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We recently featured a two-part article by Lesley Crane, considering the question of whether knowledge management is a science.  (Part I, Part II)  Alongside the article, we included an open survey asking readers what they think.  This caused quite a stir, and we had 186 responses in total. So, what did the community think on this question? 

Lesley’s Analysis

The headline news is that a clear majority – nearly 57% - consider KM to be a science, more than the naysayers (24%) and those not sure (19%) combined. Even more telling, of the 184 participants who shared their view on how such an accepted scientific status might impact on the practice of KM, a further clear majority (78%) thought that this would be positive. Impacts included increased support from top management (just over half), greater access to funding (more than a third), more credibility (57%), improved understanding and support from the workforce (just under half), and access to better facilities and resources (again, more than a third). That is pretty convincing, and paints a positive and beneficial perspective of scientific practices. But also, in contrast, suggests a professional discipline that is not getting the support it deserves or needs.

So, who were these participants? Almost half of them claimed to have the term ‘knowledge’ in their job title, with over 40% working at Director or Senior Manager level, and the rest at Manager or Team Leader level. Interestingly two-thirds of all 178 respondents to the question of how they got into KM came through formal study / qualification or had received work-based training. The picture that emerges is of a professional practice operating at senior or middle management level, most of who could be very nearly described as vocationally motivated. Moreover, there is the strong suggestion that KM could and would be so much more – if it had the right level of support from management and workforce, for instance. A scientific status might just help to accomplish this.

Survey participants were also given the opportunity to leave a comment, with almost half doing so – quite a large proportion. It is to these comments that I particularly turned my attention and analysis. First, I categorised them into ‘unambiguously positive’ (49%), ‘unambiguously negative’ (26%) or just plain ‘ambiguous’ (25%). Then I looked to see what primary themes were invoked in support of whichever cause the commentators pinned their colors to. The case of those who dispute the scientific status of KM is interesting.

First, those arguing against the scientific status of KM propose that, while KM might well draw on multiple science fields, this does not make it a science in its own right. Now, decades ago, many scientists might have agreed with that: multi-disciplinary was, to the purists, a dirty word, and not to be trusted. So, one observation that can be drawn is that those arguing for the non-scientific status of KM hold a rather traditional – even old-fashioned - view of science. This perspective plays out in the deeper analysis of the commentary: for instance, one commentator expresses the notion that KM may be built on the knowledge sciences with those principles applied in practice, but this does not qualify the practice of KM as scientific. I disagree: it qualifies KM as an applied science (see the original discussion - Part I, Part II). Another perspective suggests that because KM deals with human behaviour, this disqualifies it as a science. I know a whole lot of psychologists who would disagree with that one!

Cherry picking from some of the other negative comments, we find that KM is not a science because: it deals with qualitative not quantitative data.  (Ahem! Quite a substantial part of social sciences, for example, deal with qualitative stuff – my own work included); that behavioural sciences are not proper sciences (that sort of talk would cause a lot of behavioural scientists to pull on their fighting gloves); and KM has no body of knowledge or theory to call its own so it can’t be a science. On the latter point, I would point to the tens of thousands of academic publications in dozens of professional journals devoted to the discipline of KM, and its multitude of theory – so much that I have argued elsewhere that there is simply too much. Other commentators suggest that KM is no more than a theory (sic!), best practice, a methodology, or even just a culture. In contrast, I would suggest that not only is KM all of those things, but it is precisely these attributes amongst others which qualify KM as a science in its own right.

On the other side of the debate, those commentators who support KM as a science can be broadly grouped into three main themes:

• first, that KM is an art and a science; 
• second, that it is a complex social science or that it draws on various sciences; 
• third, that it is KM’s practices and methods which make it a science (e.g., harnessing and synthesising knowledge from diverse sources, measuring performance to inform knowledge of process, the study of structures and behaviours)

In other words, exactly the opposite to the arguments made by the naysayers. What I find revelatory about this is the richness of description of a professional practice which largely puts humans front and center, and which is dedicated to designing, mediating, customising and nurturing environments with the sole purpose of ensuring the best engagement of people and the highest productivity. 

Good analysts should always attend to what is not there, as much as what is. At this point the lightning bolt hit! Bang! A very nearly complete absence of “technology” in any of the comments! To understand why this is so astounding, know that the debate over the role – and culpability in failure – of technology in the context of KM initiatives has been a furious one in the academic literatures for decades.  It has also long been mythologised that the key skill of the knowledge manager is a native fluency in Sharepoint! Not according to the participants in this survey. Or if it is, it is not worth talking about.

