Pulling it all together

Since I’ve spent the last 24 hours pulling myself together, maybe now it’s time to pull the literature together. I told my husband, half jokingly, that what I’ve learned from this course is that there is no truth, none of us actually knows what we know, and the information economy will destroy everyone but the 1%. More seriously, the literature is full of broad, interesting themes: Knowledge is mediated, situated, negotiated, and self-referential; what we know is no more or less than who we are. Knowledge is created and shared in relationships of trust; knowledge gains as much of its meaning from our relationships as it does from its contents. Organizations, be they little tiny ICT firms in Hinterland, South Dakota, Fortune 500 companies, cities, or countries, rely on the knowledge of their members and of the organization itself to seek advantage, to create, to innovate, to grow, and to succeed – but they do so at their risk. Knowledge – explicit and tacit – can make us our best or our worst in terrible circumstances. Technology is helpful, but is only as useful as the users, who are engaging, creating, sharing, and relating. Nothing is universal – not our work, not the problems we face or the solutions we create – but for the fact that we’re all in it, we’re all part of groups of people coming together to know and to do more with our knowing. And, perhaps, that’s a simple but profoundly good thing to know.

References:

Chalmeta, R., & Grangel, R. (2008). Methodology for hte implementation of knowledge management systems. Journal of hte American Society for Information Science and Technology, 59(5), 742 – 755.

Alavi, M., & Leidner, D.E. (2001). Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly, 25(1), 107 – 136.

Touskas, H. (2001). What is organizational knowledge. Journal of Management Studies, 38(7), 973 – 993.

Knowledge is a dangerous business

While we’ve talked at some length about trust, reciprocity, and the social nature of knowledge creation and sharing, we haven’t really addressed the risks that attend KM. Which in retrospect, is kind of funny, since lawyers (and even we defected former lawyers) are all about risk and mitigation. Heck, one of the first things you learn in Torts is Learned Hands Calculus of Risk, wherein a duty of care has been breached if the cost of precautions is less than the probability of the risk * the cost of the risk. But, as much fun as it is to talk about the end of the world at the hands of deepening inequality due to the digital divide and lack of access to information resources (‘sup, Tremblay? How you doin’, Stock?), there are much more mundane risks that nonetheless must be considered. Anyone who’s dealt with an NDA or a non-compete knows that, given that knowledge provides a competitive advantage, and that information is an economic resource, there must be a balance between sharing information broadly enough to capture competitive advantage, but not so broadly as to hand that advantage over to the competition. Liability can also attach if sensitive data is improperly shared or disclosed (such as multimillion dollar HIPAA fines should personally identifiable information be leaked).  Additionally, Trkman & Desouza raise interesting risks such as the loss of core competencies due to overreliance on outside sources of knowledge (whom I badly want to refer to as epistemological communities, although that doesn’t quite fit in this context 😉 ) and the nonrecoverability of the loss if knowledge sharing and transfer within a network fail. Their framework provides a useful means for thinking about the relative degrees of risk (since nothing is risk free) and balancing them – proximity and assymetry in particular being important concerns that often get dropped by the wayside. It looks in the literature as if the authors have explored this issue empirically in a further publication – I intend to read that work over; their framework jibes well with my sense of risk mitigation, so I’m curious to see if it was validated.

Interestingly, while the Massingham article also addresses risk management framework, I felt that it would’ve fit better with the disaster readings, as opposed to Trkman & Desouza. Massingham’s framework is intended to use KM training to reduce the impact of humans’ generally crappy risk assessment by adding a “Knowledge Score” to the “Risk Score” common in traditional (and less-than-successful, because humans are so not rational, despite the protestations of the dismal science) decision trees. Although the method is entirely non-intuitive, it seems to have been successful in eliminating cognitive distortions and allowing EngServ to more accurately identify real risks, taking into account the knowledge resources available to address various risks and challenges. Like Melinda, I found this article difficult to approach, likely because my quantitative training stopped at Calculus, so thinking quantitatively about this kind of problem doesn’t come naturally to me. However, when I think about it in the context of Kumar & Chakrabarti’s work about the Challenger disaster and bounded awareness, it makes sense: by quantifying where our knowledge is strong or weak, we make it much less likely that we’ll overlook useful, readily available information and make a disasterously bad choice (or, in the case of the EngServ case study, we’ll realize that what looks like a potential disaster is actually much less likely to be so because we do have useful, readily available information). In particular, Kumar & Chakrabarti’s discussion aobut the self-referential nature of tacit knowledge helped me understand how Massingham’s risk score could reduce the power of cognitive distortion in risk management (which, in totality, still is about balancing risks, and requires…dum dum dum…judgment. We just can’t get away from tacit knowledge!)

 

References:

Trkman, P. & Desouza, K.C. (2012) Knowledge risks in organizational networks: An exploratory framework. Journal of Strategic Information System, 21(1), 1-17.

Massingham, P. (2010). Knowledge risk management: A framework. Journal of Knowledge Management, 14(3), 464 – 485.

Kumar, J.A., & chakrabarti, A. (2012). Bounded awareness and tacit knowledge: Revisiting Challenger disaster. Journal of Knowledge Management, 16(6), 934-949.

