Humans are tribal. We need to belong to groups. But this instinct to belong is also an instinct to exclude. Besides the positive benefits of these social structures, they all share some undesired antipatterns and bubble effects, including:
- Silo Mentality: people and teams within the bubble want to protect their information, not share it with others in the same company.
- Limited Discoverability: learnings, knowledge, and information outside the bubble cannot be reached and discovery is limited (is this a universe or multiverse?)
- Poor Learning Retention: information and learnings are lost forever when people leave the company.
- Duplication: when sharing is limited, work is duplicated; the same ideas are developed and the same impediments are tackled across multiple silos.
When learnings become trapped in bubbles, knowledge is hidden. Teams face similar issues, run similar experiments, develop the same antipatterns, and fail to use each other’s learnings.
We can observe various forms of bubbles within organizations: role-based silos, agile, Scrum, Kanban teams, long-lived value stream–aligned teams, and so on.
1: Waterfall Bubbles
On a conference call about the effectiveness of the new Jira set-ups, a lengthy discussion took place about how to configure notification mechanisms when tasks move from one state to the other. At one point, I asked why the notifications were needed. What would happen if the developer forgot to move a task on the board and the notification wasn’t triggered? The response was silence. No one could think of any other way that the person in the next stage in the process would know that they had work waiting for them. Knowledge workers have become so accustomed to working with tools and in their own silos that it didn’t occur to them that they could actually speak to each other, pick up the phone, or bellow across the desks that they’d finished their task. Traditional, sequential, waterfall delivery methods create bubbles in each role-based silo. Analysts talk to analysts. Architects go to dinner together. Developers are down at the pub while the testers are testing. IT Ops are too busy fire-fighting. Information between waterfall bubbles travels by handoffs and document passing with loss of knowledge as described in Antipattern 8.1.
2: Agile Team Bubbles
The idea of agile teams comes with many positive behavioral patterns. They’re small, cross-functional, multidisciplinary, long-lived entities with a clear focus, accountability, and the autonomy to self-organize. Their members build inward-looking behaviors, not connecting and sharing learnings with the rest of the organization. They collaborate daily in person to plan and discuss progress, impediments, and opportunities. When agile teams work well, their members build strong social connections and loyalty. The team succeeds or learns together. As those connections strengthen, there is a risk that they form bubbles disconnected from the rest of the organization. Even with a positive organization for complex work, in the absence of deliberate intent, learning can be confined within invisible barriers instead of flowing freely throughout the organization.
3: Value Stream Bubbles
Long-lived teams built around long-lived value streams should provide an optimal, stable flow of communication and learning and enable teams to produce better designs. Even these teams-of-teams can become bubbles. The challenge is balancing how and when to direct communications only through the value streams or share them with the rest of the organization. In an effort to optimize the value stream information and flow of learning, organizations sometimes go as far as inadvertently cutting communication lines beyond the value streams. This fails to optimize for overall organizational performance.
ASREDS Learning Loop
To counter learning bubbles, the authors of Sooner Safer Happier developed the the ASREDS learning loop: Align, Sense, Response, Experiment, Distill, and Share.
The ASREDS Learning Loop
(from Sooner Safer Happier by Jonathan Smart, Zsolt Berend, Myles Ogilvie, and Simon Rohrer.)
The loop begins by clearly calling out Align, to ensure that there is clear alignment to the higher level intent, goal, North Star, mission, or outcome hypothesis. This is the first step of the learning loop—it installs vertical transparency (as we saw in Pattern 5.3), and it connects the otherwise disconnected bubbles of strategy and delivery teams. Determine your aligned hypothesis that you want to learn about here.
Once aligned, it’s time to Sense the context, the customer, terrain, history, behavioral patterns, antipatterns, underlying mental models, values, and one’s own learning so far. It is fundamental to learn and understand the starting point, the unique context. As G.K. Chesterton is attributed as saying, “Don’t ever take a fence down until you know why it was put up.” Start where you are. Subscribe to learning from others, and sense the outside world to learn new potential patterns of success.
Next Respond by designing one or more experiments in order to test the hypothesis. These could be new or they could be the amplification or dampening of previous experiments.
Experiment and Distill
Then, run the Experiment and Distill the results to generate insights and metrics. Discuss it with participants in the experiment; run a retrospective or debrief to identify learnings.
Finally, Share by publishing the learning and updating doctrines and patterns. This enables others to pick it up when at the Sense step. This final Share step in the loop is essential, and I find it is rarely done.
To read more, check out Sooner Safer Happier: Anitpattern and Patterns for Business Agility from Jonathan Smart, Zsolt Berend, Myles Ogilvie, and Simon Rohrer.