway now in the areas of its supply chain, finance, workforce management, and order-to-cash processes. Hennessy reports to Linda Sanford, IBM's senior VP of on-demand transformation and IT. Practicing what it preaches, IBM doesn't think of its IT organization as being merely an IT department. "We call it BT and IT," Hennessy says, giving business transformation equal billing to the software, systems, and services side of its mission.
  • Also, recently in the Handbook of Service Science, in Spohrer and Maglio we describe the importance of symbol processing in service systems for the calculation and innovation of value cocreation opportunities…
  • We can summarize these as the six foundational premises of service science, and empirical evidence for and against them can be marshaled… and studies are appearing that do just that…
  • In conclusion, a focus on smarter systems and modern service can help cities and universities (along with other industry and government partners) to invest together in sustainable innovations, that both reduces waste and expands capabilities. Perhaps someday we may even discover and equivalent of Moore’s Law for improving service systems… but until that time, I want to say… ================================ Moore’s Law is sustained by investments that improve computational systems according to a roadmap Can we create an investment roadmap that will improve service systems according to a roadmap? GIE (Globally Integrated Enterprise) uses a run-transform-innovate investment model for continuous improvement. Run = use existing knowledge, routine operations and maintenance Transform = use industry best practice knowledge to gain the benefits of known improvements Innovation = create new knowledge that allows improvements in both ends and means of service systems, and the resources they configure. As information about service systems doubles each year, and storage, processing, and bandwidth rise, making globally better decisions is an important opportunity to explore. FYI.... short history of transistors, integrated circuits, and data centers From transistors... 1. The transistor is considered by many to be the greatest technology invention of the 20th Century 2. While the concept of the transistor has been around since the 1920's (Canadian Physicist Julius Edgar Lilienfeld's 1925 Patent - devices that use physical phenomenon of field electronic emissions)... 3. Commercially available individual transistors that could be wired into circuits, invented and commercialized in 1947 & 1948 (Bell Labs Shockley Point Contact/Junction Transistor Theory 1947, Raytheon CK703 first commercially available 1948) To Integrated circuits... 4. However, it was not until the late 1950's and early 1960's that manufacturing process advances and commercial applications began using many of them in integrated circuits (TI, Bell Labs, etc.) - Sept 1958 the first integrated circuit (Jack Kilby TI) To Moore's law.... 5. By 1965 Gordon Moore's (Intel) paper stated the number of transistors on a chip would double about every two years (and exponential increase that has over 40 years of confirmation)... 6. The number of transistors manufactured each year (in 2009) is estimated at 10**18 - 3.9 x 10**6 transistors produced in 1957 (tenth anniversary of first transistor) - abut 10**18 transistors manufactured in 2009 (62th anniversary of first transistor) To data centers and "electricity consumption" .... 7. By 2005, data centers and server farms consume 0.5% of total worldwide electricity production (1% if cooling is included) - 2005 consumption equivalent of seventeen 1000 MW powerplants - electric consumption for data centers doubled from 2000 to 2005 Sources: http://semiconductormuseum.com/HistoricTransistorTimeline_Index.htm http://www.mentor.com/company/industry_keynotes/upload/rhines-globalpress-low-power.pdf http://www.iop.org/EJ/article/1748-9326/3/3/034008/erl8_3_034008.pdf?request-id=7cf4b6e5-498f-4ed4-bfc9-76eda96773ce
  • In conclusion, let’s consider the big picture – starting with the big bang…. and evolution of the earth, life on earth, human life, cities, universities, and the modern world… the evolution of observed hierarchical-complexity Age of natural systems (age of the universe): Big Bang http://en.wikipedia.org/wiki/Age_of_the_universe Age of urban systems (age of complex human-made world): Oldest city http://en.wikipedia.org/wiki/List_of_cities_by_time_of_continuous_habitation (end of last Ice Age was about 20,000 years ago, about 5 million people on earth by 10,000 years ago) http://www.ncdc.noaa.gov/paleo/ctl/100k.html (last Ice Age was probably started about 70,000 years ago when a super volcano erupted blocking sun light) Many people still ask -- where is the science in the “Service Science?” One answer is that the science is hidden away in each of the component disciplines that study service systems, scientifically from their particular perspective… However, the big picture answer is “Ecology” - Ecology is the study of the abundance and distribution of entities (populations of things) in an environment… and how the entities interact with each other and their environment over successive generations of entities. The natural sciences (increasingly interdisciplinary) study the left side, using physics, chemistry, and biology Service science (originated as interdisciplinary) studies the right side, using history, economics, management, engineering, design, etc. Service science is still a young area, but from the growth of service in nations and businesses to the opportunity to apply service science to build a smarter planet, innovate service systems, and improve quality of life… it is an emerging science with bright future, and yes… it will continue to evolve : - ) Most people think of ecology in terms of living organisms, like plants and animals in a natural environment. However, the concept of ecology is more general and can be applied to entities as diverse as the populations of types of atoms in stars to the types of businesses in a national economy. I want to start my talk today on “service,” by first thinking broadly about ecologies of entities and their interactions. Eventually, we will get to human-made service system entities and human-made value-cocreation mechanisms… but for today, let’s really start at the very beginning – the big bang. About 14B years ago (indicated by the top of this purple bar), our universe started with a big bang. And through a process of known as fusion, stars turned populations of lighter atoms like hydrogen