 

Wikis, Social Media, and Web 2.0, Oh My!

So, we’ve looked recently at some larger themes in the research; trust, relationships, knowledge sharing, reuse, and dissemination, and ICT as a means of lessening informational distance. As Anne points out, “Wasko and Faraj argue that individual contributions in electronic networks of practice can also be explained in part social capital and individual motivations,” and so I was curious to see the role of relationship in the success or failure of all these fancy new web tools in helping us improve our KM (and, since I’m addicted to Buzzfeed quizzes, I enjoyed both Lisa and Anne’s discussions of Buzzfeed as KM, though I don’t have much to contribute on that front).

Wikis are familiar to everyone; anyone with teacher friends is familiar with the constant need to admonish students against using Wikipedia as a source. However, the positivity of Grace’s findings surprised me; my personal experience with Wikis in the corporate environment is that they have a tendency to become neglected, outdated messes unless there’s someone whose entire role is dedicated to managing them. Also, some of the advantages Grace identified (back in 2009, to be fair) seem to have been lost in the face of more apt technologies (for example, when it comes to email overload, Wikis seem to have been supplanted by the likes of Dropbox and Google Docs, which allow collaborative authorship without “publishing” the results outside of the authors until it’s ready for dissemination). The Levy article (in addition to being distractingly poor in terms of writing) felt similarly outdated. In the five years since Levy wrote, the “gravitational core” of Web 2.0 has become so deeply embedded in our relationship to the Internet that the idea of users as simply passive information consumers seems laughable. Interestingly, even the Level 0 apps mentioned in the article are now interactive Web 2.0 apps: Google Maps can hook up with the GPS on your phone, hook you up with your Google+ friends who might be nearby, and share info with your network. Her tables comparing tech and KM principles are actually quite helpful and largely still relevant, although social media doesn’t get the heavy treatment it would nowadays (since, back in 2009, MySpace was apparently still a thing).

The first conclusion that Wasko and Faraj led me to was that I needed to add Brown and Duguid to the conversation, since so much of the Wasko & Faraj work was informed by Brown & Duguid’s work.Wasko & Faraj’s summation of Brown & Duguid, stating that “knowledge flows are best understood by examining how work is actually performed and thinking about knowledge and learning as an outcome of actual engagement in practice,” struck me as a simple, yet profound insight into KM. Understanding “engagement in practice” requires us to understand the tacit knowledge, the situational and cultural mediation and negotiation, and the epistemological principles of the community of practice at hand. Understanding “how work is actually performed” requires engagement with the community of practice itself, and forces us to engage an understanding of the social capital and trust at play. It seemed, in short, to encapsulate all of the principles we’ve been trying to get at in a very complete formulation.

Like Kelly, when I got to the question that forms the heart of Wasko & Faraj’s work, I was struck by it. Why DO we spend our valuable time helping people with whom we lack relationships of trust and reciprocity? The authors rely upon Nahapiet and Ghoshal to try to formulate an answer; interestingly, though it didn’t strike me when I read Nahapiet & Ghoshal, reading their work applied struck me as deeply tinged with Skinnerian behaviorism. Interestingly, social capital seemed to play little to no role in people’s choice to share knowledge in electronic networks; I wonder, in the age of social media, if results would be different as compared to the impersonal nature of the message boards studied,

I wish I had read Brown & Duguid much earlier, especially given all the hate I heaped on poor Brown for Bridging epistemologies. While the work on non-canoical practices (as compared to official accounts) nicely exposes questions of tacit v explicit knowledge, I think it also highlights the issues of evolving knowledge (Nonaka’s spiral) and of knowledge creation and transfer in the face of non-stable environments (to be honest, the deeper I get into the literature, the more I wonder if there is or ever was a truly “stable” knowledge environment, since relationships, needs, and the world itself constantly change).

In light of the foregoing, Yuan et al.‘s results register as a big ol’ “not surprised.” Of course people use a variety of ICT’s – part of practice is finding the best tool for the job. And while Melinda seemed surprised that people prefer social media to more traditional ICT, I’m not: social media is social. Although our online personas are typically better looking and more exciting than our IRL selves, they nonetheless carry our names and core pieces of us; our social media “self” is still part of ourselves.And the relationships within social media are, at heart, social relationships – given the social nature of knowledge creation, it seems only natural that we’d prefer social media for knowledge sharing.

References:

Brown, J.S., & Duguid, P. (1991). Organizational learning and communities-of-practice: Toward a univfied view of working, learning, and innovation. Organization Science, 2(1), 40-57.

Grace, T.P.L. (2009). Wikis as a knowledge management tool. Journal of Knowledge Management, 13(4), 64-74.

Levy, M. (2009). Web 2.0 implications on knowledge management. Journal of Knowledge Manage, 13(1), 120 – 134.

Wasko, M.M., & Faraj, S. (2005). why should I share? Examining social capital and knowledge contribution in electronic networks of practice. MIS quarterly, 29(1), 35 – 57.

