Fundamentals of Risk in Decisions – Part 2

In the previous blog post in this series, we introduced the concept of intangible factors that can influence (or prevent) decisions even though a compelling financial argument might be clearly apparent. At the core of decision paralysis is fear:

  • What do I not know?
  • Am I missing something?
  • Can I really believe/achieve the projected outcomes?
  • Will I regret making a decision? Maybe status quo is good enough.
  • If I wait to decide, I’m sure I’ll have more/better information later.

The three general rules of moving toward a favorable decision are:

  1. The ratio of the investment to the expected return influences the decision between financial risk and performance risk
  2. The level of risk tolerance should exceed the level of risk exposure
  3. The upside value potential should exceed the value being put at risk

Rule 1 deals with the emotional part of the decision conundrum and highlights how the amount of resources required, the amount to pay or the size of the deal can trigger an emotional bias that can magnify the apparent size of the risk. This influence causes us to alter our strategy, sometimes subtly, because we “feel” the risk more. But this feeling may be an illusion.

The second rule of the decision process is that the level of risk that is acceptable should be greater than the level of risk you are being exposed to. Analyzing these risk factors involves:

  1. Identifying the most comment incident events that might occur
  2. Determining how each event would impact the decision
  3. Determining how much risk can be tolerated for each event
  4. Evaluating the probability of the event occurrence in each of the decision choices

These risk factors are measured and computed to arrive at a risk exposure and risk tolerance value for each solution. The gap between the tolerance and exposure is termed “inherent risk”.

Inherent Risk graph
If this result is negative, then the inherent risk of the decision is unfavorable and indicates that there may be unmitigated risk in the decision since the exposure is greater than what is willing to be accepted. Conversely, if the gap is positive, then the inherent risk is favorable and suggests opportunity to assume some additional risk to gain additional value opportunities. The inherent risk can be applied to the decision investment to create a risk-adjusted investment value.

The VMware Risk Analysis process identifies specific areas of risk, assesses the customer’s feeling for the potential for problems and risk tolerance, and computes an inherent risk/return factor that can be applied to the TCO. This process is used to create a risk-adjusted TCO by increasing or decreasing the benefit with respect to the perceived risk.

In summary, the key to drawing the fear-based decision inhibitors into the light is to identify, quantify, analyze, then forecast each possible measured event. Essentially, we are defining the intangible risk factors and determining our level of risk acceptance, then evaluating the probability or likelihood of the occurrence of each event for each decision choice. Ultimately, a score is developed that considers if the risk this decision exposes is less than the risk we’re willing to accept to achieve the desired outcomes. If so, then the decision has acceptable risks than can be managed or mitigated.

In the final installment of this blog series, we’ll discuss the third rule which applies the inherent risk factor to the cost side of the decision and show how this can produce:

  1. A risk adjusted investment or TCO in an IT decision
  2. A return on risk
  3. An estimation of value impact

These economic factors provide additional insight into a decision that now contains the influence of risk, emotion and intuition and can help lead you to a more confident plan of action.

Resources to learn more:

About the Authors

Craig Stanley

Group Product Line Marketing Manager / Cloud Economics at VMware

Craig Stanley is a Group Product Line Marketing Manager in the Cloud Economics group. He specializes in economic cost analysis and the art of decision making. Craig has been in the IT industry for over 35 years, including 9 years as a Gartner VP and Research Director and 8 years at VMware. As a Gartner analyst, he specialized in datacenter benchmarking, trends and analysis and authored several research notes. At VMware, Craig has been responsible for developing methodologies that help our customers understand how to effectively connect and align their IT initiatives to their desired business objectives. As a Cloud Economist, he drives conversations around the economic value and benefits of VMware’s Cloud offerings. Craig holds a BS degree from the University of South Alabama and an MBA from The Citadel in addition to a US Patent for a mathematical benchmarking methodology. He is based in the US.

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