This study aims to explore the main features of managerial performance reporting (MPR) in Ghana and applied a national social-cultural framework to understanding the MPR practices.

It is a qualitative study based on responses from mid-level managerial employees within the top companies in Ghana dubbed Ghana Club 100 (GC100). GC100 includes a balanced mix of companies across varied industry classifications and local and multinational companies (MNCs). This enriches the data and deviates from similar studies that have usually relied on data from multinational companies.

There is evidence that while MPR practices in Ghana do not significantly deviate from western approaches, the underlying reasons for such managerial practices and actions may defer on national socio-cultural lines. This study discusses how various cultural attributions explain the features and motivations for MPR practices in Ghana, including a difference in expectations about the purpose of an MPR.

MNCs must be guided by the findings of this study in their drive to inculcate standardised practices across organisations. It is also essential for MNCs to appreciate the more than usual reliance on verbal cues and symbols in interpreting the appropriate course of action. Regulators must consider systematic activities that reduce the tension and suspicion between them and business actors to improve information transparency. Whistleblowing schemes, while helpful, may not be effective because organisational agents within MPR practice consider themselves part of an “in-group” and manage their dissonance through categorisation, rationalisation and superficial attention to standards. Because of the excessive use of unwritten cues, auditors must consider visits to the client’s operational premises and other independent observation efforts vital to their evidence gathering process.

To the best of the author’s knowledge, this paper is among the first to evaluate MPR practices based on direct responses from “persons close to the MPR action” rather than the current overreliance on secondary data sources such as content analysis.