Yuan, Y.C., Zhao, X., Liao, Q., & Chi, C. (2013). The use of different information and communication technologies to support knowledge sharing in organizations: From e-mail to micro-blogging. Journal of hte American Society of Information Science and Technology, 64(8), 1659-1670.

 

A sense of place

My initial notes for this post’s themes included “location,” “community,” and “who we are/where we are.” They’re broad themes, but, building on Blackler, draw upon the sense that our knowing is socially and culturally mediated; any community of practice, as an epistemological community, has a sense of place to its identity, even if that place isn’t physical. So, along the theme of “place,” I chose:

Stock, W.G. (2011). Informational cities: Analysis and construction of cities in the knowledge society. Journal of the American Society of Information Science and Technology, 62(5), 963-986. (For the record, I know I used Castell’s work that this is built on in a recent paper, and I can’t recall which – it’s driving me batty).

Goggins, S.P., & Mascaro, C. (2013). Context matters: The experience of physical, informational, and cultural distance in rural IT firm. The Information Society, 29, 113-127.

Lam, W., & Chua, A.Y. (2009). Knowledge outsourcing: An alternative strategy for knowledge management. Journal of Knowledge Management, 13(3), 28 – 43.

Stock’s article struck me as depressingly true (despite utilizing the gag-worth term “glocality’). I currently live in a highly gentrified suburb of Vancouver, BC – but the economic interactions of my current hometown make it much more part of Hong Kong/Beijing than anywhere in North America (and the fact that I speak neither Mandarin nor Cantonese very much leaves me out of the economic life here). Interestingly, many people’s economic lives remain centered around that world city, probably because, as Stock asserts, the center of information is there – my hometown is largely a resort, a place to park assets and live when not working; the real economic and knowledge development is still happening in Hong Kong and Beijing. I was happy to see Stock address gentrification; when I first started reading about “space of flows,” I was screaming in my head: “But these informational cities will displace those who’ve been left out of the information economy!” So, I was relieved to see Stock address that, as opposed to cheerily embracing information society idealism. The discussion of job and income polarization, the social consequences thereof, and the Matthew principle are all useful (I see those U- and J-shaped curves with foreign labor all the time). I had a harder time locating this article within KM, but I suppose it epitomizes it in a sense – organizations (in this sense, the corporations and universities that make up the knowledge nexus of an informational city) that capitalize upon their knowledge will gain (and perpetuate) their advantage in a way that makes increasingly rigid differentiation between knowledge winners and losers.

Stock dovetails nicely with the Goggins & Mascaro piece; whereas Stock largely examines the characteristics of cities that have successfully transitioned into being “informational cities,” Goggins & Mascaro examine the experience of a rural IT firm and the impact of different forms of distance, including cultural distance (although they’re addressing the difference between digital natives and non-natives, as opposed to the cultural differences in substantial immigrant populations) and informational distance. Goggins & Mascaro’s research largely bears out  Stock’s work: STC had trouble recruiting the kinds of knowledge workers that ITC firms typically employ, because the educational level of its rural recruits was typically much lower than one would find in an informational city. STC overcomes this through a 12 week bootcamp on hire, but throughout, we find STC is having to overcome the informational distance imposed by their geographical distance, and the agglomeration and spillover benefits that make informational cities such founts of innovation and economic growth just aren’t present in the rural areas.

Finally, Lam & Chua’s work on knowledge outsourcing (KO) took me back to Chua’s work on disaster management (hey, if you find a publishable theoretical model, ride that pony to the finish!): once again, we find the process-oriented model of knowledge creation, knowledge reuse, and knowledge transfer. Same story, different context (since, really, context is what it’s all about). Unsurprisingly, relationships are, again, at the heart of the KM venture, even in a KO situation. And it’s this author’s opinion that relationship is the real heart of the informational city, and of the success and failure of KM in almost every circumstance, because, ultimately, it’s about trust and tacit knowledge. The example that sprang to my mind was Lean Manufacturing, even though it seems about as far as you can get from FU’s courseware outsourcing. With Lean Manufacturing, in order to preserve value and eliminate waste, the Lean professional has to develop deep knowledge of what constitutes value, and therefore what constitutes waste, to the client – it’s a KO relationship that requires the consultant to develop intense tacit knowledge of the client business.

Folksonomy

I’m not entirely done with my folksonomy yet, but, that’s where my mind is, so I figured I’d go ahead and lay out some of that process. Like Melinda, I initially thought that I would have some grand overarching set of tags to organize my readings. Instead, I’ve ended up with an enormous word cloud. However, when I look at the tags, they bring back the themes and context of the specific article, as well as illustrating themes that align nicely with the themes I’ve picked up through the materials: trust, information sharing, codification, tacitness/explicitness, and ultimately, truth. Tagging was probably the hardest part of the reading for me: I read, pondered, posted, and then after all of that, added the articles from a particular post to CiteULike and tagged. When I tagged, I tried to distill the major themes of each article into one- to two-word phrases, and found myself frequently having to refer back to the articles. It was an interesting exercising in codifying my tacit understanding of the work, and I’d say that my folksonomy really functions as a codification of my understanding of KM. While I liked the social knowledge creation aspect of using CiteULike with my classmates (I totally stole some of your tags, Whitney), I think I’ll probably stick with my db for tracking references in the future; it’s mine and it’s comfortable.

