The Rebirth Of The Learning Organization

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

Eating Our Own Cooking

What do a doctor suggesting a patient diet, an IT person asking a fellow worker to start using a new application, a mom asking a child to eat something or an analytics expert asking a business person to trust statistical insights all have in common? They are trying to get other people to do things.

But as the old saying goes, too often, this suggestion comes across as “do as I say, not as I do.” We’ve heard other variations on this theme, such as “doctor, heal thyself” or my favorite, “eat your own cooking”.

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When I was a CIO, I used to tease some of the staff by pointing out they were all too willing to tell everyone else that they should use some new technology to do their jobs, but when it came to new technology in the IT world, the IT staff was the most resistant to change.

Among the most important changes that need to happen in many organizations today are those based on new insights about the business from analytics. But in big organizations, it is difficult to know how well those necessary changes are being adopted.

Analytics can help with this problem too. Analytics tools can help to figure out what message about a change is getting across and how well is the change being adopted? In which offices, regions, kinds of people?

Yet, it is rare for analytics folks to use their tools to help guide their own success in getting analytics to be adopted. Here, though, are two examples, the first about individuals and the second about organizations as a whole.

Individual Willingness To Change

A couple of years ago, the Netherlands branch of Deloitte created a Change Adoption Profiler (CAP) model of their clients’ employees based on the willingness to adopt changes. As they describe it:

“Imagine being able to predict who will adopt change, and how they will adopt it before the change has even occurred. At Deloitte, we have developed a data driven decision making method called the Change Adoption Profiler – it provides insights into your company’s attitude toward change and allows you to address it head on.

“The CAP uses a diagnostic survey based on personal characteristic and change attitudes. Unlike traditional questionnaires CAP combines this with behavioral data to understand the profiles that exist within the organization. The CAP provides reliable, fact-based analytics – provides client insights that support smart decision making, reveals risks and signals how to approach change at an early stage.”

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There is a nice little video that summarizes its work at https://www.youtube.com/watch?v=l12MQFCLoOs

Sadly, so far as I can tell from the public web, no other office of Deloitte is using this model in its work.

Organizational Analysis

Network analysis, especially social network analysis, is not a new focus of those in analytics. But, again, they don’t normally use network analysis to understand how well changes are being spread through an organization or business ecosystem.

One of the exceptions is the Danish change management consulting firm, Innovisor. They put particular emphasis on understanding the real organization – how and why people interact with each other – instead of relying solely or mostly on the official organization chart.

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This little video explains their perspective – https://www.youtube.com/watch?v=ncXcvuSwXFM

In his blog post, Henry Ward, CEO of eShares, writes at some length about his company’s use of this network analysis to determine who were the real influencers in the organization. They ended up identifying 9 employees, not necessarily executives, who influenced 70% of all employees directly and 100% through a second connection. A detailed presentation can be found at https://esharesinc.box.com/shared/static/8rrdq4diy3kkbsyxq730ry8sdhfnep60.pdf

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Given the value of these kinds of examples, the problem of not eating your own lunch is especially interesting in the analytics field. Perhaps it is new enough that many of its advocates still have the zeal of being part of an early, growing religion and can’t see why others might resist their insights. But they would be convincing if they could show how, with analytics, they did their own jobs better – the job of getting their organizations to achieve the potential of their insights.

Team of Teams

The book, “Team of Teams: New Rules of Engagement for a Complex World”
by retired General Stanley McChrystal and his associates Tantum Collins,
David Silverman, and Chris Fussell has been out for
more than a year. I hadn’t gotten around to reading it partly because I
wasn’t sure I wanted to read what I thought would be yet another
general’s exercise in self-promotion.   I’ve also been through too many
conferences filled with speeches from high ranking executives that are
essentially war stories in which they are the heroes of the story.

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So, when I finally had the time to read it at the end of last year, I was surprised to find that this book is one of the best recent books on management. It has been criticized by some as not really having anything new in it and merely reflecting the undue length of time it has taken a general to figure out these things.

While there is some truth to that, the fact remains that most large corporate and public sector organizations operate in the old style that McChrystal finds inadequate for a new era of change, complexity, and creativity. This includes even highly touted tech companies who reach a certain size and stage of maturity, even while they profess to be using agile approaches.

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For General McChrystal, it’s a question of what the organization is designed to achieve. Traditional “Taylorism”, which has been the model of most large organizations, aims to maximize efficiency. As part of that goal, he writes “organizations have implemented as much control over subordinates as technology physically allowed.” That certainly sounds like the traditional image of the Army and many large corporations.

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Instead, he argues that in today’s world, adaptability is much more important. This is a necessary response to deep and widespread technological changes. He also notes that those same technologies make possible a more modern, more adaptable organization.

Although much of what it’s in the book isn’t exactly new, the authors synthesize the material and lay it out to build a story that should be compelling to any senior executive.

The value of teams and the use of the intelligence of team members, rather than considering them cogs in a large machine, is explained well.  But the real challenge in leading large organizations is how to scale those benefits.

That’s where McChrystal and co-authors make a real contribution.

Here are some the key take-aways:

  • A systems approach and a more organic rather than mechanistic view is needed by leaders when looking at large organizations whose units must work together. Each person in the organization needs to maintain a systemic perspective too.
  • Frequent inter-team communication – “shared awareness” of the environment that develops into “shared consciousness” – is necessary to prevent teams from doing things that run counter to the needs of the overall organization.
  • On the latter point, perhaps communication is too weak a word because it implies that each side decides when and what to say. The General found instead that absolute transparency between units (and teams) was necessary. And, as he noted, “In traditional organizations, this constitutes culture change that does not come easily.”
  • Although this has been well known to organizational researchers for some time, the practice of using physical space to encourage this kind of approach is not widespread. General McChrystal relates his own and other organizations use of common spaces. Of course, in a world of increasingly virtual organizations it is especially important to create continuously operating virtual spaces, with full video, to achieve the same effect.
  • Where people from different teams couldn’t be physically next to each other, he set up “embedding and liaison programs to create strong lateral ties between our units, and with our partner organizations. Where systemic understanding mirrors the sense of ‘purpose’ that bonds small teams, this mirrored the second ingredient to team formation: ‘trust.’”
  • The leader as mastermind or chess master is yet another old concept to be thrown away and replaced by the model of a gardener who enables the ecosystem rather than directing it. We should not “demand unrealistic levels of knowledge in leaders and force them into ineffective attempts to micromanage.”
  • In order to be able to react with necessary speed to ever changing situations, organizational leaders need to abandon traditional control because “Individuals and teams closest to the problem, armed with unprecedented levels of insights from across the network, offer the best ability to decide and act decisively.”
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This book is an excellent guide to effectively managing large-scale operations to implement a strategy. But, much like the wars that General McChrystal was part of, it doesn’t focus on whether the larger strategy makes sense. That’s not a criticism of the book, just a realization that there are important considerations beyond its scope.

© 2017 Norman Jacknis, All Rights Reserved

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