Abstract
This paper examines the relationship between operational risk management and knowledge learning process, with an emphasis on establishing the importance of statistical and mathematical approach on organizational capability to forecast, mitigate and control uncertain and vulnerable situations. Knowledge accumulation reduces critical situations unpredictability and improves organizational capability to face uncertain and potentially harmful events. We retain mathematical and statistical knowledge is organizational key factor in risk measuring and management process. Statistical creativity contributes to make quicker the innovation process of organization improves exploration capacity to forecast critical events and increases problem solving capacity, adaptation ability and learning process of organization. We show some important features of statistical approach. First, it makes clear strategic importance of risk culture within every level of organization; quantitative analysis support the emergence of latent troubles and make evident vulnerability of organization. Second, innovative tools allow to improve risk management and organizational capability to measure total risk exposition and to define a more adequate forecasting and corrective strategy. Finally, it’s not so easy to distinguish between measurable risk and unmeasurable uncertainty, it depends on quantity and quality of available knowledge. Difficulty predictable extreme events can bring out crisis and vulnerable situations. Every innovative approach which increases knowledge accumulation and improves forecasting process should be considered.
Highlights
This paper examines the relationship between operational risk management and knowledge learning process, with an emphasis on establishing the importance of statistical and mathematical approach on organizational capability to forecast, mitigate and control uncertain and vulnerable situations
In literature we find out paper explaining mathematical techniques application to operational risk evaluation and other concerning risk management principles and features
In the first part, we describe some aspects of operational risk mainly with respect to relationship between uncertainty and corporate learning process; in the second one, we argue general mathematical approaches implications on operational risk and knowledge management and we show an innovative mathematical method and exploit its advantages, disadvantages and further extensions
Summary
In literature we find out paper explaining mathematical techniques application to operational risk evaluation and other concerning risk management principles and features. Knowledge management is a dynamic capability [6]; a successful strategy in the short term may become less efficient in the long one if the firm is unable to increase continually its knowledge, improving competences and innovating competitive advantage. When these conditions are both satisfied, an organization can implement a generative learning process to preserve new knowledge creation and innovation. In this perspective, statistical analysis and mathematical models are some of possible tools which can help firms to improve knowledge accumulation and decision making processes. We need to distinguish between governance and management of business risk They are two interconnected but different moments of decision-making process. At opposite, when the decision maker believes to know the event distribution, his strategic behavior is determined by a cognitive model built on its previous experience and makes him less sensitive to environment changes and to perception of every signal which could prevent or handle unexpected situations (extreme events) and crisis
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