Among the more ambitious and expansive CEOs, there’s a special kind of holy grail – transforming their organizations into learning organizations. Jack Welch, former and famous CEO of GE, put it this way in the 1990s:
“an organization’s ability to learn, and translate that learning into action rapidly, is the ultimate competitive business advantage.”
The Business Dictionary defines a learning organization as an
“Organization that acquires knowledge and innovates fast enough to survive and thrive in a rapidly changing environment. Learning organizations (1) create a culture that encourages and supports continuous employee learning, critical thinking, and risk taking with new ideas, (2) allow mistakes, and value employee contributions, (3) learn from experience and experiment, and (4) disseminate the new knowledge throughout the organization for incorporation into day-to-day activities.”
Or as Peter Senge, one of the founders of the learning organization movement, has famously said in 1990:
“A learning organization is an organization that is continually expanding its capacity to create its future.”
As you can see, this dream started more than 25 years ago.
By the first decade of this century, however, Mark Smith wrote:
“[W]hile there has been a lot of talk about learning organizations it is very difficult to identify real-life examples.”
The companion in thought of the learning organization movement was the knowledge management movement. Its goal was to capture, organize and distribute knowledge among the members of an organization.
But, in his 2014 paper, “A Synthesis of Knowledge Management Failure Factors”, Alan Frost was already conducting autopsies for the failure of knowledge management initiatives in many organizations.
In some ways, this reminds me of the first great wave of Artificial Intelligence in the 1980s when a lot of effort went into trying to codify the knowledge of experts into expert systems by extensively questioning them about their decision processes. It turns out that it is hard to do that.
Often experts – the knowledgeable ones – can’t really articulate their decision rules and to make matters worse those rules are at times probabilistic. Like other humans, experts often seek to develop rubrics to simplify a problem, which unfortunately can limit their ability to continue to observe what’s happening. Human perception, in general, in an imperfect instrument.
Thus, even if an organization is successful in widely distributing the knowledge developed by its staff, it may be just propagating ideas that are, at best, only partly true.
All of these factors, and many others, has slowed down the march to the dream of learning organizations.
But now we are possibly at the beginning of a rebirth of the learning organization.
What’s different today? Analytics and big data make the process of organizational learning much easier and better. Indeed, it is perhaps time to add analytics as a sixth discipline to Senge’s Five Disciplines of a learning organization.
After all, it’s not that people don’t know things that are important to an organization’s success – it’s just that they don’t know everything that is important and they can’t or won’t keep up with the torrent of new data vying for their attention.
The traditional gathering of the human knowledge combined with the continuously improving analytics models can achieve the dream so nicely stated by the executives and visionaries of twenty-five years ago.
For example, instead of trying to interview experts at length to capture their knowledge, today, someone in analytics would prefer to review the thousands of cases where the characteristics of the case, the decision by an expert and outcome was known. Then some kind of machine learning would search for the underlying patterns. In that way, the expert’s tacit understanding of the world would arise out of the analytics.
Nor does this cut out experts in the knowledge acquisition process. It just changes their role from being a memoirist. Instead, the experts can help kick off the building of the model and even assist in interpreting the results of the analytics.
Once the learning has begun, there is still much to learn (no pun intended) from the pioneers of this field. While they had great difficulty obtaining the knowledge – feeding the learning organization – they knew the rules of distributing that knowledge and making it useful. That is a lesson that today’s folks specializing in analytics could learn. Among these:
- The importance of organizational culture
- Leadership interest and support – especially for open discussion and experiment
- Measurement (which would certainly provide grist for the analytics mill)
- Systems thinking
For an illustration, see “Evidence in the learning organization” from the National Institutes of Health, in which these issues are focused on the medical profession.
If a marriage of the learning organization and knowledge management movements with the newer focus on analytics takes place, then all of those fields will improve and benefit.
© 2017 Norman Jacknis, All Rights Reserved