Proposed Service Science Research Landscape

Many individuals and groups are working to establish a research program and research projects in Service Science, Management, and Engineering or Service Science. These individuals and groups come from different research backgrounds and bring different perspectives and points of view to this emerging field.

The purpose of this blog post is to propose a research landscape which can help us situate service science research from across our varied disciplines. My hope is that, through this blog medium, we can collaborate to enhance and evolve the landscape so that it can serve several roles, including:

1. Help researchers understand how their research relates to existing service science research activities and that of specific researchers so that they may define effective collaborations;

2. Help researchers and project leaders determine which aspects of service science research are not addressed within a large research project or program; and

3. Help educators define service science curriculum and courses that cover specific aspects that are being addressed in service science research.

First I will provide some definitions, a practice which is extremely important when discussing topics that cross disciplines. For the context the proposed research landscape, “service” is defined independently of the notion of technology. In [1], a service is defined as “the application of competences for the benefit of another”. More broadly in [2], a service is defined as “the application of resources (including competences, skills and knowledge) to make changes that have value for another”.

A “service system” is defined as “a configuration of people, technologies, and other resources that interact with other service systems to create mutual value” [2].

By contrast, a “web service” is more narrowly defined as “a software system designed to support interoperable machine to machine interaction over a network” [3]. In the context of service oriented architectures (SOA), “services” are described as network-accessible software components that are aligned with business processes [4].

“Service Science” then is the study of the application of resources in one or more service systems to the benefit of another service system. Service Science is trying to develop a science of service systems and their interactions [2].

“Service Science, Management, and Engineering” (SSME) is sometimes used interchangeably with the term “service science” but it involves more than “service science” does. It includes applying management and engineering principles to services and has been defined as, “ the application of scientific, management, and engineering disciplines to tasks that one organization (service provider) beneficially performs for and with another (service client) [1].

Note that the definition of “services” has changed over time from meaning tasks that one performs for and with another in [1] to the application of resources for mutual benefit in [2]. This is evidence that the field is emerging and changing in such a way that it will benefit from having a landscape on which to ground various research activities.

The vision of service science remains boldly or ambitiously to be to create a coherent integrated body of knowledge to support ongoing innovation in service systems design, operation, and improvement [5]. A picture that has been used by IBM researchers to show the breadth of service science activities shows three layers:

The lowest level of this diagram represents the technical architecture, the middle layer defines work practices and on the top layer sits the services business. Research in service science or SSME spans these three different layers; thus, these three layers define one of the dimensions of the proposed landscape.

To articulate the other dimension of the proposed research landscape, we first look at the definition of a service system since research in service science requires researching service systems. A service system is defined as “a dynamic value co-creation configuration of resources, including people, organizations, shared information (language, laws, measures, methods), and technology, all connected internally and externally to other service systems by value propositions” [6].

Because organizations contain people and technology and information is shared through people and technology, the second dimension of the research landscape focuses on the people and technology resources in service systems.

Recall that a service is defined as the application of competence for the benefit of another entity. Services, therefore, involve at least two entities, one applying competence and another integrating the applied competences with other resources and determining benefit [6].

For benefit to be realized and competences to be applied, these two entities must interact in some way. The interaction could take place between two technological systems and be performed through web services. It could be that people in one entity are interacting with technology in another as in business to consumer e-commerce. Finally, it could be that technology is mediating people to people interactions such as when a researcher interacts through chat or email with a reference librarian to find information.

The second dimension of the proposed landscape, therefore, differentiates research as to whether it studies connections and interactions between people, between people and technology, or between technology and technology.

There are a couple of points to note about research that is situated within this landscape. First, the research may study interactions and sharing between two entities that are within the same organization or in different organizations. That aspect of the research is not differentiated on the landscape.

Second, the underlying goal of research that gets situated within this landscape has to explicitly address services as defined in [1] or [2]. In this way, we would not include research on the bottom level of this landscape picture that advances technology in a way that could simply be applied to service paradigms as well as being applied to several other paradigms. Rather, the research we situate on this landscape must study an effective and novel application of technology in new ways to enhance services or advances in technology that are motivated by specific kinds of services.

So for some examples of where research would fit within this proposed landscape, consider SOA and Web Services research which fits in the bottom to middle left side of the landscape. Two pieces of work I’ve collaborated on in virtual worlds fits in the upper right. And work I’ve collaborated on in understanding the structure of the social network in corporate blogs (technology mediated person to person interaction and sharing) fits in the middle right side of the landscape.

