Probing Organizational Efficiency

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Purpose: In investigating the performance of multidivisional organizations, ability to account for each division's importance and contribution enhances the deftness of resource allocation and targeting desired outcomes. With this motivation, we introduce network data envelopment analysis (NDEA) from Operations Research in this conceptual article and discuss how two articles from this journal can be extended using this approach. Design/methodology/approach: NDEA was first developed to deliver a more in-depth understanding of underlying sources of operational inefficiency. Thus, NDEA can be viewed as a peer benchmarking method useful in comparing performance of organizations and identifying divisional inefficiencies that may detract from overall performance. NDEA’s ability to capture interactions among multiple variables in an objective manner based on actual observed data rather than sample averages is one of its key advantages. Findings: We discuss how NDEA can be applied in Organisational Analysis by examining two articles from this journal. Briefly commenting on one of the cases here, we show that a network can be defined as the interacting divisions of cultural norms and structural forms. The potential improvements (i.e., horizontal re-alignment) indicated by NDEA can guide management on the extent organisational alignment could be changed in reaching strategic aims. The author’s theoretical model is conducive to assessing the amount and direction of change from the proposed alignment model in a multi-criteria framework – characteristics embraced by NDEA. Practical implications: Given the hierarchical nature of organizations where employees are nested in work groups or teams, groups nested in departments or divisions, and divisions nested in organizations, application of NDEA at various levels of analysis is feasible. Originality/value: NDEA’s ability to account for each division's importance or assign desired weights in what-if analyses adds to flexibility in managerial decision-making regarding allocation of resources, or re-alignment of processes and targeting of desired outcomes. Such a method that does not assume independence among multiple performance measures provides additional assurance to those concerned about shortcomings of additive scales in complex organizations.