Wild horses sculpture at Drexel

Category: learning

  • Knowledge-Sharing In Collaboration Across Organizational Boundaries

    Knowledge-Sharing In In Collaboration Across Organizational Boundaries

    Susan Gasson
    College of Computing & Informatics,
    Drexel University

    Please cite this paper as:
    Gasson, S. (2007) ‘Knowledge-Sharing In Collaboration Across Organizational Boundaries.’  Working Paper.  Available from https://www.improvisingdesign.com/knowledge-sharing/ ‎ Last updated 08/15/23

    Sharing Knowledge in Collaborative Teams

    Knowledge-sharing in collaborative design is problematic, because it involves the merging of a variety of stakeholder perspectives to achieve a collective “vision” of what needs to be changed: the task objectives, the task goals and – even – the problem being addressed. We tend to assume that groups develop a common perspective on collaborative tasks over time, but there is quite a bit of research that demonstrates otherwise.

    The problem of collaboration is exacerbated when the collaboration spans organizational boundaries, such as groups that comprise members from different functions or divisions. People who work in different functional units not only tend to have diverse ways of defining organizational problems, that are related to their disciplinary and professional backgrounds, but also define problems and their solutions according to the local conventions of their department or function. A group of managers and participants in the work processes to be changed may have difficulty in agreeing what needs to change as they find that they have very little shared understanding of organizational problems – or how to resolve them. Each stakeholder defines the problems in a different way, depending on their experience of these problems and of the situation in which they occur (Gasson, 2004).

    Different subgroups of stakeholders may have shared understandings, that encompass a subset of the problem definition. These subsets often form the basis for political alliances, that emphasize specific aspects of the organizational problem-situation (Gasson, 2007). But knowledge about the actual problem, represented in Figure 1 by the union of the various perspectives (the bold outline), is difficult to represent and therefore to debate. Each stakeholder sees a different part of the problem, with different emphases and priorities, that are filtered through a different interpretation, based on their educational and work experience. So sharing knowledge – about how things work and what should or could be done – is difficult.

    Knowledge Convergence

    This is not an issue for simple, well-structured problems, that are easy to define. For example, if a group of stakeholders is designing a solution to the problem of reporting on what hours different employees work on different projects to which they are assigned, the problem is fairly easy to define and the solution follows from this problem definition. While there may be some “softer” aspects of the problem that need clarification (for example, how a “project” is defined, how employees can be expected to record the hours that they work, or cultural constraints of reporting on what various people work on), most aspects of the problem are straightforward and therefore easy to structure into a clear, consensus problem-definition. Over a period of working together, different stakeholders share their knowledge about a well-defined problem, to reach a clearly-defined domain of action. The degree of shared understanding can be increased, as trust between group members increases over time therefore very high.

    Wicked2

    Figure 1: Knowledge Convergence In Collaborative Work

    Not so for problems that are complex and ill-defined. A group of stakeholders who work together over time may be able to define the rationale for change and the context of the problem in a consensual way, but each member of the group will conceive of the problem and appropriate solutions in very different ways. The degree of shared knowledge possessed about the problem to be solved may not increase much from that shown in Figure 1. This is because organizational problems are “wicked” problems (Rittel, 1972). Wicked problems, according to Rittel and Webber (Rittel and Webber, 1973) have ten specific characteristics:

