Why Good Weather Isn’t Good Enough: The O2D (Operations to Decisions) Divide

Murphy (1993) noted that weather forecasts only realize value when used to assist in making good decisions. Yet nearly 25 years later, while there are many real-world decision support systems developed for specific weather-impacted scenarios, use of weather forecast information in objectively optimized decision making remains far from widespread. Rather, most routine weather-impacted decisions are made using a subjective mix of experience and intuition based on a limited set of available information. How much fuel should be put on an aircraft facing uncertain weather at the destination? When should an evacuation order be issued for city in the face of a tropical cyclone threat? What route should one take to work given the expected snow? Such choices are routinely made without optimized decision guidance, despite the fact that such guidance is increasingly feasible.

We discuss three general points about the state of weather-based decision making in our enterprise today:

1. That weather-based decisions are ubiquitous and our enterprise’s general focus on improved outcomes during high-impact weather events is realizing only a fraction of the potential value of weather forecasts for all of society’s weather-based decisions.
2. That decision support or assistance is insufficient for optimized decision making and that our enterprise must focus more on decision making in order to realize the full value of our science. Further, weather-based decision making is complex and multidisciplinary, and our enterprise has generally thought of the decision-making process as “someone else’s problem”. We often think our responsibility only to provide good weather information. However, our enterprise has the most at stake in realizing it’s value to society and therefore must take on a larger role in creating optimized decisions.
3. That as the skill of weather forecasts continues to improve, so do weather-impacted decisions. However, our foundational forecast data is also getting more complex (e.g., via the emergence of probability forecast information) such that decision makers often are not able to fully digest or use the all available information. As a result, the gap between the potential value in our forecasts and the realized value (the “operations to decisions” divide) implies that our science is leaving an increasing portion of its potential value on the table.

In order to make a material reduction in the O2D divide, we believe three changes in our enterprise are needed. First, we must embrace decision guidance and made-decisions as our end product and not just be content with weather content and decision support. Second, we should broaden our decision services focii beyond high-impact weather but across for all types of weather’s impacts on society. Lastly, we need to develop more generic weather-based decision making infrastructures and technologies rather than bespoke capabilities for specific problems. Material improvements in these three aspects will materially increase the value our enterprise delivers to society.