Can Industry Predict the Size of an Industrial Building?

What explains these differences? The data do not identify the specific factors that determine building size. One possible explanation is that companies within the same industry often operate under very different business models. While some require only warehousing or distribution space, others integrate manufacturing, assembly, automation, or large-scale logistics operations.

So far, the analysis has shown how building sizes are distributed across industries. But is this a stable pattern or simply a snapshot in time? To answer that question, SiiLA compared occupancy patterns observed in the second quarter of 2020 with those of the second quarter of 2026. The results show that although eight industries increased their typical occupied building size—by between 6.2% and 30.1%—two remained virtually unchanged and four recorded declines ranging from 3.5% to 20.5%, overall occupancy patterns by industry remained stable³.

Likewise, the data indicate that these changes were not concentrated within a single group of industries. Among those recording the largest increases were both industries that typically occupy large facilities, such as Transportation & Logistics, and industries with much smaller typical building sizes, such as Education and Agriculture. At the same time, Consumer Products and Manufacturing—the largest occupiers of industrial space—posted relatively modest increases, while Food, Beverage & Tobacco remained virtually unchanged.

The observed stability indicates that differences among industries are not driven solely by short-term market conditions. Thus, the true value of industrial classification lies not in predicting the exact size of an industrial building, but in narrowing the range of space requirements that can be expected for a given type of activity. From that point forward, the analysis must shift from the industry itself to the specific characteristics of each company.

For more information and analysis of Mexico’s industrial real estate market, visit SiiLA Market Analytics or contact us at contacto@siila.com.mx.

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¹ Differences among industries were evaluated using the nonparametric Kruskal-Wallis test (H = 369.67; p < 0.001), followed by Dunn post hoc comparisons with Holm correction. Although statistically significant differences were identified between some industries, the effect size was small (ε² = 0.038), indicating that industry explains only a small share of the observed variation in industrial building size.

² The interval indicates where most occupancies within each industry are concentrated. To prevent a small number of exceptionally large or small buildings from distorting the comparison, the analysis uses the 10th and 90th percentiles instead of minimum and maximum values.

³ Statistical significance was evaluated using nonparametric tests for independent samples, with Holm correction for multiple comparisons. At the 5% significance level, no industry showed statistically significant differences in its typical occupied building size between the second quarter of 2020 and the second quarter of 2026.