    1. Wicked problems have no definitive formulation. A problem can only be defined by exploring the type of solution required: problem and solution are interdependent. Each attempt at creating a solution changes the stakeholder’s understanding of the problem.
    2. Wicked problems have no stopping rule. Since you can’t define the problem, it’s difficult to tell when it’s resolved. The problem-solving process ends when resources are depleted, stakeholders lose interest or political realities change.
    3. Solutions to wicked problems are not true-or-false, but good-or-bad. Since there are no unambiguous criteria for deciding if the problem is resolved, getting all stakeholders to agree that a resolution is “good enough” can be challenging.
    4. There is no immediate or ultimate test of a solution to a wicked problem. Solutions to such problems generate waves of consequences, and it is impossible to know how these waves will eventually impact the situation. Wicked problems are interrelated (see point 8) and so resolving one problem may make another problem better or worse.
    5. Every implemented solution to a wicked problem has consequences. Once the Web site is published or the new customer service package goes live, you can’t take back what was online or revert to the former customer database, because customers have different expectations. So consequences not only relate to the original problem, but change the nature of the problem that now has to be resolved.
    6. Wicked problems do not have a single, well-defined set of potential solutions. Various stakeholders have differing views of acceptable solutions. It is a matter of judgment as to when enough potential solutions have emerged and which should be pursued. Alternative solutions may be just as good as the solution selected [1]. Alternative solutions may not exist.
    7. Each wicked problem is essentially unique. There are no “classes” of solutions that can be applied to a specific case. As Rittel and Webber wrote in “Dilemmas in a General Theory of Planning,” “Part of the art of dealing with wicked problems is the art of not knowing too early what type of solution to apply.” This moves us a long way away from the generalized ontology of the semantic web, or the pattern language proposed by Alexander (1999) [2].
    8. Each wicked problem can be considered a symptom of another problem. A wicked problem is a set of interlocking issues and constraints that change over time, embedded in a dynamic social context. So organizational problems are highly interrelated and resolving one problem in a particular way will affect other problems in unpredictable ways.
    9. The causes of a wicked problem can be explained in numerous ways. There are many stakeholders who will have various and changing ideas about what might be a problem, what might be causing it and how to resolve it. Problem resolution cannot be achieved through problem analysis, but must be achieved through “argumentation” (Rittel, 1972), where multiple views of the problem are debated and negotiated among stakeholders.
    10. The planner (designer) has no right to be wrong. Scientists are expected to formulate hypotheses, which may or may not be supportable by evidence. Designers don’t have such a luxury—they’re expected to get things right. Rittel (1972) argues that you cannot build a freeway to see how it works. Similarly, you cannot build an information system to see what type of IS you need [3].

    As a consequence, problem-solving and design groups tend to diverge, as much as they converge over time, in defining the problem that they are resolving. Design tends to proceed via a series of “breakdowns”, in which the current group consensus falls apart and a new consensus is formed around a mobilizing vision, that provides a good-enough definition of the problem to mediate negotiation and constructive argumentation (Gasson, Under Review).

    So What?

    We need new methods and approaches to manage IS design and collaborative problem-solving/innovation groups. Most current approaches are based on an individual model of problem-solving, that views problems as ill-structured (Simon, 1973). Ill-structured problems, while being ill-defined are capable of being structured, once a suitable problem-boundary and set of constraints have been agreed. But as I argued above, organizational problems are wicked problems and are therefore not amenable to objective definition or structuring. Approaches to wicked problem resolution [4] require techniques for surfacing people’s implicit assumptions, so that everyone is talking about the same elements of the problem. They require ways of managing multiple perspectives at once: recording constraints and solution requirements at multiple levels of decomposition, so that understanding of the problem is not “lost” when the group changes focus. They require ways for allocating responsibility for different parts of the problem to those familiar with those parts and for building trust so that these different views of a solution can be aligned, even if they are not shared. My research is about how these things can be achieved.

    I explore methods and processes for (a) sharing distributed information and knowledge, and (b) managing collaborative problem-solving and design activities in groups where knowledge-sharing is not feasible because the context and the problem are so diverse and “wicked”. Some of the issues that have arisen from this program of research so far are:

    Is the process goal-driven? Most views of problem-solving see this process as goal-driven, at least at a high-level. In other words, collaborative groups designing IT-related change derive a “common vision”. The findings from my prior research demonstrate that, for complex problems that span organizational groups and/or units, a common vision is highly unlikely to be shared. Group collaboration is impeded by continual revisiting of this vision, in the attempt to derive a common language for the project change goals.

    How do distributed groups assess their progress? In traditional perspectives of collaborative work, progress is judged by how far a group has proceeded towards a set of common goals for a solution. If the group is unable to establish a common set of goals, because group members view “the problem” in multiple ways, how do they assess progress towards achieving a collective solution? My prior studies indicate that groups do manage this satisfactorily and that group members assess a set of subtle change-management elements that are unrelated to the elements that we would normally define as part of a common vision. Further studies will investigate these elements further.