into heavier atoms like helium, and when stars of a certain size have done all the fusion they could, they would start slowing down, and eventually collapse rapidly, go nova, explode and send heavier atoms out into the universe, and eventually new stars form, and the process repeats over and over, creating stars with different populations of types of atoms, including heavier and heavier elments. So where did our sun and the earth come from…. Eventually after about ten billion years in the ecology of stars and atoms within stars, a very important star formed our sun (the yellow on the left) – and there were plenty of iron and nickel atoms swirling about as our sun formed, and began to burn 4.5B years ago, and the Earth formed about 4.3B years ago (the blue on the left)… In less than a billion years, the early earth evolved a remarkable ecology of complex molecules, including amino acids, and after less than a billion years, an ecology of bacteria took hold on early earth (the bright green on the left). The ecology of single cell bacteria flourished and after another billion years of interactions between the bacteria, the first multicellular organisms formed, and soon the ecology of sponges (the light blue on the left) and other multi-cellular entities began to spread out across the earth. Then after nearly two billion years, a type of division of labor between the cells in multicelluar organism lead to entities with cells acting as neurons in the first clams (the red on the left), and these neurons allowed the clams to open and close at the right time. After only 200 million years, tribolites appeared the first organisms with dense neural structures that could be called brains appeared (the black on the left), and then after about 300 million years, multicelluar organisms as complex as bees appeared (the olive on the left), and these were social insects, with division of labor among individuals in a population, with queens, drones, worker bees. So 200 million years ago, over 13B years after the big bang, the ecology of living entities is well established on planet earth, including social entities with brains and division of labor between individuals in a population…. Living in colonies that some have compared to human cities – where thousands of individuals live in close proximity and divide up the work that needs to be done to help the colony survive through many, many generations of individuals that come and go. Bees are still hear today. And their wingless cousins, called ants, have taken division of labor to incredible levels of complexity in ant cities in nearly every ecological niche on the planet, except under water. Now let’s look at the human ecology,and the formation of service system entities and value-cocreation mechanisms, a small portion of which is represented by the colored bar on the right. Recall bees appeared about 200 million years ago, a small but noticeable fraction of the age of the universe. Now take 1% of this little olive slice, which is 2 million years… that is how long people have been on earth, just one percent of this little olive slice here. What did people do in most of that 2million years? Basically, they spread out to every corner of the planet, and changed their skin color, eye colors, and hair colors, they spread out and became diverse with many different appearances and languages. It took most of that 200 millions just to spread out and cover most of the planet with people. When there was no more room to spread out the density of people in regions went up…. Now take 1% of that 2million years of human history which basically involved spreading out to every corner of the planet and becoming more diverse, recall ecology is the study of abundance and distribution and types of interactions, and 1% of that 2million years is just 20,000 years, and now divide that in half and that represents 10,000 years. The bar on the right represents 10,000 years or just 500 generations of people, if a generation is about 20 years. 500 generations ago humans built the first cities, prior to this there were no cities so the roughly 5M people spread out around the world 0% lived in cities, but about 500 generations ago the first cities formed, and division of labor and human-made service interactions based on division of labor took off – this is our human big bang – the explosion of division of labor in cities. Cities were the big bang for service scientists, because that is when the diversity of specialized roles and division of labor, which is at the heart of a knowledge-based service economy really begins to take off... So cities are the first really important type of human-made service system entities for service scientists to study, the people living in the city, the urban dwellers or citizens are both customers of and providers of service to each other, and division of labor is the first really important type of human-made value-cocreation mechanism for service scientists to study. (Note families are a very important type of service system entity, arguably more important than cities and certainly much older – however, family structure is more an evolution of primate family structure – and so in a sense is less of a human-made service system entity and more of an inherited service system entity… however, in the early cities often the trades were handed down father to son, and mother to daughter as early service businesses were often family run enterprises in which the children participated – so families specialized and the family names often reflect those specialization – for example, much later in England we get the family names like smith, mason, taylor, cooper, etc.) So to a service scientist, we are very excited about cities as important types of service system entities, and division of labor as an important type of value-cocreation mechanism, and all this really takes off in a big way just 500 generations ago when the world population was just getting to around 5M people spread out all around the world – so 10,000 years about about 1% of the worlds population was living in early versions of cities. It wasn’t until 1900 that 10% of the world’s then nearly 2B people lived in cities, and just this last decade that 50% of the worlds 6B people lived in cities, and by 2050 75% of the worlds projected 10B population will be urban dwellers. If there is a human-made service system that we need to design right, it is cities. It should be noted that the growth of what economist call the service sector, parallels almost exactly the growth of urban