Managing Organizational Knowledge

This thread of my work explores the forms of knowledge shared across organizational boundaries, the mechanisms for sharing knowledge that are employed, and how human-sensemaking is mediated by processual, technical and informational artifacts. My work draws on theories of distributed cognition, contextual emergence, and sociomateriality. Hayden White observes that human sensemaking relies on subjective forms of narrative for meaning. Much of this work explored how to enable a “conversation with the situation” that introduces reflexive breakdowns into the situated narrativizing and framing in which humans routinely engage. This results in different types of support, focusing on the different forms of knowledge that are required for decision-making — and the degree to which such knowledge can be shared.

In virtual organizations and distributed project groups, non-human objects increasingly mediate human relationships, as they displace humans as collaboration-partners in distributed knowledge networks. We may be able to identify forms of metaknowledge that work across domain boundaries by identifying mediating object roles – e.g. categorization schemes, instrumentation, databases, and routinized practices that embed frameworks for analysis or participation. My analysis has revealed different forms of group memory management in use, depending on the organizational scope of projects and the locus of control in the global network. Organizational knowledge – about how to work, how to frame organizational goals and outcomes, and how to organize work effectively – is mediated by technical objects, creating assemblages of social and technical systems of work, that guide the emergence of new business practices. The distributed scope of organizational locales creates four categories of knowledge that are acquired in different ways, summarized in Figure 1.

Figure 1. Forms of Knowledge (Gasson & Shelfer, 2006)

Codifiable knowledge is the simplest to define, as this knowledge is routine and programmable. It equates to explicit knowledge, in that we know that we know it – and we can articulate what we know, so it can be stored for others to access and use. Typical examples are organization charts, or the rules, standards, and forms used in business processes.

Transferable knowledge is articulable, but it is also situational – it is related to the context in which it is applied. For example, an IT systems developer might design software differently for a general-purpose website, whose users are relatively unknown, than for a small local application to be used by 4-5 people working together to perform specific business calculations as part of their shared work. The knowledge of when to apply different design techniques depends on the designers experience of working in various business environments and is generally acquired through some sort of apprenticeship process, where they learn from someone who has more experience of that environment.

Discoverable knowledge is less straightforward. It combines tacit knowledge (Polanyi, 1961), which is process or skills based, with implicit knowledge that people fail to recollect consciously, or perceive explicitly (Schacter, 1991). As such knowledge is inarticulable, its possessors must recall it inferentially, by relating reported case studies to their own experience, or pattern recognition that can be related to data analysis findings. An effective way of surfacing such knowledge is to discuss historical data or case studies to explore what is known collectively about various situations. This is similar to the argumentation method proposed by Rittel (1972) in his discussion of “second generation design.”

Hidden knowledge is the most difficult type to surface. It’s not the sort of knowledge that you are going to realize, unless you stop to reflect on what went wrong in your decision-making, or how an action was performed. For example, an IT Manager commented to me that the business process he had selected for a new initiative in organizational change was not as “stand-alone” as he had expected. He stopped to think, then commented that “in fact, I couldn’t have chosen a worse process to start with – it was related to every single business process we have.” Then he paused, and added, “but actually, you could say that about all of our business processes. It seems there is no such thing as a stand-alone process!” This category of knowledge is surfaced through breakdowns (Heidegger, 1962), where the “autopilot” of everyday action is disrupted by the realization that one’s usual recipe-for-success in such circumstances is not working. At that point, the tool or process we were about to use goes from being ready-to-hand, ready for automatic use, to being present-at-hand, needing reflection in order to work out how to use a tool, or how to behave in those circumstances (Winograd & Flores, 1986). During breakdowns, we need to stop and think, revising our mental model of how the world works to come up with a new way of behaving that is a better fit to the situation. Again, Rittel’s (1972) argumentation approach would be helpful here, as people pool and debate what they have learned from a failure, collectively.

The ways in which we learn, then, are dictated by the scope of access that we have to our colleagues. The more distributed people are, the more that knowledge is mediated across formal technology channels, as distinct from being acquired through face-to-face conversations. This remoteness means that we are more reliant on formal knowledge, that is codifiable, or discoverable from formal sources of information. When people are co-located, they can spend time learning from what others do, or how a mistake or failure happened. They key take-away is that we need multiple ways of configuring and using technology platforms, for all types of knowledge to be supported. We cannot design one-size-fits-all information and communication technology systems.

Selected Bibliography:

Khazraee, E.K. & Gasson, S. (2015) ‘Epistemic Objects and Embeddedness: Knowledge Construction and Narratives in Research Networks of Practice’ The Information Society, 31(2), forthcoming, Jan. 2015.

Gasson, S. (2015) “Knowledge Mediation and Boundary-Spanning In Global IS Change Projects.” Proceedings of Hawaii Intl. Conference on System Sciences (HICSS-48), Jan. 5-8, 2015. Knowledge Flows, Transfer, Sharing and Exchange minitrack, Knowledge Systems.

Gasson, S. (2012) The Sociomateriality Of Boundary-Spanning Enterprise IS Design, in Joey, F. George (Eds.), 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/SocialImpacts/8/

Gasson, S. (2011) ‘The Role of Negotiation Objects in Managing Meaning Across e-Collaboration Systems.’ OCIS Division, Academy of Management Annual Meeting, San Antonio, August 11-16, 2011.

Gasson, S. and Elrod, E.M. (2006) ‘Distributed Knowledge Coordination Across Virtual Organization Boundaries’, in Proceedings of ICIS ’06, Milwaukee, WI, paper KM-01. [Winner of ICIS Best paper in track award].

Gasson, S. and Shelfer, K.M. (2006) ‘IT-Based Knowledge Management To Support Organizational Learning: Visa Application Screening At The INS’, Information, Technology & People, 20 (4), pp. 376-399. Winner of 2008 Emerald Literati outstanding paper award.

DeLuca, D., Gasson, S., and Kock, N. (2006) ‘Adaptations That Virtual Teams Make So That Complex Tasks Can Be Performed Using Simple e-Collaboration Technologies’ International Journal of e-Collaboration, 2 (3), pp. 65-91

References

Heidegger, M. 1962. Being and Time. New York NY.: Harper & Row New York

Polanyi, M. 1961. “Knowing and Being,” Mind (5:70), pp. 458-470.

Rittel, H.W.J. 1972. “Second Generation Design Methods,” DMG Occasional Paper 1. Reprinted in N. Cross (Ed.) 1984. Developments in Design Methodology, J. Wiley & Sons, Chichester: 317-327.

Schacter, D. L. (1992). Implicit knowledge: new perspectives on unconscious processes. Proceedings of the National Academy of Sciences, 89(23), 11113-11117.

Winograd, T. and Flores, F. 1986. Understanding Computers and Cognition. Norwood New Jersey: Ablex Corporation.