Subscribe to DSC Newsletter

Evaluating Enterprise Risk in a Complex Environment

 

 

Evaluating Enterprise Risk in a Complex Environment

 

Ivan De Noni, Luigi Orsi, Luciano Pilotti
University of Milan, DEAS, Milan, Italy; University of Padua, Padua, Italy.

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. Statis-tical 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 vul-nerability 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 ap-proach which increases knowledge accumulation and improves forecasting process should be considered.


Keywords: Complexity, Extreme Events, Operational Losses, Quantitative Management

 

http://www.scirp.org/journal/PaperInformation.aspx?paperID=2750

Views: 46

Tags: chaos, complexity

Comment

You need to be a member of AnalyticBridge to add comments!

Join AnalyticBridge

On Data Science Central

© 2019   AnalyticBridge.com is a subsidiary and dedicated channel of Data Science Central LLC   Powered by

Badges  |  Report an Issue  |  Privacy Policy  |  Terms of Service