The R2O triangle of triangles

There have been many attempts to develop a single framework for streamlining R2O transition activities that is capable of handling the wide range of projects. While some have short-lived success, eventually these frameworks encounter difficulty meeting the diverse time, funding, maturity, scale, and scope characteristics of R2O projects. One idea to better represent the status of R2O projects has been to replicate the Technology Readiness Levels (TRLs) that the National Aeronautics and Space Administration (NASA) uses to monitor the maturity of certain technologies. While TRLs and analogous concepts have their place in the engineering community because of their relationship to physical, mission-relative deliverables, such readiness levels and other representations of progress are challenging to develop for a fluid R2O environment.

There are a few major reasons for this challenge. First, when R2O activities commence, there is no guarantee that they will produce a transitioned product in the end. The nature of that end product may evolve substantially over the course of the R2O cycle. Second, R2O activities are convened for an exceptionally wide range of scientific concepts and operational needs. A R2O model that works for the numerical modeling community will differ from one that is successfully applied to satellite missions. Testing and training (not to be confused) within the R2O cycle will have different objectives, and as such, the process and effort must be distinct. Third, the gap between the science and the need may also vary. In some cases, the R2O cycle must resolve whether the proposed science solution is tightly matched to the operational need. In other cases, it is very clear that it is and this can accelerate implementations and demonstrations. Lastly, interim success in R2O activities that are inherently cyclic is difficult to quantify. The concept of operational readiness is going to vary amongst stakeholders, and R2O deliverables are not necessarily easy to isolate in terms of their reach. There are likely other nuanced reasons as well based on the organizations and technologies at play (e.g., budgets and leadership priorities).

For this reason, the simplest representation of R2O has four primary portions: the research idea, the operational need, collaboration, and organizational support. These four portions can be arranged into a triangle to represent their relative importance and interdependency. The research idea and operational need are at the base of the triangle because they are necessary for R2O by definition. Without one or the other, the R2O effort will not survive.

The R2O triangle of triangles. Figure developed by Jordan Gerth.
The R2O triangle of triangles shows the relative importance and interdependency between the research idea, the operational need, collaboration, and organizational support.

The base of the triangle represents the perfect match: a well-developed research idea matches a strong operational need with no retooling required. Theoretically, the amount of collaboration in such a scenario would be minimal. Organizational support is necessary to ensure the institutional and technological capacity exists for the concept to reach the targeted practitioners.

Where the state of the science is further from the operational need, collaboration will be necessary to incite innovation. Resting atop collaboration is organizational support. Organizational support is necessary to further the abstract objective of R2O. If there is no such support, the R2O effort is unlikely to scale.

A careful observer will notice that without collaboration, it is possible for some semblance of the triangle to remain. However, substituting organizational support for collaboration will result in instability, especially when a research idea and operational need are not closely matched. It should also serve as an indicator that people and relationships, or a culture, are necessary to achieve R2O successes. A significant risk exists when support is provided to an activity that has not been substantially corroborated between research and operations. Generally this risk can be quantified based on the amount of funds provided to research and development and the capacity built to prepare operations.

Ideally, collaboration should eventually bleed into organizational support for mature and scalable R2O projects. Such coherence not only shows general awareness and appreciation for R2O at all levels of an organization or community, but also confirms alignment between leadership priorities, the challenges of practitioners, and the capabilities of research.

Maybe we should write R2O as RΔO from now on…

Jordan Gerth

Jordan Gerth

is a research meteorologist with a decade of R2O experience, interacting with academia, the federal government, and the private sector on weather satellite and software projects.
Jordan Gerth

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