I think it’s important to realize that different kinds of business services may drive the research differently so I explicitly list 4 kinds on the landscape (large enterprise, small enterprise – although I’m not 100% sure there is a difference between them for the purposes of services research – government services, and non-profit services). Most of the work on theories of service science assume for-profit services and, while I haven’t looked at it very closely yet, I think it’s worthwhile to consider that some of the theories and definitions may not apply as well in non-profit services.

In a future blog post, I will describe how my current research activities fit within this landscape.

References:

[1] J. Spohrer, P. P. Maglio, J. Bailey, D. Gruhl, “Steps Toward a Science of Service Systems,” IEEE Computer, Jan. 2007

[2] J. Spohrer, S. L. Vargo, N. Caswell, and P. P. Maglio, “The Service System is the Basic Abstraction of Service Science”, Proceedings of the 41st HICSS, Jan. 2008

[3] W3C, http://www.w3.org/TR/ws-gloss/

[4] Wikipedia, SOAhttp://en.wikipedia.org/wiki/Service-oriented_architecture

[5] Kieliszewski, C., From a presentation at a meeting of the Alberta CAS (Center for Advanced Studies) Research Board Meeting, December 2007.

[6] Maglio, P., From a presentation at a CAS Alberta Workshop on Service Science, Management, and Engineering, March 2008.

ACM, ACM-W, and Great Advice

I was recently elected to the Council of the ACM for a 4 year term as one of 5 members-at-large. My initial decision to run is thanks to much encouragement from my colleague and mentor, Gabby Silberman. I’m extremely honoured to be serving with the tremendous talented people who were also elected and to be counted among those who have served on ACM Council in the past.

Some time ago, I joined the listserv for ACM-W (the ACM committee on Women in Computing). From the website, ACM-W “celebrates, informs and supports women in computing, and works with the ACM-W community of computer scientists, educators, employers and policy makers to improve working and learning environments for women”. I have benefited from being part of that community by reading with pleasure and pride the posts which share information, encouragement, and suggestions.

The first ACM-W newsletter was recently published and it is full of interesting profiles and articles. There is an interview with Fran Allen (first woman to win the ACM Turing Award) that I thought was terrific. I knew Fran when I was at IBM and have been a long time admirer of hers. She is an amazing mentor to so many people. I really like the advice Fran gives in her interview so wanted to point to it here: "Focus on your work, not your career – that will happen later; build professional networks; get multiple mentors and be a mentor; nearly all projects involve teams and there is evidence that diverse teams produce the best results, also they are the most interesting; have fun."

I think it’s great advice whether you are working in industry or in academia or going to school.

My Decision to Leave IBM

I was at IBM for 22 years ... I started on June 10, 1985 and my last day was November 30, 2007. I joined the University of Toronto Faculty of Information Studies in January 2008. I took Dec. "off" to regroup and get prepared emotionally.

I must say it was a big decision ... something I tried not to think too much about but instead went with my gut. I don't have tenure and came in at the Associate level so only have 3 years to get tenure. I try not to worry about this too much but it lurks in the back of my mind!

I joined IBM right after my undergrad but I knew I wanted to be an academic. I had also applied for scholarships and grad school. I received a Canadian gov't scholarship (NSERC Postgraduate Scholarship) that was deferrable for 2 years to go into industry so I took the job at IBM to get some experience (it was in the area of compiler development). I left after 2 years to pursue grad studies (my masters) and my (wise) manager at the time convinced me to take an educational leave of absence. I remember his reaction, “Never say never, Kelly. Things change. You’ll change,” when I told him I was never coming back. When I finished my masters and started my PhD, I went into IBM to resign but they extended my leave (that was almost 20 years ago -- I don't think it would be possible today). After my PhD, I wanted to have children and at the time looking for a faculty job seemed like a stressful process. I was offered and accepted a great job at IBM, had 2 wonderful children, and worked for 13 more years taking advantage of excellent opportunities and jobs I was given at IBM. Then (all of a sudden), I realized I had spent half my life with IBM (!) and I decided academia was now or never so I applied for academic jobs (I had built a lot of contacts in academia in Canada through my work at IBM so that helped).

And, here I am! It's pretty exciting and scarey all at once! People ask me what I miss the most about IBM and the answer is always, "the people" but fortunately, as an IBM CAS Faculty Fellow, I have the opportunity to stay in touch with and continue to interact with many of those tremendous people.

