Forecasting Demand for U.S. Ground Forces

Assessing Future Trends in Armed Conflict and U.S. Military Interventions

by Matthew Lane, Bryan Frederick, Jennifer Kavanagh, Stephen Watts, Nathan Chandler, Meagan L. Smith

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To defend against potential threats, the U.S. Army devotes significant resources to strategic and operational planning. This planning is an exercise in risk management across the wide array of potential threats facing the United States. Military planners need tools that leverage emergent trends in the global geostrategic environment to forecast future contingencies to preemptively build, shape, and prepare U.S. forces for the kinds of missions they are most likely to encounter in the future and for the contingencies that pose the greatest strategic risk to the United States.

This report provides empirically grounded assessments of potential future demands for U.S. ground forces. It does so by presenting a dynamic forecasting model that projects future U.S. ground interventions in a range of scenarios through the year 2040. The model the authors have developed incorporates annual projections of opportunities for U.S. intervention—including armed conflicts and their aftermath—and U.S. ground interventions themselves for each year in the 2017–2040 time frame. The authors present three main types of projections: trends in the future operating environment, including the incidence of interstate wars and intrastate conflicts; future U.S. ground interventions, including those involving deterrence, combat, and stabilization activities; and the anticipated average force requirements for those interventions. This analysis identifies key factors that can serve as early warning indicators of future conflicts and provides an improved empirical basis for estimating the frequency, magnitude, duration, and overlap of future contingencies.

Key Findings

This report describes a model that can be used to project trends in armed conflict and demands for U.S. ground forces through 2040 under different scenarios. In a baseline, or "no surprises" future:

The risk of interstate war appears likely to increase, although it is likely to remain low by historical standards.

The total demand for U.S. ground interventions is expected to decline slightly or remain the same, but this trend is accompanied by a projected increase in the forces required to meet the demands of these interventions.

There is a substantial likelihood that there will be demand for a sizable U.S. stability operation between now and 2040.

The Middle East, Eurasia, and East/Southeast Asia are the most likely locations for future demand for U.S. ground interventions, although locations vary across combat, deterrence, and stabilization missions.

The report also describes the results of four alternative scenarios that differ dramatically from the anticipated baseline:

The largest increases in demands for U.S. ground forces, including combat forces, were seen in the scenarios that model a Global Depression and a substantially more revisionist China.

In the scenario that models a global pandemic, based on a reprise of the 1918–1920 Spanish Flu, the demand for U.S. ground forces increases only modestly from the baseline scenario, with increased demand strongest for deterrence and stability missions.

In the scenario that models an isolationist United States, U.S. ground forces participate less in deterrence missions, but this reduction is offset by a forecasted increase in demand from combat missions.

Table of Contents

Chapter One

Introduction

Chapter Two

Historical Trends in Armed Conflict and U.S. Ground Interventions

Chapter Three

Methodology for Forecasting Future Armed Conflicts and U.S. Ground Interventions

Chapter Four

Future Demand for U.S. Ground Forces: Forecasts of Armed Conflicts and U.S. Military Interventions

Chapter Five

Conclusions and Implications for U.S. Army Force Planning

Appendix A

Historical Force Requirements Coding Methodology and Notes

Appendix B

Forecasting Model Assumptions, Components, and Processes

Appendix C

Results of Alternative Future Scenario Forecasting Models

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