I Thought We Agreed

Team leaders want meetings to end with agreements that lead to concerted action. Much of the advice on team meetings is about how to create alignment. The assumption being, if we agree in the meeting then we’ll act on our agreements after the meeting.

What Really Happens

We know from experience that the vigorous head nods at the end of a discussion don’t always produce the outcomes we appeared to want. In fact, we’re often so relieved to see the head nods, we don’t bother to confirm what people are really thinking when they seem to agree. Here are few possible interpretations of a nodding head:

  • This is a good plan. I’m ready to make it happen.
  • I can live with this idea, but don’t expect me to make it a priority.
  • This will never work, but I’m not going to derail the meeting.
  • If we all nod, the meeting will end.

What can a team leader do to increase the odds that apparent agreement will turn into productive activity?

CADA

The CADA Framework describes four distinct team conversations once a proposed course of action has been presented or developed. In each conversation, the team adopts a specific attitude.

  1. Be Curious
  2. Be Analytical
  3. Be Decisive
  4. Be Accountable

Curious

The team agrees to set aside its reactions and judgments about the proposal. The team asks questions about the basis for the proposal and the implications of acting on the proposal. For example:

  • What information sources were used to shape the proposal?
  • Who will be impacted by adopting the proposal? How might they react?
  • How will we know it’s working?

Analytical

The team makes distinctions between facts and opinions about the proposal. The team asks questions about the risks and benefits of the proposal. For example:

  • What are the pros and cons of the proposal?
  • What options were rejected? Why were they rejected?
  • Given the risks, are we better off doing nothing? If we move forward, how will determine the most appropriate implementation timing?

Decisive

The team reaches a conclusion based on their role in making the final decision. The team asks questions about their level of commitment. For example:

  • Who else will need to weigh in before we can act on this decision? What are their thoughts?
  • How will we talk about the decision to stakeholders?
  • What do each of us need to feel better about any aspect of the proposal we have doubts about?

Accountable

The team comes to trust that we will each make good on our commitments. The team asks questions about dealing with next steps and obstacles. For example:

  • What will we do next to move things along?
  • What barriers to successful implementation do we anticipate and how will we deal with them?
  • How will we share with each other information about what’s working and what we’ve learned?

The key to using the CADA Framework successfully is ensuring that everyone is in the same conversation at the same time. For example, don’t allow people to get analytical when giving the team time and space to be curious.

We feel relieved when we align on something. Sometimes we feel worn out by the effort required to find consensus. When possible, you may want to follow up an alignment meeting with a separate CADA session when people are fresh, and they have been able to reflect on their conclusions before discussing implementation.

Finding Scarce Insights in Abundant Information

Data and information are essential to solving problems well. Data and information are abundant these days. So why do we feel less able to figure things out and less confident about knowing what to do?

Too Much of a Good Thing

Part of the problem is that we have too much of a good thing. At all times and in all places, Information and data are effortlessly accessible. We are conditioned to prioritize incoming alerts and breaking news. We are awash in information, most of it unsatisfying. It’s hard to quench your thirst if you’re trying to drink from a firehose.

First, a working definition to help us differentiate data from information. Think of data as the unorganized facts and figures we detect with our various tools and measuring devices. Information is what you get when someone processes, structures, organizes, or otherwise interprets the data. 75248 is a number, it is data. When 75248 is recognized as a Zip Code, the data becomes information.

A Better Solution

One solution to the too-much-of-a-good-thing problem is to collect less data. A better solution is to learn how to transform abundant data into insightful information. Insights help you solve problems, but insights are hidden. Insightful information is better than obvious information in the same way that an x-ray image of a painful shoulder is better than a visual examination of a painful shoulder.

Better, more insightful information helps in four ways

  • It helps you avoid solving the wrong problem
  • It reduces the risk of missing something important
  • It generates unconventional options
  • It ensures that previously excluded perspectives are seen, heard, and valued

Solving problems is about changing situations. If you want to change a dissatisfying situation, you can think of your challenge as a tug-of-war between the forces holding things in place and the forces motivating change. Kurt Lewin first developed this way of thinking about problem-solving in the 1940s; he called it, “Force-field analysis.”

SCAN for Insights

At Unstuck Minds, we think of our SCAN model as a simplified version of Lewin’s force-field analysis. SCAN stands for Structures, Context, Assumptions, and Needs. Structures can be thought of as the ways we currently do things. Context can be thought of as what’s going on in the external environment. Assumptions can be thought of as our unquestioned beliefs. Needs can be thought of as the desires, concerns, and perspectives of people we should include.

To make it easier to identify the Lewin’s force-field elements, SCAN is made up of two dimensions that focus on restraining forces and two dimensions that focus on driving forces. Structures and Assumptions on the left side of the model tend to keep things stable and preserve the status quo. Context and Needs, on the right side of the model tend to introduce destabilizing changes.

How to Uncover Insights

Let’s say you’re an executive who has formed a team to tackle a thorny organizational problem. You fear that after the team has spent a lot of time researching and organizing their findings, you’ll be left with voluminous information, very few insights, and no clear point-of-view or recommended path forward.

Instead of waiting to see what the team comes up with, request that they organize their presentation based on the SCAN framework:

  1. Structures: What are we currently doing that will make it hard for us to implement an improvement?
  2. Context: What is changing in the environment that requires a response or provides an opportunity?
  3. Assumptions: What unquestioned beliefs about our situation are worth challenging?
  4. Needs: Who should we include in our thinking and planning; what matters to them and what do they think?
  5. Now What?: What insights and options emerged from your work and where should we focus our resources and efforts?

It seems counterintuitive to seek more information as a solution to the problem of information overload. But learning to form insights helps us manage the data and control the aperture of our attention. With practice, SCAN helps us see past the uninvited information to the hidden insights and options unavailable to the overwhelmed mind.