Individual and organizational Learning: Few reflections from management practice
My concept of learning – what it means and what makes it effective – has gone through a significant change in the last two decades. A significant – but not all – part of my educational experience can be summarised as learning about the existing concepts, understanding the relationships between them, finding out about experimental techniques and/or research methodologies and on occasions to aim for a higher level of conceptualisation to develop hypothesis and generate insights. Most of it was focussed on learning about what is already established and known in the field. This process led to a short-lived confidence in the “certainty” of knowledge acquired along with a belief that I know what is required to be done in situations, where this learning is to be applied.
Though the world has changed significantly in the last two decades, I think the above model still provides, if done well, a good foundation for being socially and/or economically productive in whatever field one endeavours to be in. This is also an approach which is easier to follow and explain (or “sell”) inside an organization. The learning process also appeals to analytical minds. – something that our educational and organizational processes work hard to maximise. However, upon reflection, I find that this understanding of learning process presents only a limited perspective on what one needs to do to become a better learner.
Following my experience of last two decades, my concept of learning has changed to include the following:
Effective learning involves open-ended an enquiry process
A robust learning is multidirectional as opposed to unidirectional. By unidirectional, I mean a sequential learning process that starts with assumptions and concepts, moves over to an understanding of cause and effect relationships, which in turn leads to a framework/model to generate hypothesis and/or predictions, and finally analysing the findings to develop recommendations/ insights. This is analytical reasoning at its best.
On the other hand, multi-directionality implies reflecting on the different facets of the issue under consideration. These facets include questioning the validity and relevance of assumptions. In physical and social sciences, important breakthroughs happened when assumptions were questioned. That questioning of assumptions can lead to useful insights is true both for path-breaking research and also day to day organizational life. We can remind ourselves that financial crises of 2008 itself was a result of widely held assumption that house prices do not come down.
To me, multi-directionality also implies reflecting/questioning the existence and certainty of an event, phenomenon or anything that we are focusing on in the organization. Frequently, it involves questions like how do we know for sure that an issue exists, that it corresponds to what everyone thinks it is, and that “matrices” measure what they claim to measure and relevant to the purpose. It also means that organizational cultures should “celebrate” the employees who raise questions, which are outside organizational comfort zone.
While many of the above implications can also be drawn from the concepts of single and double loop learning,1 given the new economic reality of knowledge based organizations, which are supposedly less hierarchal and also depend on variety of new disciplines/insights from employees at all levels, it is important that more employees at all levels engage – and given an opportunity to engage – in the above reflective practice to produce better organizational outcomes. In essence, robust learning involves working through the ontological and epistemological aspects of our chosen area of learning 2.
Effective learning leverages on other fields of knowledge
Learning involves being aware of and leveraging other related and unrelated areas of knowledge. For a long time, specialism and super-specialism has been celebrated, just as it should be. It is now needed more than before, because of knowledge proliferation and complex cause and effect relationships that now exist in many disciplines. There is, however, good anecdotal evidence of problem solving and breakthroughs (particularly from the research on creativity) when insights from another field have contributed to problem solving and progress in one’s own chosen area.
It is expected that fusion of knowledge from different industries/areas is likely to result both in new industries (such as 3D printing; it is speculated that it could potentially be used to print organs) and new concepts, products and innovations (as in renewable energy and personalised medicines). Similarly, progress in fields dealing with complex problems is most likely to be the result of integration of technology and knowledge from various fields. As an example, cancer research is now benefitting from the integration of knowledge from different areas, such as medical sciences (stem cell research and better targeting of cancer cells), information technology (big data and computing power), medical technology (sensors, Nano-technology and ultrasound waves to target cancerous cells), and wellness research (healthy lifestyles, meditation and exercises) It is likely that products and processes resulting from integration of knowledge from different areas that were considered an innovation in the past may be considered as “routine” in near future, and the “innovation standards” will go up.
What does it mean for the organizations? While some of the implications are well known (such as less hierarchy and better information flow), there are others which have not yet received due attention. As an example, since many of the ideas that rely on integration of learning from different disciplines may not result in commercially successful products, organizations will soon have CVs that will include both big failures and successes. This is already the case with firms like Amazon and Google. How would shareholders respond to this? How do we assess the performance of multiple team and leaders, who had failed say 60% of times in last five years? Since many of the innovative products are likely to result from fusion of knowledge, how do we identify/manage talent that works in a multi-disciplinary, open-ended, uncertain and – from a career point of view -riskier projects?
Effective learning needs “self-competition” and long term orientation
Learning yields most when it is curiosity led (this is relevant even when the immediate motivation is organizational problem solving) and results in the expansion of idea/opportunity options. For experts, it also means a continuous effort to supersede their own existing knowledge with new learnings, alternate interpretations and further advances towards a more generalizable model.
A good learning process leads to fresh questions and further learning pursuits, and in that sense, it is self-obsoleting and self-enhancing at the same time. It also means an effort to ensure that a good amount of learnings/knowledge at any point remains of recent origin/acquisition. While this is easy to agree with in theory, there are some important questions as to its practical usefulness for many reasons, such as lack of opportunities to employees to use even their existing knowledge to a great extent, and the fact that the developments in machine learning/algorithms and Artificial Intelligence (AI) will outpace an individual’s acquisition of “traditional knowledge” (i.e., concepts and cause and effect relationships) in an increasingly number of industries.