ETA: Link, of course! http://www.citeulike.org/user/darralynnhofman

It’s all academic, anyways…

So, hot off my foray into disasters, and the depressing conclusion that we can never be prepared, because in a constantly evolving situation, everything relies on the tacit knowledge of the individuals or community making the decisions, I headed in the world of knowledge management and academic libraries. In particular, I went into this reading curious to see the role of trust, community assumptions and worldviews (talk about shared assumptions of validity – do you get more specific on that front than in the academy) and the role of tacit knowledge in informing our ideas of truth and objectivity.  Although it doesn’t deal with these articles, I was also thinking of Whitney’s comments on the distance between pedagogy and practice (seriously, though, Whitney, you WEREN’T BORN when Challenger exploded??? *goes to the old person corner of shame*) So, around the general theme of academic libraries, I chose:

Gandhi, S. (2004). Knowledge management and reference services. The Journal of Academic Librarianship, 30(5), 368-381.

Jantz, R. (2001) Knowledge management in academic libraries: Special tools and processes to support information professionals. Reference Services Review, 29(1), 33 – 39.

Blackler, F. (1995). Knowledge, knowledge work and organizations: An overview and interpretation. Organization Studies, 16(6), 1021 – 1046.

Townley, C.T. (2001). Knowledge management and academic libraries. College and Research Libraries, 62(1), 44 – 55.

Interestingly, the initial premise of the Townley article seems outdated, perhaps speaking to the penetration of knowledge management: “librar­ies do not consider organizational knowledge as a resource in its own right as they do personnel, collections, or facilities.” Even in 603, issues of organizational knowledge and competitive advantage were addressed, and a number of the academic librarian positions I’ve seen posted of late emphasize skills in data analytics, presumably to capitalize on explicit organizational knowledge (I know SAS if anyone’s looking…). The contemporary Jantz article, while not addressing the KM tradition explicitly, is nonetheless based on trying to codify some tacit knowledge of librarians into the Common Knowledge Database. And a mere three years after Townley states that libraries aren’t using organizational knowledge, Gandhi sees that “KM [has] become visible on the radar screens of libraries.” The Blackler article, perhaps because it is not situated within the academic library milieu directly, offers a more developed and sophisticated view of organizational knowledge as a culturally-located, active process (Want to guess which article I prefer?).

AT this point, Townley, in particular, felt largely like more of the same. The same themes that we’ve seen throughout – KM as a means to gain competitive advantage, respond to increasing environmental turbulence, and to encourage knowledge creation and sharing in an atmosphere of trust – appear again here. While the application of KM principles to expand the role of the academic librarian within the institution is novel and could be well worth the effort, although I believe Townley skips over the intense amount of tacit knowledge that is required to be a successful leader, change maker, and coordinator, as such an expanded role would require. His discussion about proactivity and the conflict between KM principles and traditional librarian principles of confidentiality is interesting, but, given our ability anonymize data, I believe history has come down on the side of KM. Jantz, on the other hand, seemed like an extremely local attempt without clear guiding principles (I would be curious to know if the CKDB has survived). Which leaves us with Gandhi and Blackler.

Like Melinda, I liked Gandhi’s definition of KM as “organizing to know” (although, as I learned from my paper, it’s specifically organizing to know within organizations; at the individual level, it’s information seeking). Although, unlike Melinda, I wasn’t really taken with Gandhi’s description of the information continuum; for me, it was more like, “Seriously? The data pyramid AGAIN?” (But perhaps that reaction is from studying it in 600, 601, AND 602 last semester). I do like Gandhi’s framework of knowledge, management, IT, and culture. The example of employees withholding information when they feel that management withholds from them reminded me all too much of my time in the corporate world, and also underscored the issues of trust and that trust is created when we share knowledge…it all keeps coming back around in beautiful tacit circles 😉 Having been a database admin once upon a time, I enjoyed her discussion of DBMS and the fact that, yes, they are in fact still just information management systems (and, imho, will remain so until we can codify tacit knowledge to the point that we can give information semantic meaning for computers…at which point, I welcome our new robot overlords). And I absolutely agree with Gandhi’s ultimate conclusion that the future of librarianship – if we are to have a future – lies in moving beyond mere administration, and embracing our role as specialist knowledge managers.

So, all of this brings me to Blackler. We all know my biases by now. I’m deeply cynical about the post-industrial society (much less the information society) and structural inequality. I doubt the very existence of such a thing as “objectivity” or “truth,” and believe that all information is culturally mediated and preloaded with the biases and world view of the person sharing it. I’m disillusioned with the professions, and have read just enough Lacan to be dangerous. (Look, Ma, I’m a postmodernist!) So of course I loved Blackler. He shares my biases and concludes, I believe quite rightly, that there’s no such thing as “knowledge” floating out there in the ether. There is knowing, which is a mediated, situated, provisional, pragmatic, and contested process and interaction. While it’s not a novel formulation (Bourdieu’s doxa, for example, address largely the same issues), it provides an almost entirely novel way of looking at questions of knowledge management in a capitalist system. AS Blackler puts it, “The question thus becomes: ‘How are system of knowing and doing changing, and what responses would be appropriate?'” Dynamite stuff, really.