CASCON 2008 -- A Great Opportunity

Each year, IBM Toronto Centre for Advanced Studies and National Research Council Canada host a conference (CASCON) in Markham, Ontario. The conference is in the broad area of computer science and is considered to be the premier general international computer science conference held in Canada. It attracts international participation and over 1500 people usually attend over the course of 4 days. The first was held in 1991 and I have attended every one since. I started attending when I was a PhD student and I used the opportunity to “demo” my PhD research. The feedback I received from attendees was invaluable in the shaping of my thesis and results. I have also organized workshops and been a member of the Program Committee in the past (I’m on the Program Committee this year). In the last few years I was General Co-Chair so I’ll admit I am quite biased! But it really is a great opportunity for people whose work fits into one of the broad theme areas. Plus, it is free to attend and the lunches are delicious!

There are three main parts of the program: Academic papers (reviewed and selected by an international program committee with ~25% acceptance rate – papers are published in the ACM Digital Library); workshops and tutorials (my personal favourite part of the conference); and demos (another highlight). There are also very interesting and thought-provoking keynote speakers.

CASCON is called a “Meeting of Minds” because it aims to bring together academic researchers with practitioners and government researchers to meet and build collaborations. I highly encourage people (especially students) to take advantage of this local, free conference to showcase your work, engage in discussions, and meet new people.

You can participate as a contributor to CASCON by submitting a paper, organizing a workshop, or submitting a demo or poster. Or, you can participate as an attendee and attend any the workshops, demos, and paper presentations you wish. However, I highly recommend taking the opportunity to participate as a contributor – at least to put a poster or demo on display.

See the CASCON 2008 website for important dates, actual location, link to the call for papers, and description of topics of interest.

Great Pre-tenure Advice

I missed March!! I didn’t post anything to my blog in March. Well, technically, I did create a blog post because I set up a blog for my Service Science class where students could blog about an interesting service innovation that uses social computing technology. It was a huge success, each student blogging on something completely different. We all learned something new. So, I didn’t blog here but I blogged elsewhere.

I also missed posting something I really wanted to post about in February. On February 12, I attended an informal presentation by Professor and Vice Provost, Academic, Edith Hillan for women faculty who are pre-tenure which was hosted by her office and the Status of Women Office. It was a wicked cold day and there were fewer people there than expected but Professor Hillan delivered a great presentation, providing key tips for women faculty who are pre-tenure. She gave advice and suggestions based on her own experience and on the fact that she reviews between 100 and 150 tenure files per year. Here is what I took away from this very informative and useful event (the numbering and text are my own based on the notes I took during Dr. Hillan’s presentation):

1. Time and Task Management: she asked us to think about what we are doing to save time and provided suggestions:

a. Arrange your teaching so all classes meet on the same 2-3 days per week. You are only required to teach in 2 academic terms per year so don’t volunteer to teach in your “off” time. Make it very clear to students in your class which times you are available and set clear expectations about when they can expect a response from you (eg, within 48 hours). Don’t put off doing things that look too overwhelming (eg, the exams or papers you have to mark) – get started and make progress.

b. Set limits on the amount of time you spend on each thing. Set boundaries, stick to them, and say, “NO!” if necessary. Closely organize your work week. Work in brief, regular sessions instead of binges.

c. Don’t go for perfection!! This is a tough one for me because I’ve been practising being a perfectionist for over 45 years now!

d. Don’t always answer the phone or emails – let them go to the next day, or set up specific regular time when you deal with email and at other times, don’t. I tried this when I was at IBM for a while and it really does work but it is extremely hard for me to be disciplined about this (I, by habit, check email every few minutes).

e. Do double duty (also known as “leverage”). Find opportunities where your teaching links to research and where engagements with students (both undergrad and grad) link to your research. For example, co-author papers with students, and participate in service that gives you leverage somewhere else.

f. Take your holidays. This is an important one!

2. We talked about classes and teaching and she said that student responses to teaching are important so offered the following advice:

a. Make sure you are well prepared for classes. Provide good course outlines and bibliography. Present what will be covered at the start of the class.

b. Be very clear about what is expected from students (assignments, when they will be due, how they will be marked, how to contact you, etc.). She said the biggest complaint from students is that it wasn’t clear what was expected from them.

c. Leave time each lecture for student interaction and questions.

d. Take the pulse of student opinion mid-term and make adjustments. Show the students are you are interested in what they have to say. Clearly explain to students why they are completing final course evaluations and how it will affect your future.

e. Be open about your course being a “course in development” if it is one. But make sure you are able to teach courses again in the future (prepare once, reuse). Beg for and borrow course syllabi, exams, etc. from those who have taught the courses before.

