Lecture Series on
If I may, let me start my journey on this subject with some meaningful quotes from many greats:
“The person who risks nothing, does nothing, has nothing, is nothing, and becomes nothing. He may avoid suffering and sorrow, but he simply cannot learn and feel and change and grow and love and live.”
Paul Tillich quotes (German born AmericanTheologian and Philosopher, whose discussions of God and faith illuminated and bound together the realms of traditional Christianity and modern culture. 1886–1965)
“Only those who will risk going too far can possibly find out how far one can go.”
Having heard about Risk, let’s start from the scratch and explain our logic, modeling, and applications. Let start with our logic:
Managing Risk-Sensitive decision-making process is one of the fundamental challenges in operational, tactical and strategic levels. Ignoring the presence of the risk entity, may be resulted in a hard to manage incident of deviation, disruption or disaster. Rather than to be reactive to the risk consequences, it is much easier to be proactive by recognizing, identifying, analyzing, and then managing the risk.
I like to start with introducing of some basic instances of risk management in the form of prototype and expand upon those cases.
In operations management the most frequently encountered incident is risk aversion in inventory management. The trade-off between the Cost of Goods Sold (CGS) and service level (SL) is the decision of concern.
In an example of tactical instance, managing the risk associated with the development of a new product, is a case of risk analysis. This includes capital investment, environmental issues and consumer’s welfare.
At strategic level, corporate financial performance is the main focus and interest.This includes the incorporation of marketing intelligence in expending proper capital and proper allocation of resources in strategic issues.
As we agree that risk is not avoidable, may be a necessity, in a theoretical as well as practical setting of a business entity, the design of a risk-tolerant and/or risk control framework will be of prime interest.
The basis for our approach and study here are the understanding of the theoretical framework for risk-sensitive decision making along its expected utility function and its application along with probabilistic processes. The same logic may be applied to operational, tactical, and strategic issues.
Modeling of Risk Analysis – If I wanted to describe this question in one sentence, I would say
“Any Risk Analysis Modeling is composed of a predictive model for the possible events and an associates utility function for loss or gain.”
This description is applicable to Operational, Tactical, as well as Strategic scenarios. The art, science and technology deployed in this process have paramount impact in the consequence of the application of such a model. In an operational inventory management case, the risk of stock out and the consequential service level may be simply modeled as an (s, S) policy. It also may be modeled as a dynamical stochastic model with empirical demand and supply probability function.
Risk analysis at a tactical level, such as new product development, may provide the same variety of options in modeling.
The same applies to strategic issue….Stay Tuned for the next week. I look forward to your input, contribution, and comments. I may be reached at javad@supplychain institute.com.