 

 

 

Disasters, disasters everywhere…

Now begins the end of semester marathon blogging. Pro-tip: don’t do this. Extra pro-tip: If you don’t want to do this, don’t have your only babysitter get divorced and become unavailable, your mom end up in the ICU, and your second kid start going through the autism diagnosis process in the middle of a semester. Especially if you suck at self-management to begin with.

So, with me being a disaster, and having had an interesting discussion about disasters and vulnerable populations with Rebecca on her blog, I’m diving into KM and disasters/disaster management. Of the readings, I chose the first two as directly disaster oriented, and the third because policy considerations are always an element in disaster coordination, especially in large international disasters (and, of course, because I have a law degree and see POLICY EVERYWHERE).

Chua, Alton Y. K. “A tale of two hurricanes: Comparing Katrina and Rita through a knowledge management perspective.” Journal of the American Society for Information Science and Technology 58 (August 2007): 1518-1528.

Jones, N.B. & Mahon, J.F. (2012) Nimble knowledge transfer in high velocity/turbulent environments. Journal of Knowledge Management, 16(5), 774-788.

Haas, P.M. (1992). Introduction: Epistemic communities and international policy coordination. International Organization, 46(1), 1-35.

It might sound simplistic (I’m choosing to go with the term “foundational”), but I found the expository material and Jones & Mahon, defining the nature of high velocity/turbulent environments and the relationship between knowledge and learning processes, and the challenges of communication and complacency, a good point to begin thinking about knowledge in disasters. The interactive, iterative nature of knowledge in HVTE’s made me think of Nonaka’s knowledge spiral. It also brought to mind Rebecca’s question about disasters: “Even though we plan for disasters, are we ever truly prepared?” The nature of disasters as HVTE means, no, we’re not: the situation is constantly evolving, and as such, knowledge in that situation (and thus our response and preparation) is “an ongoing, continuous and
nearly simultaneous process as the constantly changing environment offers new knowledge
and the opportunity for continuous knowledge innovation and dissemination.”

This line from the article seems, to me, to capture the essence of the struggle of knowledge management in disasters specifically, and knowledge management generally: “capturing relevant information and knowledge [and] getting it
to the right people at the right time.” This is the heart of the matter, and this is the reason that, while the Internet and computing technology have made so much more information available, they haven’t made decision making easier or professional judgement less important; tacit knowledge provides the context to judge what’s relevant, who the right people are and what the right time is. As Chua states, citing Nonaka & Takeuchi, “knowledge creation is heavily social in nature” – and it’s the tacit piece of that creation that makes knowledge management in disaster situations so challenging. While both Chua and Jones & Mahon are struggling to codify the process of KM in disasters – Chua with the knowledge creation/reuse/transfer model (prediction/implements/relief and rescue), Jones & Mahon with…whatever you want to call Fig. 1….what they’re really trying to cope with is the nature of organizational decision making in high stakes situations. We, as a society, place a high value on empiricism, on informed decision making and educated conversations…but if you want a “great” litigator, emergency physician, paramedic, or other person who works in high stakes, time pressured (HVTE) environments, what you really want is experience, because of the judgement and the “gut feeling” that comes from a deeply developed body of tacit knowledge (P1 and 3 in Jones & Mahon). The challenges of communication, cooperation, and complacency arise (and will continue to arise, no matter how perfect our processes) because at every step, judgement is required: Who do we need on the knowledge team? Which members of which team need to be briefed? Our processes can develop organizational capacity, but they can’t ensure organizational effectiveness. There is no such thing as objective, and there is no such thing as complete information (or complete KM processes).

Haas’ epistemic communities lie at the heart of all of this, even though the term doesn’t arise in Jones & Mahon or Chua’s analysis. As Haas states, the information that epistemic communities (be they bureaucrats advising the UN or technical experts working for BP) provide is “neither guesses nor “raw data; it is the product of human interpretations of social and physical phenomena.” Tacit knowledge will always and forever frame what we know; no matter how much we try to codify, reality remains socially constructed, and our decision making framework can never be divorced from all of the tacit knowledge that we, individually or collectively, bring with us.

Starting to find some footing

Now that we’re halfway through the semester, and halfway through the reading list, I’ve begun to feel that I have my footing. The ground isn’t constantly shifting beneath me, and I can see the outlines of the landscape. Some themes are beginning to emerge: the relationship between tacit and explicit knowledge; information sharing, trust, information creation, and the social dimensions of organizations; the role and significance of codification and codebooks; and of course, epistemology itself, and the relationship between knowledge, process, and action (henceforth, I’m ignoring JTB in favor of Nonaka’s definition of knowledge as justified belief that enhances one’s ability to take action). It was with these emerging broad themes in mind that I chose this week’s reading: Nahapiet & Ghoshal’s “Social capital, intellectual capital, and the organizational advantage,” Powell & Snellman’s “The knowledge economy,” and Tremblay’s “The information society: From Fordism to Gatesism.” Why these? Because the broad themes emerging all point to knowledge creation and management as an organic, social process, one knotted up in the intricacies of living and being in a society (however broadly or narrowly one wants to define society, be it at the enterprise level, nation-state level, or even global level). These articles seemed like they could be helpful in understanding KM from that perspective. (On a somewhat tangential note: I’ve been avoiding the research articles because, frankly, both of my graduate degrees have been professional degrees (law and LIS), and have next to no methodological training…therefore, I feel inadequately qualified to really sift through those articles critically).