population size and increased division-of-labor opportunities that cities enable – so in a very real sense SERVICE GROWTH IS CITY GROWTH OR URBAN POPULATION GROWTH… in the last decade service jobs passed agriculture jobs for the first time, and urban dwellers passed rural dwellers for the first time. But I am starting to get ahead of myself, let’s look at how the human-made ecology of service system entities and value-cocreation mechanisms evolved over the last 10,000 years or 500 generations. The population of artifacts with written language on them takes off about 6000 years ago or about 300 generations ago (the yellow bar on the right). Expertise with symbols helped certain professions form – and the first computers were people writing and processing symbols - scribes were required, another division of labor – so the service of reading and writing, which had a limited market at first began to emerge to help keep better records. Scribes were in many ways the first computers, writing and reading back symbols – and could remember more and more accurately than anyone else. Written laws (blue on right) that govern human behavior in cities takes off about 5000 years ago – including laws about property rights, and punishment for crimes. Shortly there after, coins become quite common as the first type of standard monetary and weight measurement system (green on right). So legal and economic infrastructure for future service system entities come along about 5000 years ago, or 250 generations ago, with perhaps 2% of the population living in cities…. (historical footnote: Paper money notes don’t come along much until around about 1400 years ago – bank notes, so use of coins is significantly older than paper money, and paper money really required banks as service system entities before paper money could succeed.). About 50 generations ago, we get the emergence of another one of the great types of service system entities – namely universities (light blue line) – students are the customers, as well as the employers that need the students. Universities help feed the division of labor in cities that needed specialized skills, including the research discipline skills needed to deepen bodies of knowledge in particular discipline areas. The red line indicates the population of printing presses taking off in the world, and hence the number of books and newspapers. This was only about 500 years or 25 generations ago. Now university faculty and students could more easily get books, and cities began to expand as the world’s population grew, and more cities had universities as well. The black line indicates the beginning of the industrial revolution about 200 years ago, the sream engine, railroads, telegraph and proliferation of the next great type of service system entity – the manufacturing businesses - that benefited from standard parts, technological advances and scale economies, and required professional managers and engineers. About 100 years ago, universities began adding business schools to keep up with the demand for specialized business management skills, and many new engineering disciplines including civil engineering, mechanical engineering, chemical engineering, and electrical engineering, fuel specialization and division of labor. By 1900, just over 100 years ago, or 5 generations ago 10% of the worlds population, or about 200 million people were living in cities and many of those cities had universities or were starting universities. Again fueling specialization, division of labor, and the growth of service as a component of the economy measured by traditional economists. Finally, just 60 years ago or 3 generations ago, the electronic semiconductor transistor was developed (indicated by the olive colored line on the right), and the information age took off, and many information intensive service activities could now benefit from computers to improve technology (e.g., accounting) and many other areas. So to recap, cities are one of the oldest and most important type of service system and universities are an important and old type of service system, as well as many types of businesses. Service science is the study of service system entities, their abundance and distribution, and their interactions. Division of labor is one of the most important types of value cocreation mechanisms, and people often need specialized skills to fill roles in service systems. Service science like ecology studies entities and their interactions over successive generations. New types of human-made service system entities and value-cocreation mechanisms continue to form, like wikipedia and peer production systems. Age of Unvierse (Wikipedia) The age of the universe is the time elapsed between the Big Bang and the present day. Current theory and observations suggest that the universe is 13.75 ±0.17 billion years old. [1] Age of Sun The Sun was formed about 4.57 billion years ago when a hydrogen molecular cloud collapsed. [85] Solar formation is dated in two ways: the Sun's current main sequence age, determined using computer models of stellar evolution and nucleocosmochronology , is thought to be about 4.57 billion years. [86] This is in close accord with the radiometric date of the oldest Solar System material, at 4.567 billion years ago. [87] [88] Age of Earth The age of the Earth is around 4.54 billion years (4.54 × 109 years ± 1%). [1] [2] [3] This age has been determined by radiometric age dating of meteorite material and is consistent with the ages of the oldest-known terrestrial and lunar samples . The Sun , in comparison, is about 4.57 billion years old , about 30 million years older. Age of Bacteria (Uni-cellular life) The ancestors of modern bacteria were single-celled microorganisms that were the first forms of life to develop on earth, about 4 billion years ago. For about 3 billion years, all organisms were microscopic, and bacteria and archaea were the dominant forms of life. [22] [23] Although bacterial fossils exist, such as stromatolites , their lack of distinctive morphology prevents them from being used to examine the history of bacterial evolution, or to date the time of origin of a particular bacterial species. However, gene sequences can be used to reconstruct the bacterial phylogeny , and these studies indicate that bacteria diverged first from the archaeal/eukaryotic lineage. [24] The most recent common ancestor of bacteria and archaea was probably a hyperthermophile that lived about 2.5 billion–3.2 billion years ago. [25] [26] Cities (Wikipedia) Early cities