    What types of collaboration tools and techniques might be useful to increase the degree of shared understanding? If boundary-spanning groups really do possess conflicting or diverse perspectives of the problem to be solved and the types of solution that might be appropriate, are there specific techniques or approaches that might aid in increasing the shared element of the group’s understanding of the problem? My experience as an educator, developing methods for collaboration in a classroom context that often involves groups with diverse memberships, leads me to believe that certain types of approach might “displace” individuals’ current understanding sufficiently to allow a shared vision to emerge, at least for a limited scope of action. These techniques are to be developed further, through “action research” studies.

    References

    Alexander, C. 1999. “The origins of pattern theory: The future of the theory and the generation of a living world,” IEEE Software (16:5), Sept-Oct. 1999, pp 71-82.

    Gasson, S. 2004. “A Framework For Behavioral Studies of Social Cognition In Information Systems,” ISOneWorld: Engaging Executive Information Systems Practice, Information Institute, Las Vegas, NV.

    Gasson, S. 2005. ‘The Dynamics Of Sensemaking, Knowledge and Expertise in Collaborative, Boundary-Spanning Design’, Journal of Computer-Mediated Communication (JCMC), 10 (4). http://onlinelibrary.wiley.com/doi/10.1111/j.1083-6101.2005.tb00277.x/abstract

    Gasson, S.  2007. ‘ Progress And Breakdowns In Early Requirements Definition For Boundary-Spanning Information Systems’ in S. Rivard & J. Webster (Eds.) Proc. ICIS ’07, Montréal, Québec, Canada Dec. 9-12, 2007

    Rittel, H.W.J. 1972. “Second Generation Design Methods,” Reprinted in N. Cross (ed.), Developments in Design Methodology, J. Wiley & Sons, Chichester, 1984, pp. 317-327., Interview in: Design Methods Group 5th Anniversary Report, DMG Occasional Paper, 1, pp. 5-10.

    Rittel, H.W.J., and Webber, M.M. 1973. “Dilemmas in a General Theory of Planning,” Policy Sciences (4:155-169).

    Simon, H.A. 1973. “The Structure of Ill-Structured Problems,” Artificial Intelligence (4), pp 145-180.

    Notes

    [1] This is quite distinct from Simon’s perspective, that there is an “optimal” solution, that can be selected from a range of alternatives according to a set of definable criteria. Wicked problems do not possess any clearly-definable definition, so a single set of criteria for a solution cannot be defined.

    [2] Alexander, incidentally, was the initial proponent of hierarchical decomposition – the model that underlies the waterfall model of design and the traditional systems development life-cycle.

    [3] Although actually, the sad truth is that this is exactly what tends to happen … which explains why so many people are disenchanted with their IS development group.

    [4] Note that I do not use the term “problem-solving” here. One can only solve a problem that is amenable to definition. According to Rittel (1972), a wicked problem can only be understood through designing a solution. This is a high-risk activity and should not be treated in the same way as “solving” a well-defined problem.

    Page last updated 05/14/2015 © Susan Gasson (sgasson@drexel.edu) ; Paper last modified: 12/02/2007

  • Virtual Knowledge Exchange & Online Learning

    Whenever we have a group of people collaborating virtually, whether in online learning or in virtual project collaboration, their work and organizational roles become invisible. We therefore need to design in aspects (affordances) of digital technology that enable group, coordination, joint sensemaking, and knowledge exchange. These studies investigate how such groups coordinate knowledge exchange and how we can support these processes.

    Selected Papers:

    Waters, J. & Gasson, S. (2015) “Supporting Metacognition in Online, Professional Graduate Courses.” Proceedings of Hawaii Intl. Conference on System Sciences (HICSS-48), Jan. 5-8, 2015. Advances in Teaching and Learning Technologies minitrack, Collaboration Systems and Technologies.