Nahapiel & Ghoshal’s theory of social capital, in all three of its dimension, facilitating the creation and exchange of knowledge and, therefore, providing advantage to organizations (they use the technical term “firms”) who support and develop social capital actually made me think of my favorite management book, Leadership is an Art, by Max Dupree. (I know, I know, who has a favorite management book? Stay with me here). Dupree believed in servant-leadership; one leads by creating trust and empowering one’s people to contribute to the shared vision and success of the organization. In other words, by fostering a community of practice! (I wouldn’t have made the leap to Hara on my own, btw – credit goes to my own community of practice, and specifically, Melinda’s discussion of the decentralization of power). The relational embeddedness of social capital, in particular, explains why it’s so difficult for autistic people – even brilliant, well-trained ones – to become part of a firm, and to really contribute to knowledge creation in the manner that their cognitive ability would suggest – because of the social contradictions at play. And of course, Polanyi, tacitness, and epistemology come in for an appearance in the requisite, “But what is knowledge?” section.

In the context of my other readings, I found myself in the mood to argue with Powell & Snellman from the word “Abstract.” Their contention that Nonaka and Drucker are narrowly managerial in orientation seems laughable, given the revolutionary role of both writers in our conception of both knowledge management and the information society (Drucker, after all, is the one who coined the term “knowledge worker”). And their general conception of what constitutes “knowledge” and their means of orienting their evidence of of a knowledge economy towards the empirical (patent counting) falls into the same shallow thinking as Rule & Besen identified in Porat. Those who would describe the Fordist era of manufacturing as purely mechanized betray their lack of familiarity with the knowledge and skill required of the machinist and machine operator; this author would argue that the shift toward the computerized factory is not a shift towards knowledge, but merely towards the codification of knowledge such that the computer can now do what the skilled machinist did. Also, I have  enough friends who do IP work to have zero faith that an increase in patents is a reflection of anything in terms of knowledge; it’s as much a cynical business tool as anything else (seriously, patent counting as a tool seems to me a reflection of a poor understanding of how patents work).

So, a little bit wary from Powell and Snellman’s failure to understand the significant role of tacit knowledge in the Fordist manufacturing era, we now approach Tremblay’s work, which is explicitly about “Fordism to Gatesism.” Onto this trepidation is the inclusion of the term “information society,” which, as I discussed previously, Rule & Besen ripped apart. So I went into this work struggling to keep an open mind; but, Tremblay expanded it to a book in 2001, so there’s that, right? I was, however, happily surprised; rather than triumphantly trumpeting the industrial society or Gatesism, Tremblay takes a scathing look at the information society as capitalism writ large, “the commodification of information, culture, and communication.” I particularly enjoyed Tremblay’s exposition of the tacit knowledge of the communications field that make objective evaluation of “the information society” (such as the Innisiation postulate) and which undergirds the optimist/pessimist dichotomy. For those struggling with the concept of tacit knowledge, this bit of exposition illustrates nicely what tacit knowledge looks like at play. What Tremblay does a wonderful job of in this article is nailing down the “lovely naievete” of those in the optimist camp; the fundamental information society belief seems to be, truly, that access to enough information will change human nature! No more rapacious capitalists! No more dumb choices! Information and communication will transform us all! Tremblay puts words to the cynicism I’ve felt throughout: “the computerization of society, a transformation process currently underway, is not necessarily tantamount to the information society, a utopian model of society, the realization of which is more than unlikely.” 

 

Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. The Academy of Management Review, 23(2), 242-266. URL: http://www.jstor.org/stable/10.2307/259373

Powell, W. W., & Snellman, Kaisa. (2004). The knowledge economy. Annual Review of Sociology, 30, 199-220. doi:10.1146/annurev.soc.29.010202.100037

Tremblay, G. (1995).. Canadian Journal of Communication, 20(4), 461-482. URL:
http://cjc-online.ca/index.php/journal/article/viewArticle/891/797