developed in a number of regions of the ancient world. Mesopotamia can claim the earliest cities, particularly Eridu, Uruk, and Ur. After Mesopotamia, this culture arose in Syria and Anatolia, as shown by the city of Çatalhöyük (7500-5700BC). Writing (Wikipedia) Writing is an extension of human language across time and space. Writing most likely began as a consequence of political expansion in ancient cultures, which needed reliable means for transmitting information, maintaining financial accounts, keeping historical records, and similar activities. Around the 4th millennium BC, the complexity of trade and administration outgrew the power of memory, and writing became a more dependable method of recording and presenting transactions in a permanent form [2] . In both Mesoamerica and Ancient Egypt writing may have evolved through calendrics and a political necessity for recording historical and environmental events. Written Law (Wikipedia) The history of law is closely connected to the development of civilization . Ancient Egyptian law, dating as far back as 3000 BC, contained a civil code that was probably broken into twelve books. It was based on the concept of Ma'at , characterised by tradition, rhetorical speech, social equality and impartiality. [81] [82] By the 22nd century BC, the ancient Sumerian ruler Ur- Nammu had formulated the first law code , which consisted of casuistic statements ("if ... then ..."). Around 1760 BC, King Hammurabi further developed Babylonian law , by codifying and inscribing it in stone. Hammurabi placed several copies of his law code throughout the kingdom of Babylon as stelae , for the entire public to see; this became known as the Codex Hammurabi . The most intact copy of these stelae was discovered in the 19th century by British Assyriologists, and has since been fully transliterated and translated into various languages, including English, German, and French. [83] Money (Wikipedia) Many cultures around the world eventually developed the use of commodity money . The shekel was originally both a unit of currency and a unit of weight. [10] . The first usage of the term came from Mesopotamia circa 3000 BC. Societies in the Americas, Asia, Africa and Australia used shell money – usually, the shell of the money cowry ( Cypraea moneta ) were used. According to Herodotus , and most modern scholars, the Lydians were the first people to introduce the use of gold and silver coin . [11] It is thought that these first stamped coins were minted around 650–600 BC. [12] Universities (Wikipedia) Prior to their formal establishment, many medieval universities were run for hundreds of years as Christian cathedral schools or monastic schools ( Scholae monasticae ), in which monks and nuns taught classes; evidence of these immediate forerunners of the later university at many places dates back to the 6th century AD. [7] The first universities were the University of Bologna (1088), the University of Paris (c. 1150, later associated with the Sorbonne ), the University of Oxford (1167), the University of Palencia (1208), the University of Cambridge (1209), the University of Salamanca (1218), the University of Montpellier (1220), the University of Padua (1222), the University of Naples Federico II (1224), the University of Toulouse (1229). [8] [9] Printing and Books (Wikipedia) Johannes Gutenberg's work on the printing press began in approximately 1436 when he partnered with Andreas Dritzehn—a man he had previously instructed in gem-cutting—and Andreas Heilmann, owner of a paper mill. [34] However, it was not until a 1439 lawsuit against Gutenberg that an official record exists; witnesses' testimony discussed Gutenberg's types, an inventory of metals (including lead), and his type molds. [34]
  • The reasonable questions: What is a service system? What is service science?

Service science intro 20110606 v1 Service science intro 20110606 v1 Presentation Transcript

  • Introduction to Service Science Dr. James (“Jim”) C. Spohrer [email_address] Innovation Champion and Director, IBM University Programs WW To Educational Policy Thinkers June 29th, 2011, Washington DC 500+ service science related courses and degree programs worldwide
  • Outline
    • Service science
      • Service systems thinking: The ABC’s
      • Service systems dynamics: Four drivers of change
      • Service systems re-design: Some examples
        • A College Course
        • K-12 & Higher Education
          • Higher Education Specialization Opportunities (Depth)
          • K-12 General Education Preparation (Breadth)
          • The Goal: Adaptive “T-shaped professionals” (ready for life-long learning)
    • Why? Data and trends
      • Why and how technology is changing jobs
      • Why higher education & certification levels matter (to individuals)
      • And therefore, why higher education matters (to nations)
      • Why the study of service systems matters (to nations)
      • Why the study of service systems matters (to businesses)
    • End Notes
      • The birth of service science
      • What about advanced manufacturing, outsourcing, sustainability challenges?
        • Holistic-product-service-systems, regional capacity, regional innovation ecosystems
      • Learning more about service systems - pointers to 200+ books & conceptual foundations
  • Service Systems Thinking
    • Example Provider: College (A)
    • Example Target: Student (C)
    • Discuss: Who is the Customer (B)?
    • Student?
    • Parents?
    • Future Employers?
    • Professional Associations?
    • Government, Society?
    • A. Service Provider
    • Individual
    • Institution
    • Public or Private
    • C. Service Target: The reality to be
    • transformed or operated on by A,
    • for the sake of B
    • People or Individuals, dimensions of
    • Business or Institutions, dimensions of
    • Product or Tech/Environment, physical dimensions
    • Information or Knowledge, symbolic dimensions
    • B. Service Customer
    • Individual
    • Institution
    • Public or Private
    Forms of Ownership Relationship (B on C) Forms of Service Relationship (A & B co-create value) Forms of Responsibility Relationship (A on C) Forms of Service Interventions (A on C, B on C) Spohrer, J., Maglio, P. P., Bailey, J. & Gruhl, D. (2007). Steps toward a science of service systems. Computer, 40 , 71-77. Vargo, S. L. & Lusch, R. F. (2004). Evolving to a new dominant logic for marketing. Journal of Marketing, 68 , 1 – 17. “ Service is the application of competence for the benefit of another entity.”
