Finding the Peak When the Mountain Moves
I recently attended a Liberating Structures (LS) workshop in Seattle convened by long-time Plexus partner Keith McCandless. Most of you are likely pretty familiar with LS- methods that can be used with almost any size group and that help create conditions to unleash innovation and new actions. As I describe LS to friends and colleagues who aren’t familiar with them, I’m often asked something like "When would I use these methods? Are there certain types of challenges for which LS are particularly useful?” I’d like to provide my perspective on this by reflecting on other aspects of my few days in Seattle.
Summer in Seattle can be beautiful, a real contrast to the grey and damp climate that dominates the weather there most of the year. The clear blue summer skies allow one to take in the natural beauty that surrounds Seattle. Easily visible from the air as we landed and immediately pointed out to the southeast by the driver taking my wife Marcie and me to the car rental facility was the snow-capped peak of Mt. Rainier. This, with a peak of 14,410 feet above sea level, is the most topographically prominent mountain in the contiguous United States. Locals sometimes just refer to Mt. Rainier as "the mountain.” Looking away from Mt. Rainier to the east and northeast are the rest of the Cascade mountains, a huge range of volcanic mountains that rise and fall for hundreds of miles with hundreds of mountains of varying sizes. Within Seattle proper the topography is marked by significant elevation changes as well. The low points at the waterfront are at sea level. Start walking east towards Capitol Hill and you’ll rise and fall steadily, ultimately climbing more than 400 feet in elevation within a mile or two from the coast.
Coming back to challenges and the uses of LS, some challenges are like Mt. Rainier- the top of the mountain representing the highest point, the clear best solution. As you scale the mountain you can fairly easily tell if you’re closer to the peak than where you were- and for similarly identifiable problems you can also, through experimentation, clearly tell when you’re getting closer to your goal, the one optimal solution. If you’re the first one, you’ll need to create a pathway to the top. If others have gone before, just follow that pathway and you’ll get to the peak. Many industrial, factory floor challenges are Mt. Rainier-like challenges- the best machine for the task at hand. Within healthcare there are some Mt. Rainier challenges too. If a patient presents to the emergency department with severe chest pain and is found to be having a major heart attack, the team should try to get that blood vessel that has become blocked open as soon as possible, in order to prevent heart muscle from being irreparably damaged. The faster you open the vessel, the better.
Other challenges are more like hiking through other parts of the Cascades. You may be able to tell when you’re at the top of a peak, though you may have a harder time telling if that peak is higher than another one somewhere else in the range. So local optimums are easy to find, you have to go down first to try and go even higher, and that next peak you climb may not turn out to be higher than the one you left. Given enough exploration, however, you’ll eventually be able to figure out the highest point in the whole area. Experts, like guides, and other help, like technology, can help you get to that highest point. The challenges that are like this are also typically benefited by bringing in expertise and doing lots of designing, planning and experimentation. Staying with the heart attack patient example, howdo you get that patient to the catheterization laboratory to open the vessel in as short a time as possible? That’s like climbing up and down the Cascades, trying to find a higher, better point.
Then imagine a future scenario like this. It’s 1,000 years from now in Seattle. One or more of those volcanic Cascades that nearly abut the city erupts. This triggers a chain reaction and an earthquake of significant proportions. One or more of the hills that populate the city’s landscape has the bottom drop out of it, losing hundreds of feet of elevation. Several days of heavy rains leave areas that were previously hilltops now submerged under inches of water. This "dancing landscape” is related to interdependencies within the system and is associated with surprising changes in conditions. What was once the high point is now something quite different. Things that you were sure were true now are something different. For challenges like this, the quest to get to some higher, "better” point needs to be perpetual, with a focus on constant learning as circumstances evolve and situations change. How do we reduce the risk of our communities needing emergency heart attack services? How do we effectively help patients who have survived heart attacks to modify their lifestyles to reduce future risk? These are examples of dancing landscape challenges.
When your landscape dances you need to dance too. And not just the foxtrot- you may need to cha-cha, or boogie, or twist, or waltz, depending on the situation. Dancing landscape challenges require innovation, diverse perspectives, and the sort of information and feedback that can best be accomplished through connectivity and relationships. These are the results of the use of LS- people think differently, creativity is unleashed, and new relationships are formed that persist and help the system to better deal with its challenges. LS help people to become much better dancers than they ever thought they could be.
I think in healthcare improvement efforts, too many issues are viewed as Mount Rainier or Cascades challenges, and we search for the ultimate highest point, as though there is always some best practice that will be the optimal solution for everyone. That’s fine for some problems- not all landscapes dance. Sometimes implementing the checklist is the way to go. How can we augment those approaches by helping organizations recognize the cues that it’s time to dance --to hear the beat, feel the rhythm emerging, and to see the swirling patterns of color and movement that means we should get up, get together, and, by using methods like LS, join the dance?