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The survival of any company depends on its ability to respond to changing circumstances, in other words to learn from the market ecosystem and change based on that learning. Establishing continuous, data driven learning methods within teams and ecosystems is a powerful leading indicator of future agility and corporate performance. Most learning methods employed today however are not focused on how teams use learning to recalibrate teaming, workflow, and organizational decision making, but instead, on how digital products perform, and how customers of these products engage. This learning “blind spot” is why so many companies struggle with the pace and surprise of digital innovation.
Learning can’t just be about what customers think of the digital products we build, but must also include an active and ongoing recalibration of how decisions, work, and teams function based on an active and data driven learning model.
Industrial Age Approach to Learning
The industrial age created a pressing need for workers with vastly different skill sets than the agricultural age produced. This new demand led to the advent of a collective form of corporate education that embraced a learning model strikingly similar to management model that was also being institutionalized. Learners gathered in a central location, lined up in desks before a teacher who was the sole source of knowledge and the keeper of all the right answers.
This model treated learning like an industrial process, an assembly line of up-skilling workers. It also oversimplified problem solving and established a very narrow worldview by insisting there was one right answer. Reality was reduced to black and white, right and wrong, rules and procedures rather than a rich environment that encouraged exploration, innovation, and complex problem solving.
Just as a manager’s desk was positioned above factory workers, to easily observe and correct them, training was for trainers to observe and discipline learners. It was far more efficient to confine learning to reviewing standard operating procedures (SOPs), rather than, providing a shared experience that mirrored the complex nature of working life. (see our previous post, Digital Leadership Requires Ecosystems, Not Machines).
Although the ecosystem of corporations has evolved, learning methodologies have remained largely the same. We still gather learners in a sterile room and ask them to listen to a lecture, now aided by power point slides and computers instead of chalkboards. Seldom do we address complex issues, those that have no readily available answers, or situations that are generated by the students, reflecting their working reality. We simply introduce new skills and ideas, ask for questions, then proceed to the next lecture.
Systems-Based Learning
Cognitive neuroscience has proven the machine age classroom model is incompatible with the processes used by the brain to acquire knowledge. Post-training assessments also suggest minimal transfer from classroom to work environments, yet the “classroom briefing” model is still preferred by management and learners alike, partially because it is familiar and provides a degree of anonymity.
In a rapidly changing, highly competitive environment, where organizations lament the lack of innovation, employing industrial age learning principles is self-defeating. This can only lead to more of what we already have: lack of engagement, poor responsiveness to competitive change, and employees who learn only in a training environment. If business ecosystems are changing so fast, why haven’t learning methodologies changed as well?
Learning to Learn
When viewing organizations as ecosystems it’s useful to examine how new ideas are discovered, propagated and embedded. Large seminars seem like efficient solutions because they move information to groups of people with minimal time commitment. Surveys even show that employees prefer “briefings” to engaging in “sense making” because is less threatening than interacting with new ideas.
This approach not only stifles change in the corporate ecosystem, it also inhibits change in the individual. An organization’s approach to learning is ultimately reflected in employee engagement (in other words, how they develop themselves), innovation (on the job learning), and collaboration (group learning). Learning is the fundamental mover and shaker of organizational change, and it in turn mobilizes employees to stay current, obtain expertise, and innovate.
As Daniel Pink reveals in his book Drive, the pursuit and acquisition of mastery is a more profound motivator than any financial reward a company may provide. And mastery is driven by autonomy (learning in situational context) and purpose (a meaningful reason to learn). For corporate learning to move into the era of the knowledge worker, organizations must design programs to provide these three motivators: purpose, autonomy, and mastery.