  • Service System Dynamics: Four Key Drivers of Change
    • Provider: Technology (Tech) & Business Models (Service Systems)
      • New technology to boost productivity & capacity (innovate)
      • Use technology to perform routine manual, cognitive, and transactional work
      • New business models and new ventures (for-profit & non-profits)
    • Customer: Self Service
      • New self-service options to lower costs & expand choice (educate)
    • Authority: Rules
      • New rules to fix problems & achieve policy goals (regulate)
      • Institutional diversity and governance of resource commons (Ostrom et. al.)
    • Competitors: Rankings
      • New rankings to guide decision-making & gain “valued” customers (differentiate)
      • Calculating customer lifetime value (Rust et. al.)
  • Example Service System Re-Design: A College Course
    • Problem: What if a college course had…
      • Input: Student quality lower
      • Process: Faculty motivation lower
      • Output: Industry fit lower
    • Solution: Tech + Self-Service
      • E: -20% E-learning enrollment pre-certification
      • F. +10% Faculty interest tuning
      • J. +10% on-the-Job skills tuning
    After a decade the course may look quite different Service systems are learning systems: productivity, quality, compliance, sustainable innovation Maglio, P., Srinivasan, S., Kreulen, J.T., Spohrer, J. (2006), Service systems, service scientists, SSME, and innovation. Communications of the ACM, 49(7), 81-85. Year 1: 20% Year 2: 20% Year 3: 20% Year N: 20% . . . . . . . . E F J
  • Example: Specialization Opportunities for Higher Education disciplines systems Systems that focus on flows of things Systems that govern Systems that support people’s activities transportation & supply chain water & waste food & products energy & electricity building & construction healthcare & family retail & hospitality banking & finance ICT & cloud education &work city secure state scale nation laws social sciences behavioral sciences management sciences political sciences learning sciences cognitive sciences system sciences information sciences organization sciences decision sciences run professions transform professions innovate professions e.g., econ & law e.g., marketing e.g., operations e.g., public policy e.g., game theory and strategy e.g., psychology e.g., industrial eng. e.g., computer sci e.g., knowledge mgmt e.g., stats & design e.g., knowledge worker e.g., consultant e.g., entrepreneur stakeholders Customer Provider Authority Competitors resources People Technology Information Organizations change History (Data Analytics) Future (Roadmap) value Run Transform (Copy) Innovate (Invent) Starting Point 1: Observing the Stakeholders (As-Is) Starting Point 2: Observing their Resources & Access (As-Is) Change Potential: Thinking (Has-Been & Might-Become) Value Realization: Doing (To-Be)
  • K-12 STEM: “The systems we live in, and the systems we are…” “ Imagine a better service system, and use STEM language to explain why it is better” STEM = Science, Technology, Engineering, and Mathematics See NAE K-12 engineering report: http://www.nap.edu/catalog.php?record_id=12635 See Challenge-Based Learning: http://www.nmc.org/news/nmc/nmc-study-confirms-effectiveness-challenge-based-learning
    • Challenge-based Project to Design Improved Service Systems
      • K - Transportation & Supply Chain
      • 1 - Water & Waste Recycling
      • 2 - Food & Products (Nano)
      • 3 - Energy & Electric Grid
      • 4 – Information /ICT & Cloud (Info)
      • 5 - Buildings & Construction
      • 6 – Retail & Hospitality/Media & Entertainment (tourism)
      • 7 – Banking & Finance/Business & Consulting
      • 8 – Healthcare & Family Life/Home (Bio)
      • 9 – Education /Campus & Work Life/Jobs & Entrepreneurship (Cogno)
      • 10 – City (Government)
      • 11 – State /Region (Government)
      • 12 – Nation (Government)
      • Higher Ed – T-shaped depth added, cross-disciplinary project teams
      • Professional Life – Adaptive T-shaped life-long-learning & projects
    Systems that focus on Governing Systems that focus on Human Activities and Development Systems that focus on Flow of things
  • The Goal: Adaptive T-shaped professionals Ready for Life-Long-Learning Ready for T-eamwork SSME+D = Service Science, Management, Engineering + Design Many disciplines (understanding & communications ) Many systems (understanding & communications) Deep in one discipline (analytic thinking & problem solving) Deep in one system (analytic thinking & problem solving) Many multi-cultural-team service projects completed (resume: outcomes, accomplishments & awards) BREADTH DEPTH
  • Data: Why and how technology is changing jobs Levy, F, & Murnane, R. J. (2004). The New Division of Labor: How Computers Are Creating the Next Job Market. Princeton University Press. Expert Thinking Complex Communication Routine Manual Non-routine Manual Routine Cognitive
  • Data: Why education certification levels matter (to individuals) … But it can be costly, American student loan debt is over $900M
  • Data: And therefore, why higher education matters (to nations) % WW GDP and % WW Top-500-Universities Strong Correlation (2009 Data): National GDP and University Rankings http://www.upload-it.fr/files/1513639149/graph.html
  • Data: Why the study of service systems matters (to nations) Parallels the growth of cities and the digital knowledge economy High Talent Individuals High Tech Infrastructure 42% 64 33 3 1.4 Germany 37% 26 11 63 2.1 Bangladesh 19% 20 10 70 1.6 Nigeria 45% 67 28 5 2.2 Japan 64% 69 21 10 2.4 Russia 61% 66 14 20 3.0 Brazil 34% 39 16 45 3.5 Indonesia 23% 76 23 1 5.1 U.S. 35% 23 17 60 14.4 India 142% 29 22 49 25.7 China 40yr Service Growth S % G % A % Labor % WW Nation World’s Large Labor Forces A = Agriculture, G = Goods, S = Service 2010 2010 CIA Handbook, International Labor Organization Note: Pakistan, Vietnam, and Mexico now larger LF than Germany US shift to service jobs (A) Agriculture: Value from harvesting nature (G) Goods: Value from making products (S) Service: Value from IT augmented workers in smarter systems that create benefits for customers and sustainably improve quality of life.
