Fortunately, this kind of institutional-learning process has been long been studied and improved, and is often expressed as a four-part cycle. A widely used version, made famous by John Boyd of the Air Force, is the "OODA" loop: observe, orient, decide and act. Those who complete OODA cycles more quickly and effectively get better than those who don't. Boyd, a military strategist, applied OODA learning to combat operations - most notably in the 1991 Gulf War -- where it has often meant the difference between life and death.
Today, with the increasingly powerful and pervasive data-processing and connectivity at our disposal, the OODA loop is more useful than ever. Here's how it works and how it is being put to new uses:
Observe: Gather the feedback needed to learn. Feedback is data on the results of action. Roughly half of all the data assembled since the beginning of time has been collected in the past two years, with more than 90 percent of it in digital form. Social networking has created an explosion of data and other communications, resulting in applications such as "Where's My Bus?" (which shows you where the bus you're waiting for is and when it will arrive at your stop, based on GPS signals). Much more feedback is available, but we've got to look for it and find ways to capture it.
Orient: Use analysis and expertise to assess relationships between actions and results. Numbers were originally created to measure and count acres and animals for collecting taxes. Now we have "big data," opening far more problems to far-deeper analysis. Google, for example, has found that predicting the path of a flu epidemic is made quicker and more accurate by analyzing billions of Internet search questions rather than by waiting on thousands of sick people to show up at hospitals. Also important is using expertise that couldn't be reached before, as with remote X-ray readings, online student tutoring and other support from a distance. Orientation can benefit from analysis and access to expertise, but we've got to get organized to use them.
Decide: Use engagement and algorithms to improve decision-making. In reality, digital communication and tools have been better for clarifying options than for making choices. But that is changing. Stakeholder participation in decisions can be improved by providing deeper engagement. The Peace Corps, for example, found that policy decisions could be made more confidently if it moved away from relying solely on D.C. staff and instead included comments by field officers that were then discussed in conference calls. Eventually the process evolved -- and this was a dramatic improvement -- to using video calls to make final decisions. For other institutional settings and decisions, and in many more cases than before, choices can now be made by algorithms. Algorithm uses have expanded from simply restocking supermarket shelves by formula, rather than by intuition, to the development of cars that can drive themselves safely through traffic. Decisions can benefit from better engagement and analysis, but we've got to get organized to use them.
Act: Coordinate implementation across more people and specialties. We need data standardization and collaboration, as with the customs operations that now share data so that most travelers can quickly and efficiently cross national borders while suspicious cases are identified and detained for closer inspection. We also need the benefits of data sharing and collaboration to "connect the dots" for counterterrorism and law enforcement, while recognizing the need to balance the potential benefits against the negatives that may result from lost privacy and other unintended consequences. If we can assemble and use the right information, we can manage larger and more complex systems far more effectively.
In today's digital world, data and analysis have the potential to transform the essential process of learning, both for institutions and for the people who manage them. Could your organization use an approach like the OODA loop more effectively? Could you?
