The Role of PMESII Modeling in a Continuous Cycle of Anticipation and Action

TL;DR

This paper discusses how PMESII models, despite their uncertainties, can support a continuous cycle of planning and learning in international interventions by combining computational estimates with human judgment.

Contribution

It introduces a methodology for integrating PMESII modeling tools into ongoing decision cycles, emphasizing their role in aiding human analysis despite inherent uncertainties.

Findings

Computational estimates assist in planning and decision-making.

A continuous cycle of anticipation and action improves intervention strategies.

PMESII tools foster learning even with imperfect predictions.

Abstract

The inevitable incompleteness of any collection of PMESII models, along with poorly understood methods for combining heterogeneous models, leads to major uncertainty regarding the reliability of computational tools. This uncertainty is further exacerbated by difficulties in validation of such tools. They should only be used as aids to human analysis and decision-making. A practitioner must wonder: how can we accommodate the uncertainty of a tool's results by applying human judgment appropriately? In this paper, we describe two examples where planners and analysts used (or could have used) computational tools to obtain estimates of effects of various actions under consideration. Then they considered these computational estimates to draw their own conclusions regarding the effects that would likely emerge from proposed actions taken by the international mission. The key idea, in both of our examples, is a continuous cycle of anticipations and actions; in each cycle computational estimates of effects help intervention managers determine appropriate actions, and then assessments of real-world outcomes guide the next increment of computational estimates. With a proper methodology, PMESII modeling tools can offer valuable insights and encourage learning, even if they will never produce fully accurate estimates useable in a customary, strictly predictive manner.