  • Data: Why the study of service systems matters (to businesses) SOFTWARE SYSTEMS (AND FINANCING) SERVICES 2010 Pretax Income Mix Revenue Growth by Segment Services Software Systems 44% 17% 39% IBM Annual Reports
  • Stakeholder Priorities Education Research Business Government Service Systems Customer-provider interactions that enable value cocreation Dynamic configurations of resources: people, technologies, organisations and information Increasing scale, complexity and connectedness of service systems B2B, B2C, C2C, B2G, G2C, G2G service networks Service Science To discover the underlying principles of complex service systems Systematically create, scale and improve systems Foundations laid by existing disciplines Progress in academic studies and practical tools Gaps in knowledge and skills Develop programmes & qualifications Service Innovation Growth in service GDP and jobs Service quality & productivity Environmental friendly & sustainable Urbanisation & aging population Globalisation & technology drivers Opportunities for businesses, governments and individuals Skills & Mindset Knowledge & Tools Employment & Collaboration Policies & Investment Develop and improve service innovation roadmaps, leading to a doubling of investment in service education and research by 2015 Encourage an interdisciplinary approach The white paper offers a starting point to - The Birth of Service Science: A Framework for Progress ( http://www.ifm.eng.cam.ac.uk/ssme/ ) Source: Workshop and Global Survey of Service Research Leaders (IfM & IBM 2008) Glossary of definitions, history and outlook of service research, global trends, and ongoing debate 1. Emerging demand 2. Define the domain 3. Vision and gaps 4. Bridge the gaps 5. Call for actions
  • Stakeholder Priorities Education Research Business Government Service Systems Customer-provider interactions that enable value cocreation Dynamic configurations of resources: people, technologies, organisations and information Increasing scale, complexity and connectedness of service systems B2B, B2C, C2C, B2G, G2C, G2G service networks Service Science To discover the underlying principles of complex service systems Systematically create, scale and improve systems Foundations laid by existing disciplines Progress in academic studies and practical tools Gaps in knowledge and skills Develop programmes & qualifications Service Innovation Growth in service GDP and jobs Service quality & productivity Environmental friendly & sustainable Urbanisation & aging population Globalisation & technology drivers Opportunities for businesses, governments and individuals Skills & Mindset Knowledge & Tools Employment & Collaboration Policies & Investment Develop and improve service innovation roadmaps, leading to a doubling of investment in service education and research by 2015 Encourage an interdisciplinary approach The white paper offers a starting point to - The Birth of Service Science: IBM Centennial Icon of Progress ( http://www.ifm.eng.cam.ac.uk/ssme/ ) Source: Workshop and Global Survey of Service Research Leaders (IfM & IBM 2008) Glossary of definitions, history and outlook of service research, global trends, and ongoing debate 1. Emerging demand 2. Define the domain 3. Vision and gaps 4. Bridge the gaps 5. Call for actions
  • What about advanced manufacturing? http://www.youtube.com/watch?v=nd5WGLWNllA
  • Rethinking “Product-Service Systems” F B Service System Entity Product-Service-System B F SSE B F SSE B F SSE B F SSE B F SSE B F SSE B F SSE B F SSE B F SSE B F SSE B F F F B B Service Business Product Business Front-Stage Marketing/Customer Focus Back-Stage Operations/Provider Focus Based on Levitt, T (1972) Production-line approach to service. HBR. e.g., IBM e.g., Citibank “ Everybody is in service... Something is wrong… The industrial world has changed faster than our taxonomies.”.
  • Holistic Product-Service-Systems & Regional Innovation Ecosystems http://www.service-science.info/archives/1056
    • Examples: Nations, States, Cities, Universities, Luxury Hotels, Cruise Ships, Households
    • “ Whole Service” Subsystems: Transportation, Water, Food, Energy, Communications, Buildings, Retail, Finance, Health, Education, Governance, etc.
