After Action Reviews (AAR)

LEARNING OVER TIME

Reflection gives teams a chance to examine why events differed from their expectations. If they move straight to problem solving or simply try harder, they may miss what the surprise reveals about their assumptions.

“This more prepared mental state is really where a lot of the longer-term payoff is,” says Galloway, describing her work with Intel management teams. “Part of our disagree-and-commit discipline is establishing a monitoring process to track the consequences of decisions.” This involves an explicit time frame after which participants in Galloway’s groups come back to key questions and assess whether “things are working like we thought or we’re learning something we weren’t expecting. Either way, those who disagree know they are providing useful perspectives that shape our ongoing learning.

“For example, we had a scenario planning process in ‘99, with the management team of one of our fabs. We looked at possible futures that were far from people’s normal mindset, like a major collapse in the tech market or the effects of a disruptive technology. We forced ourselves to think through how we would respond. This occurred at the height of the bull market. We couldn’t build capacity fast enough. But we hadn’t even gotten all our scenario stories written and circulated to everyone when the tech market bust suddenly started.” Because they had thought through this possibility, the Intel management team had a big advantage, Galloway says, and they were “able to take corrective actions quickly. These included some things that were difficult to do, like offering redeployment, moving resources to areas where they were more needed, and changing our fab strategies. We responded quickly and with a clear picture of our new direction because we had reflected on potential actions.

“We take this reflective work very seriously,” she adds. “There is no point in doing it if you do not take the time and resources to do it well. Sometimes it takes a year before people see the value in some of our dialogues.”

Galloway has learned to keep good records, using graphic facilitation and more conventional types of recording—“anything that helps people see that their thoughts were heard. I’ve had people ask ‘Can I look at those meeting reports?’ two years later because now these issues are coming up again and they remember some important ideas. It all comes down to helping people at the time they really need help. You have to be patient.”

And you have to make reflection part of the way work is done. One simple method that has found broad application within the SoL network is “After Action Reviews,” a tool developed by the U.S. Army. It can be used after an elaborate two-day war game simulation or after a one-hour meeting. In its simplest form, an AAR consists of three questions:

• What happened?
• What did we expect?
• What can we learn from the gap?

Having simple protocols like AARs for connecting action and reflection matters, but having a supportive management environment is essential. In the Army, AARs took root as part of a long-term journey, as one general put it, “from a culture of reports to a culture of review: we were always good at writing reports for our superiors but not necessarily at learning from our experience.” The same management commitment is needed in companies.

AFTER ACTION REVIEWS 6

Within minutes after the lights went out on August 14, 2003, everyone at DTE Energy, the parent of Detroit Edison, knew that something big was happening. Within those few moments, the power grid had failed for fifty million Americans and Canadians. But, for DTE, the blackout of 2003 was not just a freak occurrence. Rather, it was an extreme case of the emergency response which defines the essence of their business, and from which they would learn how to improve. Within 24 hours of the blackout, a series of After Action Reviews were called to assess how well DTE managed excess capacity to restore service, deployed personnel, communicated with the public, and met basic infrastructure needs. Such reviews have become standard practice during emergency responses at DTE—even as they work to restore power as quickly as possible, people are thinking about how they are responding and how they could do it better in the future. Even during the crisis, CEO Tony Earley said, “I must have seen at least five, maybe ten people, holding pads with the heading AAR Observations’ on them. Right in the middle of the crisis, without any prompting. People just assumed there was going to be an AAR. It was great to see.”

The integration of AARs into the culture took several years and was guided by four specific strategies:

1. Leadership by request and example. Help managers at all levels appreciate the importance of deep learning and ongoing discipline versus one-time events and quick fixes, and help them develop a learning practice that reflects their own priorities and challenges.
2. Events seen as learning opportunities. Develop the organization’s ability, at senior, middle, and grassroots levels, to recognize day-to-day events, as well as major crises, as opportunities to learn, and help teams link past and present so that lessons from the past can be applied to improving current results.
3. Grassroots exposure to AARs. Introduce teams to the tool by demonstrating its ability to provide a safe environment for learning their own priorities and challenges, but don’t mandate its use, and don’t insist on perfection.
4. A cadre of trained facilitators. Develop specialists who understand both how to facilitate AARs and how to help guide teams toward “high-yield” applications (tangible return for the investment).

The intention of these four strategies is local ownership for learning that matters. Most departments and teams know what practices they need to improve. The simple question, “If you could improve performance in one area that would make a significant difference for the enterprise, what would that be?” points them toward their most natural local learning practice. The AAR approach potentially makes the work team the first, best customer for its own learning, in sharp contrast to the “capture-and-disseminate” model of most knowledge-management practices.