The rack and stack of Russian and Ukrainian forces prior to Vladimir Putin’s February 2022 invasion of Ukraine left many analysts, myself included, convinced that by this time last year Putin and pals would be celebrating under a white, blue, and red flag in Kyiv’s Independence Square. This isn’t the first time that a material-based understanding of national power has failed.
Many military professionals and analysts of the nineteenth and twentieth centuries attempted to quantify the battlefield and also largely failed. From Lanchester’s laws of relative military force strength to Dupuy’s Operational Lethality Indices to the US Army’s weapon effectiveness index / weighted unit value metric and beyond, many creative attempts to quantify military power have successively been championed and abandoned.
Now, the pendulum appears to have swung in the opposite direction, with analysts heeding the “alchemy of combat effectiveness” and dismissing comparisons of equipment and personnel counts as “bean counting.” Today’s critics of material measures of power have a point—if the goal is to measure combat outcomes. As military analysts Michael Kofman and Rob Lee often remind us, combat is contingent upon a myriad factors, some of which involve pure chance, even luck.
But material measures continue to offer an important guide to measuring power at the national level. In a more limited sense, they continue to be informative on the battlefield, provided such measures are assessed within broader situational contexts. Put simply, materials—and mass—still matter.
Mass in the Donbas
Although a “bean counting” of Ukrainian and Russian military equipment on hand at the time of Russia’s full-scale invasion would have shown a stark contrast that heavily favored the Russians, military aid that has been provided to Ukraine since has gone a long way in narrowing the material capabilities gap. Where masses of material capabilities have failed in terms of predictive capacity for the future, they hold immense explanatory capacity for the present. In Ukraine, Russia’s material advantages should have produced battlefield outcomes heavily in its favor, and the fact that they did not shows that a range of other factors that degraded Russian military effectiveness needed to be accounted for. But by flipping that around, we can see that all of those other factors were also mitigated by Russia’s material advantages.
What other force could have executed its campaign as miserably as the Russians in the early days of their full-scale invasion and still be in the fight today? Indeed, the Russian military arguably still has a chance of winning the conflict, though we can debate what winning means in this context given Russia’s undeniable geopolitical losses. Setting the question of combat performance scorecards aside, what can better explain the periodic operational pauses in the war so far than shortages of personnel, ammunition, and equipment?
To be sure, quantitative measures of complex phenomena can fail us. As sociologist William Bruce Cameron cautioned, “Not everything that can be counted counts, and not everything that counts can be counted.” By focusing only on the easily measurable, we can become like the drunk searching for his keys under the lamppost because that is where the light is.
Quantifauxcation—or the “practice of assigning a meaningless number, then concluding that because the result is quantitative, it must mean something,” as defined by statistician Philip B. Stark—is another potential pitfall. The remainder of Stark’s quote, that “if the number has six digits of precision, they all matter,” describes the distinct but related problem of false precision.
Unfortunately, assessments that are fully divorced from the quantitative realities of our world fail too. Deeply ingrained cognitive biases lead us to be drawn in by vivid, tidy stories that communicate a clarity, consistency, and certainty—tending, as intelligence analyst Richards Heuer observed, to “disregard abstract or statistical information that may have greater evidential value.” In contrast, the “strict grammar” of mathematics, as political scientist John V. Gillespie wrote, allows for broad-based and objective comparison of alternatives and, in our case, national power.
The solutions to the problems of quantification include making an earnest attempt to measure previously unmeasured factors, and when numbers are assigned, to avoid assigning meaningless numbers. For example, the US intelligence community regularly uses the terminology of probability, including phrases such as “likely” and “probably,” even though their assessments are rarely if ever based on probabilistic statistical models. The phrases are meaningful, however, because analysts use these words with reference to a common scale of their best guess of a probability, where for example “likely” and “probably” communicate a 55–80 percent chance.
Of course, one cannot know with exactitude whether 55–80 percent is the correct likelihood, but it is far better than a shoulder shrug and disclaimer that anything is possible. And the intentionally broad range communicates that it is an inherently imprecise estimate.