    • Definition: A service system that can support its primary populations, independent of all external service systems, for some period of time, longer than a month if necessary, and in some cases, indefinitely
    • Balance independence with interdependence, without becoming overly dependent (outsourcing limits, maximum re-cycling for sustainability)
    ~25-50% of start-ups are new IT-enabled service offerings SaaS PaaS IaaS http://www.thesrii.org Nation State/Province City/Region Hospital Medical Research University Colleges K-12 Luxury Resort Hotels Family (household ) Person (professional ) For-profits Non-profits Start-Ups New Ventures
  • Learning More About Service Systems…
    • Fitzsimmons & Fitzsimmons
      • Graduate Students
      • Schools of Engineering & Businesses
    • Teboul
      • Undergraduates
      • Schools of Business & Social Sciences
      • Busy execs (4 hour read)
    • Ricketts
      • Practitioners
      • Manufacturers In Transition
    • And 200 other books…
      • Zeithaml, Bitner, Gremler; Gronross, Chase, Jacobs, Aquilano; Davis, Heineke; Heskett, Sasser, Schlesingher; Sampson; Lovelock, Wirtz, Chew; Alter; Baldwin, Clark; Beinhocker; Berry; Bryson, Daniels, Warf; Checkland, Holwell; Cooper,Edgett; Hopp, Spearman; Womack, Jones; Johnston; Heizer, Render; Milgrom, Roberts; Norman; Pine, Gilmore; Sterman; Weinberg; Woods, Degramo; Wooldridge; Wright; etc.
    • URL: http://www.cob.sjsu.edu/ssme/refmenu.asp
    • Reaching the Goal: How Managers Improve a Services Business Using Goldratt’s Theory of Constraints
    • By John Ricketts, IBM
    • Service Management: Operations, Strategy, and Information Technology
    • By Fitzsimmons and Fitzsimmons, UTexas
    • Service Is Front Stage: Positioning services for value advantage
    • By James Teboul, INSEAD
  • Service Science: Conceptual Framework
    • Resources: Individuals, Institutions, Infrastructure, Information
    • Stakeholders: Customers, Providers, Authorities, Competitors
    • Measures: Quality, Productivity, Compliance, Sustainable Innovation
    • Access Rights: Own, Lease, Shared, Privileged
    Ecology (Populations & Diversity) Entities (Service Systems, both Individuals & Institutions) Interactions (Service Networks, link, nest, merge, divide) Outcomes (Value Changes, both beneficial and non-beneficial) Value Proposition (Offers & Reconfigurations/ Incentives, Penalties & Risks) Governance Mechanism (Rules & Constraints/ Incentives, Penalties & Risks) Access Rights (Relationships of Entities) Measures (Rankings of Entities) Resources (Competences, Roles in Processes, Specialized, Integrated/Holistic) Stakeholders (Processes of Valuing, Perspectives, Engagement) Identity (Aspirations & Lifecycle/ History) Reputation (Opportunities & Variety/ History) prefer sustainable non-zero-sum outcomes, i.e., win-win win-win lose-lose win-lose lose-win
  • Service system entities configure four types of resources
    • First foundational premise of service science:
      • Service system entities dynamically configure four types of resources
      • Resources are the building blocks of entity architectures
    • Named resources are:
      • Physical or
      • Not-Physical
      • Physicist resolve disputes
    • Named resources have:
      • Rights or
      • No Rights
      • Judges resolve disputes
    Spohrer, J & Maglio, P. P. (2009) Service Science: Toward a Smarter Planet. In Introduction to Service Engineering. Editors Karwowski & Salvendy. Wiley. Hoboken, NJ. . Formal service systems can contract to configure resources/apply competence Informal service systems can promise to configure resources/apply competence Trends & Countertrends (Balance Chaos & Order): (Promise) Informal <> Formal (Contract) (Relationships & Attention) Social <> Economic (Money & Capacity) (Power) Political <> Legal (Rules) (Evolved) Natural <> Artificial (Designed) (Creativity) Cognitive Labor <> Information Technology (Routine) (Dance) Physical Labor <> Mechanical Technology (Routine) (Atoms) Transportation <> Communication (Bits) (Tacit) Qualitative <> Quantitative (Explicit) (Secret) Private <> Public (Shared) (Anxiety-Risk) Challenge <> Routine (Boredom-Certainty) (Mystery) Unknown <> Known (Justified True Belief) Physical Not-Physical Rights No-Rights 2. Technology/ Environment Infrastructure 4. Shared Information/ Symbolic Knowledge
    • People/ Individuals
    3. Organizations/ Institutions
  • Service system entities calculate value from multiple stakeholder perspectives
    • Second foundational premise of service science
      • Service system entities calculate value from multiple stakeholder perspectives
      • Value propositions are the building blocks of service networks
    • A value propositions can be viewed as a request from one service system to another to run an algorithm (the value proposition) from the perspectives of multiple stakeholders according to culturally determined value principles.
    • The four primary stakeholder perspectives are: customer, provider, authority, and competitor
    Spohrer, J & Maglio, P. P. (2009) Service Science: Toward a Smarter Planet. In Introduction to Service Engineering. Editors Karwowski & Salvendy. Wiley. Hoboken, NJ. . Value propositions coordinate & motivate resource access Model of competitor: Does it put us ahead? Can we stay ahead? Does it differentiate us from the competition? Will we? (invest to make it so) Strategic Sustainable Innovation (Market share) 4.Competitor (Substitute) Model of authority: Is it legal? Does it compromise our integrity in any way? Does it create a moral hazard? May we? (offer and deliver it) Regulated Compliance (Taxes and Fines, Quality of Life) 3.Authority Model of self: Does it play to our strengths? Can we deliver it profitably to customers? Can we continue to improve? Can we? (deliver it) Cost Plus Productivity (Profit, Mission, Continuous Improvement, Sustainability) 2.Provider Model of customer: Do customers want it? Is there a market? How large? Growth rate? Should we? (offer it) Value Based Quality (Revenue) 1.Customer Value Proposition Reasoning Basic Questions Pricing Decision Measure Impacted Stakeholder Perspective (the players)
  • Service system entities reconfigure access rights to resources by mutually agreed to value propositions
    • Third foundational premise of service science
      • Service system entities reconfigure access rights to resources by mutually agreed to value propositions
      • Access rights are the building blocks of the service ecology (culture and information)
    • Access rights
      • Access to resources that are owned outright (i.e., property)
      • Access to resource that are leased/contracted for (i.e., rental car, home ownership via mortgage, insurance policies, etc.)