I could draw many competing points of conclusion here. But, I think the most important one is of an emerging renaissance in the field of KM as both a field and practice deeply rooted in scientific endeavour, and which is no longer hall-marked by an insistence for technology as its defining characteristic. That, I would argue, is in no small part due to the increase in training and education within the practice itself.

The ability to learn and repurpose knowledge from a specific circumstance is a key to ingredient to innovation.  There are a number of ways that KM practitioners can leverage knowledge and learning.  Some of the techniques most used by KM practitioners include: (1) knowledge capture, (2) knowledge leveraging, (3) knowledge creation, (4) Lessons learned and (5) Best practices.

Learning always begins with a question, although finding the right question can be very difficult.  As Einstein said:  “If I had an hour to solve a problem and my life depended on it, I would use the first 55 minutes determining the proper question to ask, for once I know the proper question, I could solve the problem in less than five minutes.” 

Try asking these powerful questions to enhance learning and capture broadly applicable meta-knowledge:

• Can we derive or abstract a higher lesson from this?
• Can our work be captured visually?
• What are we doing here at a higher level – can we capture higher principles at work?
• What business are we really in?

The history of the Honda dirt bike shows how corporate learning, combined with a flexible or “emergent” business development strategy can lead to dramatic innovations.  As the story goes, when Honda first entered the US motorcycle market after WWII, the company planned to compete head-to-head with the iconic Harley Davidson.  With a shoe string budget and no track-record, the small team of Japanese sent to preside over the Honda motorcycle introduction soon found their product failing.

Strapped for cash, the team began to ride around on the smaller-sized motorcycles that had also taken to the US for personal transportation.  One of the Honda team members took to riding in the hills of California on weekends and noticed that many of the locals were admired his rugged, small Honda motorcycle.

The spark of innovation happened when Honda’s team was able to abstract from these learning experience that there might be an emerging American market for off-road motorcycles. The failing Honda team decided to take action on the new knowledge and try selling the small bikes. Rather than selling through the usual outlets – motorcycle dealers, they chose instead to sell the bikes through sporting goods stores. Honda’s off-road motorcycles quickly became a best seller and the rest is history.

The audacious Honda motorcycle team’s ability to abstract the Meta-Knowledge of a potential market from a few comments and observations is the essence of corporate learning. Their ability to flexibly to redefine the business to incorporate the new learning was ultimately a key ingredient to Honda’s innovative and successful entry into the US motorcycle market.

Lesley Crane continues her discussion as to whether or not KM should be considered a science. . . Our survey results will be published next week.

Consequently, one can envisage that a scientific field is characterised by dominant theory, a body of appropriate research and knowledge, and a lively research agenda. From an academic perspective, the field of Knowledge Management possesses all of these characteristics.

True, some academics are critical of the lack of solid empirical research (but it does exist) in favour of what is termed ‘normative research’[1], or  research which proceeds from a hypothetical and idealistic future position, asking what needs to happen or change in order to reach it. What further muddies the waters are two interdependencies: first, KM undeniably draws on multiple diverse fields for its theories and approaches (e.g., information economics, organizational culture and behaviour, artificial intelligence[2]), and second, leading from this, it is a field that is broadly polarised between those who treat knowledge as an object (and consequently are concerned with process and technology), and those who treat it as embedded in social interaction between people (thus, it is resident in behaviour). By any measure, KM is something of a mongrel! None-the-less, KM – at least as far as the academic field is concerned – is practised as a science. More accurately, KM is an applied science: that is, a science which applies existing scientific knowledge to develop practical applications.

But, what does the scientific status of KM mean for KM practice, ignoring for the moment whether or not KM is actually practiced within organizations as such? First, and most obviously, it means that KM is a multidisciplinary practice calling on diverse talents in organizational management, human resource management and human / behavioural psychology, the cognitive sciences, project management, communications and, of course, IT/ICT, to name just a few. This conjures the KM practitioner as a multi-talented individual with exceptional adaptive skills.

Secondly, it places the enterprise of KM into the realm of dealing with the facts. Why is that important? Well, we frequently resort to ‘scientific talk’ in our everyday conversations in order to make our arguments more persuasive. “Empirical accounting”, as it is known in the terminology of discourse analysis, is known to have the effect of rendering accounts more credible and truthful[3].  From this high level perspective, simply acknowledging KM as a scientific practice imports levels of credibility and rigour that might otherwise be absent. But that would be, in reality, a rather superficial approach.

