What does scalable learning really mean? I’ve been writing and talking about this for a while now including here, making the case that this will be a key driver of institutional success in the years ahead. In the course of conversations, I’ve discovered a lot of misunderstandings regarding what I really mean by scalable learning, so let me take this opportunity to clarify my perspective.
Why is scalable learning so important?
In the Big Shift, we’re rapidly moving from a more stable environment to a global landscape that is shaped by exponentially improving digital technology infrastructures. In the face of these exponential changes, if we’re not learning faster, we’ll rapidly fall behind. But what does learning really mean? In the context of a rapidly changing world, learning means developing new shared practices that can increase impact in a world of mounting performance pressure.
Free learning from the prison of the training room
First, let me emphasize that the learning I’m talking about doesn’t occur in a training room – it occurs in our day to day work and living environments. If we’re talking about developing new shared practices, it’s far more effective to do that in the environment where these practices are going to be applied, not in some artificial environment. Training rooms are fine for transmitting existing explicit knowledge, but not very effective for developing new shared practices.
Expand learning well beyond knowledge management platforms
Knowledge management platforms have largely been organized around sharing existing knowledge. While this may be marginally helpful, the key imperative in a rapidly changing environment is to find ways to develop new knowledge, rather than merely sharing existing knowledge.
Tacit knowledge is far more valuable than explicit knowledge
In rapidly changing environments, it’s important to realize that tacit knowledge trumps explicit knowledge. The latter can be articulated and written down and it usually takes time before it can be expressed clearly and coherently to others. Tacit knowledge is within our heads and we have a hard time even expressing it to ourselves, much less to anyone else. Because tacit knowledge is generally newer knowledge, emerging from new experiences that we’ve encountered, it’s often the most valuable knowledge, providing us with insight into how to act in a rapidly evolving environment.
Tacit knowledge becomes accessible through shared practice
Because it’s so hard to express, tacit knowledge is not easily accessible. The best way to access it is to work together and to observe the practices that emerge from this tacit knowledge. By working together, we also develop deeper, trust-based relationships that create a safer environment for us to explore new insights with others in our group that we have a hard time expressing to ourselves.
Tacit knowledge emerges from productive friction
The key is to move beyond accessing existing tacit knowledge and to work together to develop new tacit knowledge. This involves addressing unexpected needs and opportunities through the development of new practices. While we each may have some ideas about the practices that would have greatest impact, we are far more likely to develop higher impact practices if we come together and challenge each other’s ideas to come up with new practices that none of us would likely have developed on our own. This requires productive friction: the willingness to challenge and debate each other’s ideas in an environment that encourages diversity and mutual respect.
Let theory emerge from practice
Rather than sitting around and debating for prolonged periods, it’s far better to move as quickly as possible to action to test various approaches and determine which practices can lead to the highest impact on a consistent basis. As we accumulate practice in new environments, we can then start to look for patterns that will generate theories about why these practices lead to such high impact. Given how rapidly our environments are changing, these theories will likely lag our practices. We need to be continually evolving our practices to refine our theories.
Encourage learning in all parts of the organization
We are under increasing performance pressure and we can’t afford to silo our learning in certain parts of our institutions. Everyone in the organization needs to be learning faster by evolving new shared practices, whether they are research scientists in a laboratory or janitors trying to maintain our facilities. The institutions that will succeed in the Big Shift are those that help everyone to accelerate learning, rather than restricting it to a privileged few.
Focus on results and let learning be a by-product
We need to flip our learning mental model on its head. Rather than focusing on learning as the primary goal, we should shift our focus to accelerating performance improvement and let learning be a by-product. The goal is to improve performance more rapidly – that’s why focusing on developing new shared practices is so powerful. It provides us with results that we can measure and learn from, rather than investing heavily in training programs and taking people out of their working environments. Performance improvement accompanies learning, rather than lagging behind it.
Create environments that accelerate this kind of learning
If we took scalable learning seriously, we would apply design thinking and design methodologies to systematically redesign our work environments with the primary design goal of accelerating learning and performance improvement. I have been unable to find a single company that has attempted this, although our research uncovered 75 examples of companies that had redesigned slices of work environments with the result of accelerating learning.
Create and find ecosystems that can scale learning
And, if we take scalable learning seriously, we won't stop at the four walls of our enterprises and narrowly focus only on our employees. Instead, we'll seek to participate in expanding ecosystems that will help us to build deep, trust-based relationships with a growing number of third party participants that are all driven by a desire to learn faster together. Our research has helped to identify the characteristics of these kinds of ecosystems here and here.
Cultivate passion as a key driver of learning
No matter how much we redesign our work environments and expand participation in learning ecosystems, we’ll never harness the full opportunity of these environments unless we catalyze and amplify a specific form of passion among all of our participants – the passion of the explorer. We discovered this form of passion in our research on environments that produce sustained extreme performance improvement. The bad news is that only about 12% of the US workforce has this form of passion today. That’s not an accident, since our existing institutions, built on a rationale of scalable efficiency, rather than scalable learning, find this form of passion deeply suspect and do everything they can to squash it or at least restrict it to after-hours activities.
Provide effective leadership to scale learning
Like most things in organizations, the leaders help to define the culture and values. If leaders don’t embrace scalable learning, it will never scale. Here’s the challenge. The mark of a strong leader in a scalable efficiency environment is someone who knows everything, who can be relied upon to provide answers no matter what the issue or question. In a scalable learning environment, the most effective leaders are those who have the most powerful questions and who invite others to come together to discover the answers. They help to focus others on the questions that really matter. Perhaps even more importantly, they express vulnerability by acknowledging that they don’t have the answers and want help in finding the answers. In sharp contrast to scalable efficiency environments where having questions is a sign of weakness (you’re supposed to know what needs to be done), this signals to others that it’s not only OK, but essential, to have questions and to ask for help in discovering the answers.
Focus on trajectory, not snapshots
Finally, let me add that performance in a scalable learning environment is continuously evolving. Rather than focusing on snapshots of performance at any specific point in time, scalable learning organizations are relentlessly focused on the trajectory of performance – not only whether performance is improving over time, but whether it is accelerating. If it’s not accelerating, it’s not good enough. In an exponential world, we need exponential improvements in performance.
Bottom line
Hopefully, this brief post has helped to clarify what I mean by scalable learning. It’s certainly not learning in the traditional sense. It’s a very different and very powerful form of learning that, if effectively harnessed, can help all of us to achieve much more of our potential while having a far greater impact on the world around us. But, if we take it seriously, we’ll need to re-think everything. The time is now.
from Edge Perspectives with John Hagel http://ift.tt/2dtrlr6
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