      • Shared access (i.e., roads, web information, air, etc.)
      • Privileged access (i.e., personal thoughts, inalienable kinship relationships, etc.)
    service = value-cocreation B2B B2C B2G G2C G2B G2G C2C C2B C2G *** provider resources Owned Outright Leased/Contract Shared Access Privileged Access customer resources Owned Outright Leased/Contract Shared Access Privileged Access OO SA PA LC OO LC SA PA S A P C Competitor Provider Customer Authority value-proposition change-experience dynamic-configurations (substitute) time
  • Service system entities interact to create ten types of outcomes
    • Four possible outcomes from a two player game
    • ISPAR generalizes to ten possible outcomes
      • win-win: 1,2,3
      • lose-lose: 5,6, 7, maybe 4,8,10
      • lose-win: 9, maybe 8, 10
      • win-lose: maybe 4
    lose-win (coercion) win-win (value-cocreation) lose-lose (co-destruction) win-lose (loss-lead) Win Lose Provider Lose Win Customer ISPAR descriptive model
  • Service system entities learn to systematically exploit info & tech March, J.G.  (1991)  Exploration and exploitation in organizational learning.  Organizational Science. 2(1).71-87. Sanford, L.S. (2006) Let go to grow: Escaping the commodity trap. Prentice Hall. New York, NY. L Learning Systems (“Choice & Change”) Exploitation (James March) Exploration (James March) Run/Practice-Reduce (IBM) Transform/Follow (IBM) Innovate/Lead (IBM) Operations Costs Maintenance Costs Incidence Planning & Response Costs (Insure) Incremental Radical Super-Radical Internal External Interactions “ To be the best, learn from the rest” “ Double monetize, internal win and ‘sell’ to external” “ Try to operate inside the comfort zone”
  • Service system entities are physical-symbol systems
    • Service is value cocreation.
    • Service system entities reason about value.
    • Value cocreation is a kind of joint activity.
    • Joint activity depends on communication and grounding.
    • Reasoning about value and communication are (often) effective symbolic processes.
  • Summary Spohrer, J & Maglio, P. P. (2009) Service Science: Toward a Smarter Planet. In Introduction to Service Engineering. Editors Karwowski & Salvendy. Wiley. Hoboken, NJ. . 5. Exploit information & technology 6. Physical-Symbol Systems Physical Not-Physical Rights No-Rights 2. Technology 4.. Shared Information 1. People 3. Organizations 1. Dynamically configure resources Model of competitor: Does it put us ahead? Will we? Strategic Sustainable Innovation 4.Competitor Model of authority: Is it legal? May we? Regulated Compliance 3.Authority Model of self: Does it play to our strengths? Can we? Cost Plus Productivity 2.Provider Model of customer: Do customers want it? Should we? Value Based Quality 1.Customer Reasoning Questions Pricing Measure Impacted Stakeholder Perspective 2. Value from stakeholder perspectives S A P C 3. Reconfigure access rights 4. Ten types of outcomes (ISPAR)
  • Smarter = Sustainable Innovation (reduce waste, expand capabilities) Computational System Building Smarter Technologies Requires investment roadmap Service Systems: Stakeholders & Resources 1. People 2. Technology 3. Shared Information 4. Organizations connected by win-win value propositions Building Smarter Universities & Cities Requires investment roadmap
  • Time ECOLOGY 14B Big Bang (Natural World) 10K Cities (Human-Made World) Sun writing (symbols and scribes) Earth written laws bacteria (uni-cell life) sponges (multi-cell life) money (coins) universities clams (neurons) trilobites (brains) printing press (books) steam engine Where is the “Real Science” or mystery to explain? In the interdisciplinary sciences that study the natural and human-made worlds… Unraveling the mystery of evolving hierarchical-complexity in new populations… To discover the world’s architectures and mechanisms for computing non-zero-sum Entity Architectures (Є N ) of nested, networked Holistic Service Systems (HSS) 200M bees (social division-of-labor) 60 transistor
  • What is service science? A service system? The ABC’s? Economics & Law Design/ Cognitive Science Systems Engineering Operations Computer Science/ Artificial Intelligence Marketing “ a service system is a human-made system to improve provider-customer interactions and value-cocreation outcomes, studied by many disciplines, one piece at a time.” “ service science is the transdisciplinary study of service systems & value-cocreation” The ABC’s: The provider (A) and a customer (B) transform a target (C)