Some concern had been shown regarding the limited availability of castor seed to satisfy the rising yearning for its seed oil for use in industrial and domestic applications. This growing demand calls for refocus on backward integration in order to ensure sustained supply chain. This study adopts a factorial analysis that involves the use of Principal Component Analysis (PCA) and Kendall’s Coefficient of Concordance (KCC) as statistical procedures to analyze some critical factors affecting the growth of castor shrub and its seed. KCC analyzed the degree of agreement among the fifteen Judges who ranked the thirty-two identified variables affecting the growth of castor shrub and the suitability of its seed oil in industrial application in descending order of importance. The result of the KCC showed an index of concordance in ranking as indicating 61% agreement among the 15 judges. The PCA helped to analyze the Judges responses arranged in form of data matrix that was facilitated by the use of statistiXL software. The PCA result revealed significant parsimony in data reduction from thirty-two to four principal factors creatively labeled: Seed oil particularities, Resource Conversion Efficiency, Plant-cooperation-oriented yield and Soil Condition respectively. The implication of this is that the principal factors that influence the growth of castor shrub and the suitability of its seed oil in industrial application has been identified.