Heuristics, Not Predictors
In a recent effort to quantify military power, political scientist Mark Souva created the material military power measure, which combines data across militaries’ land, air, sea, and nuclear capabilities. While far from perfect—as any coarse-grained measure will fail to capture important distinctions in specific contexts—Souva’s measure accurately predicts the outcome of 80 percent of the thirty-six wars between 1865 and 2007 cataloged by the Correlates of War project.
Across a broader set of instruments of national power, the Global Power Index—a composite measure of countries’ demographic, diplomatic, economic, military, and technological capabilities—has successfully tracked and forecasted the rise of the Global South. Its account of the widening and then narrowing gap in the distribution of power in the international system offers a measurement of the United States’ unipolar moment. In the line graph presented here in Figure 6, that period was roughly 1991 through 2009—an era bookended by the collapse of the Soviet Union and the Great Recession.
The Formal Bilateral Influence Capacity Index has successfully tracked geopolitical influence in nations’ bilateral relations as well as among networks of international interactions. For example, in a forthcoming report from me and my colleagues with the Stimson Center, we note that the Middle East appears to have permanently left America’s sphere of influence in favor of its own or a more China-oriented sphere. Beijing’s latest diplomatic coup, reestablishing Saudi and Iranian ties with one another, and Saudi Arabia’s deepening ties with the Chinese-led Shanghai Cooperation Organization are but two early indicators of this development. Long-term structural transitions—including shifts in global oil demand, with US demand peaking and Chinese demand forecasted to continue to grow substantially—will continue to push trends in this direction.
An index that will be more familiar to readers, gross domestic product (GDP), also offers a useful if imperfect general measurement of national power. As economist Paul Krugman illustrated earlier this year with a simple column chart, the vast disparity in GDPs for the United States and European Union relative to Russia goes a long way in explaining why Western-backed Ukraine has been so successful in resisting Russian domination (a fact that does not diminish Ukraine’s extraordinary and unexpectedly successful resistance). And, as political scientist Jacek Kugler and others note, GDP is particularly useful for “longer-term assessments because of [its] simplicity, availability, and forecasting potential.”
These measures are heuristics, not predictors. In the theoretical framework of political scientist Alexander Wendt, they speak to the “rump materialism” underlying international interactions. While the immaterial is important, the distribution of material capabilities, their sophistication and diversification, and their positions in the world (i.e., geography) conspire to constrain outcomes—independent from, though often in connection with, ideas, norms, and other immaterial factors.
To some extent, measuring power means reifying a fundamentally relational concept. Beyond the difficult-to-measure features of a fighting force—intangibles such as the will to fight—power is an idea that emerges from “processes of social transactions.” In other words, in the language of quantitative social science, it is not a variable. To the extent that we can think of it as something concrete, it manifests in the connections between variables.
In plain language, power is not something that can be measured directly. It can only be measured by proxy. All measures of power, then, are abstractions that are necessarily divorced from some, though certainly not all, realities.
For attempts to predict the outcome of battles—where contextual factors such as morale and operational art dominate—material measures of power have proven too abstract, too imprecise. In predicting overall war outcomes, their predictive abilities are imperfect, though considerably better. (The 80 percent accurate prediction of war outcomes is far better than a coin flip.)
However, material measures of power are most useful for providing a general understanding of the grand strategic situation in which countries and their national leaders find themselves. A country’s global share of GDP is far from a perfect predictor of any outcome, but it provides a fairly accurate sense of that country’s power status in the international system. Composite measures of economic, political, and security-based capabilities will miss much, but they also have proven capable of tracking our transition from a bipolar to a unipolar to a multipolar world order.
Context, of course, remains important. So too do materials and mass, even if these measures are inadequate for drawing policy-relevant conclusions when considered in isolation. Rather than choosing one over the other, material measures of power offer objective starting points for scientific analyses—leaving room for some alchemy thereafter.
Collin Meisel is the associate director of geopolitical analysis at the University of Denver’s Frederick S. Pardee Center for International Futures at the Josef Korbel School of International Studies. He is also a geopolitics and modeling expert at The Hague Centre for Strategic Studies, a Netherlands-based security and defense think tank.
The views expressed are those of the author and do not reflect the official position of the United States Military Academy, Department of the Army, or Department of Defense.
Image credit: Petro Poroshenko