the agile sensemaking model

“Research shows that teams will organize themselves in different ways in response to how different types of complexity strains their sensemaking capacities. In order to increase their sensemaking potential, teams will reorganize their relationships in recognizable ways. We can think of these as emergent patterns of collective sensemaking.” —Bonnitta Roy

The increasing complexity of work is a result of automation, such as AI & robots, who are taking away any repetitive tasks, leaving barely repeatable tasks for humans. In addition to this automation of any work that can be described in a flowchart, we also have a larger number of human connections to deal with and humans by nature are complex. Robin Dunbar showed that we are only able to have a maximum of about 150 real human relationships before our cognitive capabilities are maxed out. Note that 150 is the size of an infantry company, a standard size that has stood the test of battle and time. But I, and many others, have thousands of connections on social media platforms like LinkedIn. How can we make sense of these?

Working in complex environments requires constant sensemaking, connecting outside the organization with the work being done inside. Increasing awareness of new ideas, methods, and processes often comes through serendipitous encounters outside the workflow. Getting work done today means finding a balance between sharing complex knowledge to get work done (collaboration), and innovating in internet time (cooperation). We have to develop methods to connect cooperative learning with collaborative action. Work is learning and learning is the work. It’s just that learning today has little in common with the education and training of yesterday.

“With every industrial revolution, there has been a corresponding learning revolution that, at the time, looked prohibitively expensive. However, the cost of maintaining the status quo in the past was the cost of missed opportunity which, in many cases, was a fortune.” —Jesse Martin

Learning is the great opportunity in organizational design today. The challenge is to connect knowledge flows inside and outside. A major factor is decreasing control mechanisms and enabling temporary, negotiated hierarchies to get work done. This work is done by individuals who are continuously engaged in sensemaking with their work teams, in communities of practice with their peers, and outside the organization in looser professional social networks to stay connected to the evolving economic and political realities.

Learning at work means enabling individuals to take control of their professional development. Workers in a creative network economy are no longer replaceable machine parts, filling defined job descriptions, but rather knowledge artisans, choosing their work and tools. This type of work is the counter-force to the majority of the gig economy where workers are merely training machines to replace them over time. For example, an Über driver is just a training vehicle for autonomous cars. Knowledge artisans are the future of creative, passionate, curious, and even humourous human work. But to do this kind of work we need organizations designed around agile sensemaking.

The challenge for organizations, especially larger ones, is to find ways of understanding what is happening throughout the system and ensuring it is communicated within the network. Knowledge artisans have to seek new ideas from their professional social networks and then filter them through more focused conversations with their trusted communities of practice. They can make sense of embryonic ideas by doing new things, alone or with their work teams. Knowledge artisans use the implicit understanding gained in their communities and networks to discern with whom and when to share their knowledge.

Communities of practice in essence act as filters of new knowledge in order to find competitive knowledge for the organization. People who understand the context of the work teams must therefore participate in communities of practice, as only they can identify what new knowledge could be competitive. Knowledge artisans need time and support to get away from their teams and see the bigger picture.

Radical innovation only comes from networks with large structural holes which are more diverse. This is why social networks cannot also be work teams, or they become echo chambers. Work teams can focus intensely on incremental innovation, to get better at what they already do. Communities of practice, with both strong and weak social ties, then become a bridge on this network continuum, enabling both individual and interactive creativity.

Working and learning in perpetual beta — constant change while getting things done — requires agile sensemaking.

The Agile Sensemaking Model (2018)

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