Viral Events

Many thanks to Rebecca for providing me with the terminology for the Pace Salsa incident I brought up in my last post: viral event, and for directing me to Hemsley and Mason’s article on the United Breaks Guitars event (those interested in the viral event that formed the basis of this paper can check Rebecca’s post for an excellent narrative recounting). I will admit that I went into Hemsley and Mason’s article expecting a relatively narrow perspective; rather, I found their paper refreshingly broad-minded. Their assertion that social media generally, and viral events particularly, reveal a much more fractious, turbulent, diverse knowledge ecosystem (KE) than has generally been assumed with KM dovetailed nicely with the Rule & Besen article. If the KE is actually full of diversity, disagreement, dissension, and disruption, then the information society fantasy is in fact just that: fantasy. I also agree with the authors that social media has reduced the information gatekeeper role; while viral events serve as a good illustration of this, the loss of the gatekeeper role (and the power of narrative on our beliefs, see Lewandowsky, S., Ecker, U. H., Seifert, C. M., Schwarz, N., & Cook, J. (2012). Misinformation and Its Correction: Continued Influence and Successful Debiasing. Psychological Science In The Public Interest (Sage Publications Inc.), 13(3), 106-131), serves to emphasize the fantastical element of the idea of an orderly society ruled by detached, neutral, objective empirical evidence. Being on that line of thinking, I dove into the rest of this week’s articles, which I had chosen due to their potential to help illuminate viral events, not expecting them to necessarily fit into the relationship I’d found between Hemsley & Mason and Rule & Besen.

To my surprise, however, Ibrahim & Allen’s article on information and trust fit nicely into my expanding understanding of KM, KE, and the contradictions and complications of defining and understanding them. In particular, Ibrahim & Allen deal with the problems of trust and information sharing in oil rig disasters like the Deepwater Horizon event. While the traditional KM/Communities of Practice view is that information sharing flows from trust, Ibrahim & Allen’s research suggests (seemingly logically to both me and my colleague Melinda, although they assert that it’s a counterintuitive thesis) that information should be shared to rebuild trust after a collapse of trust. Now then, I will confess to having a bias in favor of their chosen theoretical framework – I very much like the work of Vygotsky, and have tried to implement a fair amount of scaffolding in my child rearing. So that bias is on the table. That being said, I found their discussion of secondary contradictions – and emphasis on contradictions throughout – to be a useful intellectual tool for understanding both the role of tacit knowledge, the failure of the information society to materialize, and the persistence of misinformation, disinformation, and information mistrust. After all, we as a society, and each of our social activities, are wrought with contradictions,a dn only by sharing information can we illuminate those contradictions and increase the likelihood of trust (and, eventually compliance or action) on the part of others. This article provided a lot of richness that I didn’t expect, and I’m happy I read it.

So, with a head full of contradictions, trust, and turbulent knowledge ecosystems, I headed into Wang and Lu. My brother Nonaka gets a shout-out in their definition of knowledge (guess Kimble was right about the game-changing nature of that article!). Wang & Lu’s characterization of the role of knowledge transfer was particularly striking: “during a crisis decision makers are often forced to make critical decisions, based on limited information and knowledge and with time pressure, in response to situations marked by a high level of ambiguity and uncertainty.” All I could think was how much this reflected my experience as a manager in a medical institution, as well as my experience as a litigator and, from what I understand from my best friend, her experience as a doctor (is that scary to the non-professionals out there?). Of course, you train extensively, and go into the courtroom/patient’s room having prepped extensively, but there are just so many decisions that have to be made without extensive consultation – eventually, judgment carries the day (and, in so much of the literature, judgment is, in the end, the defining characteristic of professionalism). And while I agree that good knowledge management and ensuring the flow of knowledge along the knowledge transfer channels can help with the issue of probability, predictability, and impact, I believe judgment – which shows up in both the “Acquire and use the knowledge” (which knowledge? how do we value it?) and the “Make accurate and timely CM decision” (which decision amongst many, and based on what values?) nodes of Wang & Lu’s model of the implications of their research – ultimately carries the day. And judgment is an ugly,. ill-defined mix of both expert knowledge and tacit knowledge, with a nice dash of prioritizing and valuing thrown in. It’s why irreconcilable differences will always be with us, and why we just can’t have nice things (at least, not if “nice things” means an objective information society!).

Sources:

Hemsley, J., & Mason, R. M. (2013). Knowledge and knowledge management in the social media age. Journal of Organizational Computing and Electronic Commerce, 23(1), 138-167. doi10.1080/10919392.2013.748614

Ibrahim, N. H., & Allen, D. (2012). Information sharing and trust during major incidents: Findings from the oil industry. Journal of the American Society of Information Science and Technology, 63(10), 1916-1928. doi:10.1002/asi.22676

Wang, W. T., & Lu, Y. C. (2010). Knowledge transfer in response to organizational crises: An exploratory study. Expert Systems with Applications, 37(5), 3934-3942. doi:10.1016/j.eswa.2009.11.023

But why?

When you have small children, you hear, “But why?” a lot. I’d say I hear it approximately 3897148392 times per day. And while it’s been at the back of my mind with regards to KM, a few things have brought it to the forefront. One, a bit of outside reading I’ve been doing about impact factor, article level metrics, and ROI for research has had me thinking about the purpose of research (really, knowledge creation) and how we manage the knowledge created (HT to my colleague Anne for sharing this article, which got this ball rolling). This line of thinking became more dominant when I read my colleague Rebecca’s take on the Chua/Banerjee article, in particular the assertion that Starbucks is “successful” in their social media KM. I was left wondering, “What does it mean to successfully manage knowledge? What are we trying to do here, and why?” So, in addition to the Chua/Banerjee article, I’ve chosen to consider Hansen et al.’s “What’s your strategy for managing knowledge?” (because you don’t get much more brass tacks that HBR) and Rule & Besen’s “The once and future information society” (in hopes of some macro level orientation).

