Munich Personal RePEc Archive

Academic Institutions Risk Decisions using Six Thinking Hats based Analysis

Rangi, Pradeep Kumar and Aithal, Sreeramana (2020): Academic Institutions Risk Decisions using Six Thinking Hats based Analysis. Published in: International Journal of Case Studies in Business, IT, and Education (IJCSBE) , Vol. 4, No. 2 (24 December 2020): pp. 270-279.

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Abstract

Today, almost everyone faces extraordinary health, social, and economic risk due to the COVID-19 pandemic. As for all industries, academic institutions face unprecedented challenges and are witnessing the change in short-and long-term risk profile due to COVID-19, e.g., enhanced information and cybersecurity risk due to the adoption of new collaboration tools, deterioration in the effectiveness of traditional fraud risk mitigants as enrollment and document verifications over email, and increased risk of financial viability. In addition to having a robust risk management framework, it is critical for the institutions to carefully recognize and mitigate these emerging risks, which may have long-term implications on the institution's academic performance and perpetuity. Educational institutions, therefore, must adopt a broad spectrum of thinking methods that allow a practical framework for risk decisions and provide a strong foundation for academic institutions to function and enforce strategies both throughout and after the COVID-19 period. With the help of an example, this paper explores how "Six Thinking Hats" may serve as a decision aid and facilitate the risk decisions in an academic institution around risk appetite, risk identification, risk assessment, control design, and risk monitoring. The "Six Thinking Hats" or colors are all about gaining direction, i.e., what can happen (threat and opportunities; effect and probability) and not merely about explaining the event, what is or what has happened. Risk management being forward-looking, this is a significant risk decision consideration. The paper also analyzes the "Six Thinking Hats" method using the ABCD analysis framework as a research case study.

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