To truly leverage the benefits and values of KM as a field of science would obviously be to approach its practice in a scientific way. It would mean changing the way that strategies are developed and implemented from a reliance on ‘it worked for so-and-so’, to an adherence to formal and informal testing and trialling, adopting methods not only designed to deliver rigorous results, but results which are measurable in a meaningful way. And it means acknowledging that sometimes we can be wrong. But even results which don’t support our goals can be valuable[4]. That may sound counter-intuitive in terms of the ordinary workings of the organisation which typically frowns on error. In science, all results are meaningful and valuable, if derived from robust and valid research.

Treating KM as a science in practice also means acknowledging and acting on the understanding that sharing knowledge with other KM practitioners is vital to the development of the field of practice. That is, contributing to building the knowledge in the field. Without such co-operative and collaborative sharing one is simply working in a vacuum and people in vacuums have a habit of making it up as they go along, or of relying on repeating what has ‘worked in the past’.

One final implication of practising KM as a science speaks to the values and importance of formal qualifications and accreditations. It is true that the history and lore of KM is strewn with stories of individuals grasping the mettle and pulling off heroic feats of organizational knowledge accomplishment, all without any formal training or education in the topic. Fortunately, much of that valuable experience has been captured in books and articles. But I think of those individuals as the ‘early adopters’ of KM, and KM cannot and will not survive with an endless succession of would-be early adopters. What is needed now are knowledgeable and educated radical thinkers who can and are willing to shift the field from a vague but well-intentioned pseudo-management practice into a rigorous field and practice of scientifically-based management. As such, there is then the potential to build on successes, and to build a worthy and credible field of management and practice.

If the top agenda for C-Suite professionals is innovation and creativity, then perhaps it’s time to get innovative and creative with KM itself – in a scientific way, of course.

It's not too late to give your opinion!  Take our short, anonymous survey here:   Is KM a Science?

It comes as no great surprise that a recent investigation of C-Suite respondents finds creativity and innovation, and creating a truly service culture to be top priorities. To this wish list we could easily add sustainability, managing change in a disruptive VUCA environment, and responding to the volatility of consumer demands. All of these issues share one thing in common – they position knowledge and knowledge workers front and centre.  Easy to say, not so easy to do.

It cannot have escaped the interested reader that Knowledge Management (KM) continues to be tarnished by stories of failure: the academic literature variously apportions failure to up to 70% of KM implementations, particularly those with a strongly IT focus. 70%! Beyond academia, public forums like LinkedIn also carry their share of KM misery. There is also the matter of how KM relates to Big Data, and the issue of whether KM remains relevant in its wake.  Something is needed.

The argument here is that addressing the question of whether KM is a science might just hold the clue to how KM can finally emerge as a singular discipline, the importance and potential success of which can, at last, be cast beyond doubt.  

How could a scientific status offer a way out of the doldrums? Is it a science – could it be a science? Would it matter, particularly to KM practitioners? What would be the implications for KM practice, and how would this help KM’s case? However, addressing the core question is no straightforward matter!

Quite simply, to forensically examine the question of whether KM is a science or not requires at least some consensus on what we mean by three concepts: (1) science, (2) KM, and (3) knowledge.  Such a consensus does not exist on any account. For each, there are countless books and articles, and any number of (often heated) forums. In fact, the question over the scientific status of KM has itself a lengthy history in the academic literature. It would be impossible to encapsulate all of these perspectives here, but one cannot simply avoid the question. So, at the risk of further simplicity, I propose some common sense criteria for ‘what is science’, leaving the reader to apply their own definition for KM and knowledge.

Science is the accumulative practice in which new knowledge, acquired through rigorous observation (empiricism) and experimental research, builds on the foundation of existing knowledge. So, science is defined by its research, both in terms of accumulated knowledge, and its methods. Without wishing to become lost in the maze of debates over the currency and value of ‘experimental methods’ and ‘the empirical approach’, the fundamental perception of science is that it deals with the facts.  Most importantly, science posits that facts can be repeated or falsified through testing whereby theory is supported or discarded. Science proceeds either from a position of a theory of a state of affairs which is tested, or it conducts tests then formulates a theory to explain the test results in the most parsimonious way possible. But the key thing is that science deals in facts – knowledge. Now that statement in and of itself is the topic of considerable debate, but for the purposes here, it is an adequate proposition.  (click here for Part 2)

What is Your Opinion?  Please take our survey and let us know:  Is KM a Science?

Part Two of this article will be published next week, along with the survey results . . . stay tuned!