Unfortunately, Hansen et al. didn’t do as much to elucidate the deeper truths as I hoped. That said, their personification/codification arrangement nicely illustrates the different tools necessary for managing and leveraging the deeply tacit, difficult to codify knowledge on one side of Nonaka’s not-a-dichotomy, and the highly codifiable knowledge at the other. Hansen et al. also do a very nice job explicating the roles of different business tools (esp IT) in leveraging the different types of knowledge. For me, this article tied very nicely into the Kimble/Nonaka work from my last post, making the more abstract aspects of that work clear from a business perspective. In other words, very valuable, just not as directly applicable to the question at hand as I hoped.

I moved on to the Chua/Banerjee article, which did a nice job elucidating their idea of “successful” KM in the context of a customer-facing bricks-and-mortar retail environment. Having done some corporate ops work in the past, I can get behind “success” meaning customer engagement, bridging the gap between actual and perceived performance, and even crisis management. I need to do further reading to be able to intelligently critique their proposed framework (although I have passing familiarity with ethnography, the derivative netnography is new to me), but I don’t doubt that CKM and social media will continue to prove sources of disruptive innovation. One aspect of social media CKM that Chua/Bannerjee don’t address (quite naturally, given the relatively new nature of this work) is how companies seize on and respond to high publicity customer incidents which fall neither within the “compliments or complaints” paradigm (for example, the very NSFW Pace Salsa incident). Not necessarily germane to the study at hand, but something that this research made curious about and interested to see further research on.

Finally, we arrive at “The Once and Future Information Society.” I admittedly began reading this article with thoughts of Peter Drucker’s “The Postcapitalist Society,” which I found to be a useful work (although I found that work to be much less the utopian paean to the information society than these authors). I enjoyed the authors’ self-deprecating nod to the ideas behind the information society and the fact that “they are likely to reassert themselves in the future, if only because of the complimentary self-image that they provide to intellectuals who embrace them.” Still laughing over here. I also didn’t expect to ever encounter Comte and Saint Simon again (though personally, I find Marx’s analyses of the feudal superstructures more convincing). The theoretical heart of their paper (and my major point of departure with a number of well-meaning intellectual friends) lies herein: “The idea that deep social conflicts are somehow based on inadequate understanding is a characteristic Enlightenment notion. The broad alternative consists of views that posit irreconcilable conflicts of interest as an enduring possibility in social life, regardless of the state of reliable knowledge or scientific understanding.” I personally stand firmly in the “alternative” camp, which leads to endless attempts to educate me out of my contrary position on any of a number of issues–as though disagreement arises only due to insufficient information, and not due to legitimate differences in opinions, values, and priorities. As a recent study from Pediatrics, as well as the whole idiotic anti-vaccine debacle (yeah, I said it!) has shown, you might be able to cure ignorance, but stupid goes straight to the bone. Or, to put it more politically, irreconcilable conflicts of interest endure despite the state of scientific understanding.

Before I make my next statement, I should qualify it with the fact that I have not read Porat, and so I might be missing some essential context. That said, the fact that he distinguished a programmer as an “informational” occupation and a carpenter as a “non-informational” occupation floored me. I might have yelled, “You’re killin’ me, Smalls,” but such an occurrence can neither be confirmed nor denied. And, all of a sudden, everything came back, again, to Polanyi: Porat stuck his fingers in his ears and said, “La la la, I can’t hear you, tacit information isn’t information, la la la.” The bit of theatre of the absurd at play is highlighted by the presumption that codification means that there is somehow more information at play, as opposed to simply more explicit information. In short, this article lays bare the assumptions behind the information society demagoguery.

With this article, much of my cynical concern was finally addressed. In particular, the glorious assumptions that knowledge, properly managed, will lead to information serving great social needs with enlightened intellectuals at its head is, indeed, little more than a positivist religion. Despite the assumptions of both social science and the dismal science, humans are not rational animals. So much of what we know, do, think, feel, and are is beyond the realm of cold analysis. Some of it is tacit, some of it is raw self-interest, some of it is emotional and sentimental, and some of it is straight up craziness. Does that mean we should stop studying knowledge management, or thinking about the role of information in our society? Of course not, but I’m a dang sight happier not pretending that we’re going to find the Holy Grail in there either.

Sources!

Hansen, M. T., Nohria, N., & Tierney, T. (1999). What’s your strategy for managing knowledge. Harvard Busindess Review. URL: http://consulting-ideas.com/wp-content/uploads/Whats-your-strat-art.pdf

Chua, A. Y. K., & Banerjee, S. (2013). Customer knowledge management via social media: The
case of Starbucks. Journal of Knowledge Management, Vol. 17(2), 237-249.
doi:10.1108/13673271311315196

Rule, J. B., & Besen, Yasemin. (2008). The once and future information society. Theory and
Society, 37(4), 317-342. doi:10.1007/s11186-007-9049-6