    Gasson, S. (2012) Analyzing Key Decision-Points: Problem Partitioning In The Analysis of Tightly-Coupled, Distributed Work-systems, International Journal of Information Technologies and Systems Approach (IJITSA), 5(2), 57-83, July-December 2012. DOI: 10.4018/jitsa.2012070104

    Waters, J. and Gasson, S. (2012) Using Asynchronous Discussion Boards To Teach IS: Reflections From Practice, Proceedings of the International Conference on Information Systems, ICIS 2012, Orlando, USA, December 16-19, 2012. Association for Information Systems 2012, ISBN 978-0-615-71843-9, http://aisel.aisnet.org/icis2012/proceedings/ISCurriculum/9/

    Gasson, S., and Agosto, D.E. (2008) ‘Millennial Students & Technology Use: Implications for Undergraduate Education,’ in: Education in HCI; HCI in Education – The HCIC 2008 Winter Workshop, Jan. 30 – Feb. 3., 2008. Fraser, CO. http://www.hcic.org/uploads/Gasson1178.pdf

    Waters, J. and Gasson, S. (2006) ‘Social Engagement In An Online Community Of Inquiry’ in Proceedings of ICIS ’06, Milwaukee, WI, paper HCI-03. [Full research paper].

  • Design Methods as Performative Objects

    Brown and Duguid’s (2001) concept of a “network of practice” has been niggling away at my consciousness. The idea is that a collection of people are enabled to understand each others’ work because of commonalities in practice, but not to the extent that a Community of Practice creates shared ways of framing and performing work:

    “we include under the rubric … groups whose members, to the extent that they have common practices, are able to read and understand one another’s work. Disciplinary networks of practice cut across heterogeneous organizations, including, for example, universities, think tanks, or research labs. Professions make up yet other such networks of practice, where again similar practitioners, by virtue of their practice, are able to share professional knowledge through conferences, workshops, newsletters, listservs, Web pages and the like. … different networks of practice cut horizontally across vertically integrated organizations and extend far beyond the boundaries of the latter. Along these networks, knowledge can flow.” (Brown and Duguid 2001, p. 206)

    So create closer bonds than organizational membership, spanning organizational boundaries. If the type of intersubjectivity that derives from shared practice (i.e. what Polanyi calls tacit knowledge) does not underpin a network of practice, what does? This rings true, given the observation that IT professionals identify more with the interests of their profession than with their organization (Chou and Pearson 2012). Which brings me to the second property of networks of practice:

    “it is important to note that networks of practice may also inhibit the flow of knowledge. As Lynn et al (1996) show, professional networks will occasionally work to resist the spread of ideas felt to be inimical to the interests of the network’s members.” (Brown and Duguid 2001, p. 207).

    So how do networks of practice share knowledge? Brown and Duguid have an explanation:

    “We have used the notion of networks of practice to explain leakiness. This is not, we have suggested, simply an inherent property of some kinds of knowledge. It does not result from making knowledge explicit and so tradable. It is, rather, a function of the common underlying practice, which creates social-epistemic bonds. Where practice doesn’t prepare the ground, knowledge is unlikely to flow.” (Brown and Duguid 2001, p. 207)

    But this is not very satisfying when members of the network are not co-located. Surely, “common underlying practice” includes some form of shared framing as the basis of those social-epistemic bonds? I thought back to the work of Howard Rosenbrock (1981), who explains that IT professionals’ paradigm of system design with the aim of making users interchangeable results in deskilled, repetitive, and unfulfilling jobs for those who use these systems. He explains:

    “The paradigm is transmitted from one generation to another, not by explicit teaching but by shared problem-solving. Young engineers take part in design exercises, and later in real design projects as members of a team. In doing so, they learn to see the world in a special way: the way in fact which makes it amenable to the professional techniques which they have available.” Rosenbrock (1981, p.6),

    So we have design methods as a form of performativity, embedding ways of framing job design, as well as creating a shared design practice that ignores users’ psychological and motivation needs. But surely, IT professionals are continually learning, acquiring new skills and approaches to system design? It would appear not:

    “The fact that most IS professionals learn the bulk of their technical skills during college or immediately afterward encourages recruiters to focus on technical skills for new hires. IS professionals generally learn non-technical skills in the workplace.” (Lee et al. 2001, p.28).

    All is not lost. Lee et al. (2001) go on to observe

    “IS professionals generally learn non-technical skills in the workplace. And because these non-technical skills are so valuable in the long term, new hires need to possess the aptitude to learn these skills. This may help explain why recruiters prefer graduates who took more MIS classes than those who concentrated strictly on computer science courses.” (Lee et al. 2001, p.28).

