What stops workers from sharing or contributing their experiences and knowledge when colleagues are problem-solving?
In “‘Figure it Out!’—A Practical Framework for Workflow Learning” and “Conversations on Real-Work Issues Ignite Workflow Learning,” I emphasized that workers fix and improve their work and solve problems—in the workflow. In this process, they participate in conversations that lead to productive results. However, their confidence to openly contribute in conversations is often stymied by norms and practices that define who is an expert. In this article, I propose that in workflow learning, every worker has interactional expertise—and should be recognized as an expert based on their practical experiences relating to work issues.
Wait. What can Peter possibly know?
John Seely Brown, an organizational learning guru, shared an interesting story. To paraphrase:
We had a serious problem with a piece of our printing equipment. We called all the experts, engineers, designers, and production people to figure out what was causing the problem. After hours of discussions we could not find an explanation. This was bewildering to us.
One evening, I was in the office late and was checking the equipment. Peter, a maintenance person who collects trash and cleans, was working. Peter asked me, “What’s up with this equipment?” I explained the problem and that we could not find a solution. Then Peter asked me “Have your tried doing these steps when refilling the cartridge and running a test?”
“Really?” I exclaimed. I tried it, and it worked!
Sometimes, the solution is right under our nose. All the traditional experts couldn’t figure this out, but Peter, who was not an expert, had the answer all along. In this story, Peter is an “interactional expert,” offering practical expertise. There are many “Peters” in our workplaces, it we are willing to acknowledge and listen to them.
Moving from SME to you and me
De-emphasizing the role of the SME (subject matter expert) and nurturing a culture of “interactional experts” (practical expertise) among workers shifts the attention from the SME as the sole source of “correct” answers. The new model is that everyone’s experiences can be utilized to extract nuggets of practical expertise.
Knowledge and solutions can also come from the workers, not just SMEs and other experts. This new model improves the self-confidence of workers. Their contributions have some value in the conversations.
In workflow learning, experience sharing is where we gain valuable knowledge from interactional experts. With this shift in our learning and application model, we see the roles of the SMEs and L&D morphing into coaches, mentors, and curators of content to support workers in the Workflow Diagnostic Process. (See Figure 1.)
Figure 1: The Workflow Diagnostic Process is a continuous cycle of diagnosing problems, finding and testing solutions, and gathering feedback on those solutions
Building trust: A context of limitations
For workflow learning to be truly effective, we need to give the workers the ability to share practical experiences. A strong learning culture sets up the dynamics for the answers and solutions to be tested and trusted.
We have a methodology for testing and trusting answers and solutions. Workers can be trusted to find the answers when they present their contributions with the accompanying constraints. These are:
- The worker’s goal is finding an answer to fix, solve, or improve something.
- Their answers, whatever the source, will always reside within a context of limitations, blind spots, and unknowns. These unknowns make answers not fully reliable without the statements of the context and/or limits.
- Stating the unknowns and limits makes an answer reliable because it has the built-in aspects that must be further investigated or accepted as conditions and therefore must be considered in using or applying the answer.
An example might sound like this:
“The answer is the procedure I found in YouTube. This is what the procedure says: Step 1, 2, 3, etc.”
An alternative example might sound like this:
“The answer is the procedure I found in YouTube. However, after checking other sources there are some constraints: It works in this condition only. The people who push this are vendors. It was not clear that it applies to our problem. It could apply to our problem if we include this modification.”
The second example has greater credibility because it has the appropriate context of limitations. It demonstrates critical thinking and analysis. It therefore stands up as being a more reliable answer given the constraints. Reliability leads to trust among co-workers.
This is how experience sharing and interactional expertise grow and thrive within workflow learning. Without the appropriate contextualization, answers remain suspect.
Surface-source and deep-source knowledge
With the first example above, there is only superficial or “surface-source” information. No critical analysis has taken place yet. Surface-source information is general; it provides an overview and focuses on information that is easily and quickly available.
With the second example, though, the context of limitations and analysis of those limitations within the context of the problem they are trying to solve moves the workers toward a deeper understanding.
Good interactional expertise contributions include more than surface-source knowledge; they also include “deep-source” knowledge. The conversations are more robust. Deep-source knowledge might include these features:
- Opposing views: Presents contrasting and divergent points, mentions limitations and strengths
- Reliability: Uses facts, research, history, stories, results, and impacts on outcomes
- Reputation: Authority, cites or comes from an expert source (in-house or external)
- Follow-ups: Makes suggestions for further study, review, research, testing
This doesn’t always need to take place, however. It is dependent on the subject being discussed and the workers’ interest level in the conversation.
Bring interactional expertise into the workflow
Learning in the workflow relies on trusting coworkers to share practical experiences. Knowledge and solutions not only come from SMEs, but also from the people doing the work—the interactional experts. We gain valuable knowledge from listening to these practical experts—under the right conditions. Answers and solutions from workers require us to consider the context of limitations, to verify the information, and to conduct the proper dialogue to ensure we adopt trusted solutions.
Learn how to bring interactional expertise into the workflow at your organization. Register today for “Boots on the Ground—Implementing Workflow Learning,” a daylong workshop presented by Ray Jimenez, PhD. This pre-conference workshop takes place October 22, ahead of DevLearn 2019 Conference & Expo, October 23–25 in Las Vegas.
Collins, Harry, and Robert Evans. Rethinking Expertise. Chicago: University of Chicago Press, 2009.
Nichols, Tom. The Death of Expertise: The Campaign Against Established Knowledge and Why it Matters. Oxford University Press, 2017.
Thomas, Douglas, and John Seely Brown. A New Culture of Learning: Cultivating the Imagination for a World of Constant Change. CreateSpace Independent Publishing Platform, 2011.
Useem, Jerry. “At Work, Expertise Is Falling Out of Favor.” The Atlantic. July 2019.