Is investing time to stay relevant – possibly at a financial cost – a sensible approach given that employees are in any case using a very small percentage of what they already know, and AI and machine learning are most likely to outpace their learning in any case? Should society be investing its time and resources to such learning endeavours? These are some important questions both at individual and public policy level, and one way to look at it is to explore what is actually the purpose of learning: Is it expansion of mind and exploration of possibilities/opportunities that lead to a better outcome for society/organizations, or is the purpose more transactional as to immediate improvement in job or career prospects?
Speaking generally, I think there is more emphasis on “reverse engineering” our learning goals/approach in the sense that individuals aim for a particular economic state of being, and then reverse engineer their learnings agenda and goals (Note: This also assumes that an individual “knows” which career/job will work best for him/her in the future – an assumption that may not be always true). For complex professions, such as medicine and engineering, this approach provides a strong foundation and helps both individuals and the society. This “reverse engineering” mind-set however continues long after an individual has gained entry into a profession and career.
Given the fact that competitive new products are likely to use knowledge from different disciples, the ability to connect “dots” is likely to be useful even from a transactional job point of view. Moreover, it is difficult for develop algorithms that connect “dots” from different disciplines, though some advances are being made in that direction as well. In addition, in fast changing economic and technological environments, having a broader set of learning/knowledge “portfolio” puts an individual (or organizations) at an advantage as more change means more opportunities to leverage on the broader skill-set, and a higher probability that a particular learning or skill-set may be relevant in at least some change scenario in future. It is likely that in future individuals will have multiple careers including few “micro careers” and will have learn new skills periodically to stay relevant and economically productive. Having a broader learning agenda expands the opportunities for “micro” and multiple careers.
Effective learning incorporates understanding the context
Learning involves finding out as much as about uniqueness as about the commonalities and patterns in a phenomenon or aspect under study. I believe that both methods (namely, study of uniqueness and finding out commonalities/patterns) play an important role in the learning process, and there could be a competition between them only when there are resources (including time) constraints or if the phenomenon under study lends itself to one rather than both methods of enquiry and even then effort should be made to enhance learning by exploring both methods.
In any other situation, it is important to the learning process that an effort is made to explore aspects that make a phenomenon (or any aspect under study) unique as well as similar to other situations (including from different fields).
Speaking from anecdotal experience, I find that an analysis of what made something unique (or different) is done mostly – but not always – when it has gone wrong, or when an organization wants to pursue an opportunity similar to ones that failed previously and makes a case that it is different this time (like it was the case in financial industry prior to financial crisis). The key organizational challenge in this regard is not as much to appreciate the need for using both of these methods (though that too could be an issue); rather it is on how to translate this insight into a healthy and disciplined organizational practice and mind-set, so that all can benefit in real-time. Few suggestions could be awareness training through case-studies, modifying existing processes (including modifying check-lists and standard templates used for reporting/reviews) to include specific sections on what makes situation under consideration unique and/or similar to other such situations and what it means for decision/action, and finding out whether there is a relationship between pros and cons of a decision with the two methods (i.e., whether pros/cons strongly correspond to what makes situation unique/similar to what worked in the past).
It is not implied here that one method is better than other, or that the decisions based on one method are better (or worse). The idea here is simply that decision makers should not get blind-sided by one view/method only.
Effective learning involves knowing the limitations of current knowledge
Learning involves knowing about a chosen field of enquiry, but equally importantly also knowing what one does not know and the limitations of one’s knowledge or experience. It means going from “known knowns” to “known unknowns” to finally “unknown unknowns”3. (Note: One could also add “known unknowable”).
While an inquisitive leaner is likely to experience limits of his/her knowledge every now and then, I believe it is also a function of one’s curiosity, and humility. Organizations are more successful when they navigate their future (an unknown information state) in an effective and efficient manner and therefore there could be a range of implications of this learning “lens”.
As an example, it is better that a leader makes a decision knowing it is best decisions given the “unknowns” than to pretend that the only considerations that matter are the ones that are known and “unknown” is irrelevant. If a leader has to make a decision with incomplete information (“unknowns”) and if s/he communicates and explains the decision to the team accordingly, then it later leads to better and open-ended reviews, alternate insights, and effective course correction down the implementation process.
Another implication is that organizations should celebrate employees who “do not know” as much as employees who “know”, because, depending upon the context, it could mean that employees who “know” everything are not stretching themselves on the learning curve, or have narrow roles or do not have opportunities to see the limits of what they can contribute.
Organization learning is not a new area in management theory and practice – it has been around for a few decades now. However, in the last decade, particularly after the financial crises of 2008 and general recession, both organizations and individuals face a greater challenge for a variety of reasons to engage in reflective learning and incorporate some of the observations above.
Some of the reasons that discourage reflective learning in organizations are reduced headcount and resources creating workload and time pressures, need for a faster decision making, and a short-term orientation and incentive to problem solving. However, I also believe that there is more upside – and also organizational necessity – to engage in reflective learning now, particularly since organizations have practically exhausted their limits to improve bottom line through cost cutting.
References/Notes:
- Argyris, C., & Schön, D. (1978) Organizational learning: A theory of action perspective, Reading, Mass: Addison Wesley).
- For an interesting account arguing that to succeed in business, it is better to study philosophy instead of management, please read https://www.theatlantic.com/magazine/archive/2006/06/the-management-myth/304883/
- While the terminology “known unknowns” gained popularity after it was used by former United States Secretary of Defence, Donald Rumsfield, it is not new and used previously by others as well, as the short article (link below) in “The Atlantic” explains. (https://www.theatlantic.com/politics/archive/2014/03/rumsfelds-knowns-and-unknowns-the-intellectual-history-of-a-quip/359719/)
