How Do You Make Decisions Under Uncertainty? The Key Is Asking The Right Questions And Modeling.

Dr. William Furness is regional president of Sound Physicians in Boston, MA and a member of MIT EMBA class of 2018.

Most MBA programs teach the business fundamentals needed for success. This is certainly accurate in MIT’s Executive MBA Program, where students are immersed in more economic, finance, and analytical frameworks than one brain can handle. However, what truly sets this program apart is its focus on making decisions under uncertainty.

If you've been a leader for any amount of time, you know these critical decisions are often made under time constraints that can leave your head spinning. We've all had days as leaders where we use our gut instinct to make a critical strategic decision and later wonder if our intuition was enough. Will our approach come crashing down like a house of cards?

In this program, I discovered that one of the keys to these types of decisions is asking the right question. We learn this approach – and apply it through action learning – in just about every class:
–          What problem am I really solving for? (Organizations Lab)
–          How do I make a decision if the economic implications and data aren’t clear or available? (Data, Models and Decisions)
–          How do I predict what the ripple effect of my decisions will be? How do I plan for these issues ahead of time? (System Dynamics)
–          These decisions are being made with people who operate in a culture and with their own individual values and interests. How do I plan for that? (Organizational Processes)

As the regional president for a national physician practice, I oversee 60 hospitals and the decisions I make have real implications for patients. I recently tackled a problem, that two years ago, might have left me searching in the dark for direction. In addition to financial and strategic implications, my decision could also impact clinical quality. Fortunately, I could apply all my classes to make this decision.

What is the real problem?
My first step was to build an A3, which is a model used to better define a problem. After all, if you don’t understand what the problem really is, you may spend your time addressing the wrong issue – which will likely lead to the wrong decision.

Create a decision tree
After I understood the problem more clearly, I was able to map it out using a decision tree model and assign probabilities for each possible outcome. This allowed me to assign an estimated monetary value for each decision path.

Identify how variables are related
Then, I picked some key variables and analyzed their implications with a system dynamics model. Our decisions as leaders are not made done in a static vacuum; changing one variable can have effects on other aspects of a system. This model allowed me to identify a negative feedback loop that I could plan for ahead of time. It mitigated surprise obstacles.

Ask the right questions
Most importantly, the models ensured that I was asking the right questions for each path we might pursue. “How high does X need to be before we made the wrong decision?  Have we considered each sub-problem? What is the context we are making this decision in?” I reflected back on all my classes, as I worked to identify the right questions.

By using these approaches, I was able to gain immediate traction and buy-in among senior leaders. My final recommendation was unanimously approved because the data and models showed it was the right decision.

My organization’s problem was like many others in the real world that are complicated and involve people with different perspectives. However, by using these data-driven models and processes, leaders can create clarity for teams to move forward and execute quickly on their decisions.

How do you identify and solve complex problems in your organization?