3. We talked about service to the department through committees:

a. Try not to do too much committee work but you have to balance being a collaborative colleague with being a productive scholar and an effective teacher. Be a good department citizen.

b. Volunteer for the things you want to do then say “No!” to the others. Don’t wait to be invited if there is a committee you want to be on – ask for it.

c. Don’t try to “run the department” until after you have tenure! Similarly, don’t get involved in outside consulting until after tenure

d. She said a good committee to be on is the “PTR” committee (Thanks to Steve, I now know that stands for "Progress Through the Ranks"). The reason this committee was considered a good one was the fact that serving on it would help you understand what is needed to progress.

4. Research:

a. Make statements now to put in your dossier – your “story” – where you came from, where you are now, where you are going to go, research-wise. In your research statements, explain how you are building your program and where you are going next.

b. Publish, publish, publish (I think we all knew that one!)

c. Present at department seminars and organize seminars for your department, bringing in well-known researchers.

d. Manage your professional image. Develop a “marketable” record. View tenure as a political process: meet the candidates, the voters, ensure they know and understand your message.

e. Have regular conversations with your department chair or dean. Set objectives for the year and use these discussions to get feedback on those objectives.

f. Add something to your resume / CV every month (I love this one –it’s great advice).

5. Be assertive. This is an important piece of advice for many women I know. It applies in several of the points above with respect to committees, teaching, etc. In general, ask for things – don’t wait for things to be offered to you.

Multi-tasking and Context-Switching

Just a quick post as I haven't posted in a while and I have been thinking a lot about a lot of things but haven't had time to write anything down.

I have so many colleagues, friends, and mentors who have been in academia for years and years. They provide me with a lot of advice (almost all of it welcome) and suggestions. Just before I left IBM, one of my university colleagues told me that in academia I would find I was switching a lot between several different things -- more so than I did in industry. I remember thinking that could not be possible! At IBM, I switched between issues and topics every 30 minutes or so (back to back 30-60 min. meetings for 8 hours straight) with "sametime" (instant messages) and emails interrupting those 30-60 min. sessions for additional completely unrelated questions.

It's true that I switched more in IBM but it's also true that most of those switches were externally triggered (go to the next meeting now, respond to the urgent email request now, etc.). They were also easy to check of a list: that's done; that's done; next?

Now, I am switching between many different topics and activities (more so than I thought I would). In most cases, I have to schedule and initiate those switches. And because everything is so new, it takes me much longer to do some things than it should (or I tend to spend way too much time on some things than I should). And many of these activities are longer in duration and harder to declare as "done". Recently, in a faculty meeting, it was declared that we would meet weekly on the specific topic until we were done. A colleague remarked, "I just wish I knew what 'done' looked like!"

I actually enjoy switching between things. I have to get better at figuring out when to switch and when to keep going and, of course, when I'm "done" with something.

What is Service Science?

So, I’ve arrived here (at the University of Toronto) to embark on my scholarly and academic career. “So, what area are you in?” I’m asked. My first thought is, “I’m a computer scientist. I came from IBM. I’m interested in Service Science.” So, the next question is, “What’s Service Science?” Below I summarize what I think it is, why I’m interested, and briefly what (I think) I’m going to do next.

Service science (I am using this term – others may say “service science, management and engineering (SSME)” or simply “services”) is being called an emerging discipline. There is a big push in IBM and other companies to address this area and engage with academia to do so because the services sector (vs. manufacturing and agriculture) is the fastest growing segment of the economy in most if not all nations. Because of this significant economic shift and human labour migration, there is a claim that there is a need for organizations to be more systematic about services and services delivery; therefore, there is a need for research and innovation in services and for service science research and teaching programs to emerge (See Communications of the ACM July 2006 and IBM Systems Journal January 2008.

Programs are emerging in business schools, computer science and engineering schools, and through new multidisciplinary institutions. There are a host of others.

Establishing a research and teaching program in service science requires a multidisciplinary approach. It must combine knowledge about computing and technology with the social and cultural implications of how technology will be used in a specific business or societal service domain (or service system). I’m a computer scientist at heart and a proud member of the computer science community. I am very interested in how research advances in computer science can be made in order to impact something of importance (perhaps even change the world). I am fascinated by how these advances require understanding of and participation by people and society. Therefore, service science (as I understand it) is a very exciting area for me.

Most research to date has focused on service science with an underlying assumption that the service system or service is a business / profit service. Very broadly, I’m interested in service science in which the “business” domains are not-for-profit or community organizations. Most literature today assumes the services business is a profit-making entity. I will focus on the not-for-profit and community services organizations such as libraries, museums, healthcare facilities, etc. My initial investigations show that there are many interesting problems that come up in these contexts that are not prevalent in business environments.

So, that’s a start … within this framework, I’ve identified several interesting problems that I will blog about in future posts.