Dealing with uncertainty by opposing change

Adaptability is often sought out in employees. Individuals are stimulated to adapt to changing work contexts, tasks, and tools. Individuals working in teams also experience this need, just at the team level, meaning that all team members needs to adapt. For the team to be adaptive, you need adaptive individuals. The assumption is that once you put several people who are good at dealing with change in a team, the team will be adaptive and able to deal with unexpected and unfamiliar situation. Now this depends on how the concept of team adaptability is defined. The assumption in the preceding lines is that team adaptability emerges from individual adaptability, and the more team members have high levels of adaptability the better.

But what if mean adaptability is not important but variance in adaptability? Stay with me. It could be that it is not so much important for all team members to have high levels of adaptability, but only for some team members. The team members who are not that well able to deal with change can function as devil advocates. They will question the need for change, and help the adaptive team members elaborate and articulate clearly on their steps and action plans. A mixture of low and high adaptive employees could create a natural setting for team learning to occur through co-construction of knowledge and constructive conflict. Of course, the level of variance is important, as too much of a (potential) good think can be bad.

To understand better what teams faced with uncertainty go through, we need to borrow a concept traditionally applied to individuals. In the field of cognitive psychology adaptive expertise is an individual’s ability to deal with unfamiliar problems. Individuals develop this type of expertise if they are allowed to perform various tasks, work in an environment that values learning above performance, and are able to reflect on their domain skills. The perspective that knowledge is changing and being an expert requires continuous learning and evaluation is crucial.

Another important paper contributing to the concept of adaptive expertise is by S. E. Olsen and J. Rasmuss. They explain that when individuals perform a task, they first just blindly apply a skill (skill-based thinking). It’s like driving a car. We know how to do it, and just do it. No thinking required. For other work, example consulting, that means that we recognize the problem of the client, and select a tried-and-tested solution, maybe adapt it a bit to the characteristics of the client (e.g., size, industry). But still not much thinking is required. But, when there is nothing in our ‘skill memory’ we need to dig deeper into our brain and examine the rules that guide us to select a specific skill, or method (rule-based thinking). Now we have to start thinking. As an example, I’m always driving a manual car. Switching gears is automatic for me. It is skill-based and doesn’t require cognitive effort. But I once drove an automatic car. My first challenge was to decide what to do with my feet. Where do you put the 2nd food? I couldn’t rely on my skills, but had to inspect my rules (“Use right foot to break or accelerate and left foot for clutching”). The clutch didn’t exist, so the left foot had no use and was put aside. Driving was easy – except that my right hand kept on searching for the gear knob to switch gears. But when we are confronted with an unfamiliar situation, checking out the rules will not be sufficient. We need to examine our knowledge about why a certain rule should be applied in a specific situation (knowledge-based thinking). We therefore have to inspect our mental model about the situation and build a new mental model with rules and skills that fit this unfamiliar problem. Back to the example of driving a car, if we sit in a self-driving we need to re-examine our mental model of “sitting in the driver seat of a car” and develop new rules and skills. Can we watch movies? Work on a paper? Do conference calls? Or should we still look at the road? Following the consulting example, we need to further examine our knowledge about a client’s industry, maybe re-categorize the client’s, or redefine what it means to consult this specific client.

The same process can be applied to teams when they are confronted with unfamiliar situation. Instead of following routines (skill-based thinking), they examine why a certain process or procedure is followed (rule-based thinking), and if necessary develop a new mental model of the situation (knowledge-based thinking) to tackle the problem. As this happens at the team level, every team member can chime into the process, creating opportunities for developing new knowledge, inventing new products and procedures, and having huge – hopefully productive – task conflicts. During the redesign of mental models, those team members who do not like change are crucial for pointing out potential fallacies. It is a delicate balance between listening to their concerns with empathetic ears without giving in to every “but”, and making these no-change agents gradually feel comfortable with the new mental model.

Susannah Paletz from University of Maryland and her team shows that when teams adapt to unfamiliar situations and develop new mental model, these innovative solutions become part of the teams’ knowledge, ready to be used when the same situation appears. New mental model turn into rules and skills to be used by the team in future situation.

Academic bullet

  • Staff teams to include employees with high and low levels of adaptability. Train the team to develop psychological safety.
  • Log your changes to create an inventory of ‘new routines’. This should be done by a change proponent and opponent. Make explicit
    • Change triggers: What external or internal factor required a change in routine?
    • Change focus: What needed to be changed? Procedure, policy, product, service
    • Change Outcome: How has the ‘change focus’ be modified.
    • Contact details

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