Precision agriculture (PA) technologies used for identifying and managing within-field variability are not widely used despite decades of advancement. Technological innovations in agronomic tools, such as canopy reflectance or electrical conductivity sensors, have created opportunities to achieve a greater understanding of within-field variability. However, many are hesitant to adopt PA because uncertainty exists about field-specific performance or the potential return on investment. These concerns could be better addressed by understanding where variability in soil physical and chemical properties may have the greatest effect on crop responses to inputs, such as nitrogen fertilizer. Therefore, identifying fields that exhibit the most variation in soil characteristics (e.g. clay and organic matter content) and developing an indicator of variation that has the potential to affect crop responses to inputs could greatly advance PA adoption and use. The objectives of this research were to: 1) quantify the amount of potential soil variability over a large region, 2) generate an index that numerically identified fields that exhibit degrees of field variability, and 3) evaluate spatial clustering of variability over the region. This analysis focused on soil variability in agricultural fields across Missouri, USA. We calculated a variability index (VI) for clay and organic matter content at two depth increments (0-30 and 0-120 cm) using soil information from the National Resources Conservation Service’s (NRCS) Soil Survey Geographic database (SSURGO). Ranges in VI for clay at the two depth increments were 1-82 and 1-91 with an average of 2.4 and 2.2, respectively. Organic matter VI averaged 2.0 and 2.3 for the two increments with narrower ranges from 1-42 and 1-29, accordingly. Significant high clay VI clusters at both increments were observed mostly along the Missouri River floodplain and across southeastern Missouri along the Mississippi River. High organic matter VI clusters exhibited similar distributions along the Missouri and Mississippi River floodplains; however, significant clusters of low organic matter VI values occurred within the Central Claypan and Southern Mississippi River Alluvium major land resource areas. Output from this research could be used as a decision support tool to aide suppliers and practitioners in determining the greatest opportunities to implement PA.