    How can we remedy the perspective that leads to such impoverished outcomes? As Rosenbrock observes, IT systems can be seen as a replacement for human ingenuity and skill, or as a way of supporting these. We have a choice to automate or to informate work (Zuboff 1988). We also have two chances to undermine the automation-on-rails approach taught in so many methods classes. Back to the network of practice idea. IT professionals have a network of practice with really strong bonds. We can teach IS methods more thoughtfully to those who return – for ongoing education in Masters degrees, etc.  Finally, we can mobilize the network of practice, on LinkedIn and elsewhere, to ensure that IT professionals are aware of the types of skill and knowledge-preserving approaches to organizational system design that we would want to see used in our own organizations.

    References

    Brown, J.S. and Duguid, P. 2001. “Knowledge and Organization: A Social-Practice Perspective,” Organization Science (12:2), pp. 198-213.

    Chou, S.Y. and Pearson, J.M. 2012. “Organizational Citizenship Behaviour in It Professionals: An Expectancy Theory Approach,” Management Research Review (35:12), pp. 1170-1186.

    Lee, S., Yen, D., Havelka, D., and Koh, S. 2001. “Evolution of Is Professionals’ Competency: An Exploratory Study,” The Journal of Computer Information Systems (41:4), pp. 21-30.

    Rosenbrock, H.H. 1981. “Engineers and the Work That People Do,” IEEE Control Systems Magazine (1:3), pp. 4-8.

    Zuboff, S. 1988. In the Age of the Smart Machine. New York NY: Basic Books.

  • Designing Social Media Platforms For Online Learning

    Recently, I have been using a new social media platform to run one of my classes. The idea was, that as we are studying social informatics, we could study the effect of using social media on our own workflows first hand. I also thought that – in these days of daily Facebook and Twitter use – a social media site would add some relevance to the class. My thinking was that the “right-brain” expression that Daniel Pink  extolls as critical to motivation in the 21st Century – the design, narrative, synthesis, empathy, play and sensemaking skills – would be enabled by the use of social media (Pink, 2005). The site has a WIKI, blogs, discussion forums, and an interactive chat facility. I was proposing that we used Google+ hangout for short class discussions by video. For the first week, I set students the task to post to the WIKI, to post to their own blog, to locate some web readings, and to join Google+ if they had not already done so.

    By Thursday (from a Monday start), almost all of the students had posted to the discussion forum. Several had asked me questions by email. But no-one had posted to the Blog or the WIKI. By Friday, two of the more technologically-literate students had made blog posts. But most of the activity was still on the discussion forums – and only three students had provided me with Google+ contact details. Then I started to question my own assumptions. All of the students had used Blackboard for their online course access, which revolves around an asynchronous discussion board. So they were used to interacting via an asynchronous forum. I had assumed that they would be excited to use more “social” media for class interactions or for sharing what they had discovered about the topic. But how did this fit into their idea of how they would behave in an online class? Very badly. Most students sign up for online courses because this provides them with choices about what to do, when. They have a low learning-curve for using a discussion forum. Anything else is hard work.

    Clay Shirky talks about the cognitive surplus that is available from zillions of digitally-literate people with mundane jobs and untapped creativity. He argues that this expresses itself in the groundswell of free, open source software initiatives and in the crowdsourcing phenomenon (Shirky, 2010). But graduate students with a full-time job are already using their cognitive surplus in grappling with new areas of learning. My assumption that they may have some left over for experimenting with social media may be false. The problem is that the learning curve gets in the way of the “right-brain” expression that I wanted to encourage. I may need to rethink how far experimenting with social media is constraining people’s’ ability to express themselves.

    References
    Daniel Pink  (2005) A Whole New Mind: Why Right-Brainers Will Rule the Future. Berkely Publishing: New York.
    Pink (2005) Revenge Of The Right Brain, Wired Magazine, Feb. 2005.
    Clay Shirky (2010) Cognitive Surplus: Creativity and Generosity in a Connected Age, Penguin Press: New York.
    Clay SHirky (2010) An Extract From Cognitive Surplus. Wired Magazine, Business Video, June 16, 2010.
    Clay Shirky and Daniel Pink  (2010) Cognitive Surplus: The Great Spare-Time Revolution. Wired Magazine, June 2010.