Guessing is not a strategy: How to build decision velocity with AI and real-time data
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Posted on: June 25, 2012 04:09 PM |
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Thanks for sharing that.
In your presentation you mention that you need to know the project risk when defining ROI. I think this is a key point.
Quantitative risk analysis, specifically Monte Carlo simulations, informs us of the likelihood of achieving our claimed ROI. If you're producing a business case to justify your project, I recommend having a Monte Carlo simulation done so that you can inform your decision makers of the risk.
I have copied the below on the subject from the book "Bullet Dodging - A Risk Management Handbook for ICT Projects" (copied with permission)
"Quantitative risk analysis gives you valuable insights into your project that you cannot get from qualitative risk analysis alone.
Quantitative analysis enables you to calculate the probability of achieving cost and/or schedule objectives. Knowing in advance the likelihood of achieving your objectives enables more informed decision making and resource allocation.
But, the flip side is also true. Quantitative analysis also gives you the probability of losing money on the project. Quantitative analysis gives you an insight into the likelihood of realizing a negative return on investment (ROI) on the project. Knowing the likelihood of a negative ROI at the outset enables better mitigations and better go/no-go decisions.
Quantitative analysis gives you the ability to calculate contingency reserve requirements to achieve a set likelihood of successful project delivery. If your sponsor wants to be 80% sure of being able to deliver the claimed project benefits, quantitative analysis enables you to calculate the contingency reserves that you need to give your sponsor that level of confidence.
Quantitative analysis gives you the ability to rank and assess the factors that cause the most uncertainty. This sensitivity analysis enables you to create plans to reduce or eliminate one or more of the most impactful factors to reduce the overall project risk.
Quantitative risk analysis is the only dependable way to evaluate overall project risk. Quantitative risk analysis enables this assessment by aggregating the effect of all individual project risks on project outcomes.
Quantitative evaluation of schemes after implementation is vital for producing realistic estimates of optimism bias to be used in the future. Monitoring and evaluating will also support improvements in costs, benefits, and timing for use in appraisals.
"
In your presentation you mention that you need to know the project risk when defining ROI. I think this is a key point.
Quantitative risk analysis, specifically Monte Carlo simulations, informs us of the likelihood of achieving our claimed ROI. If you're producing a business case to justify your project, I recommend having a Monte Carlo simulation done so that you can inform your decision makers of the risk.
I have copied the below on the subject from the book "Bullet Dodging - A Risk Management Handbook for ICT Projects" (copied with permission)
"Quantitative risk analysis gives you valuable insights into your project that you cannot get from qualitative risk analysis alone.
Quantitative analysis enables you to calculate the probability of achieving cost and/or schedule objectives. Knowing in advance the likelihood of achieving your objectives enables more informed decision making and resource allocation.
But, the flip side is also true. Quantitative analysis also gives you the probability of losing money on the project. Quantitative analysis gives you an insight into the likelihood of realizing a negative return on investment (ROI) on the project. Knowing the likelihood of a negative ROI at the outset enables better mitigations and better go/no-go decisions.
Quantitative analysis gives you the ability to calculate contingency reserve requirements to achieve a set likelihood of successful project delivery. If your sponsor wants to be 80% sure of being able to deliver the claimed project benefits, quantitative analysis enables you to calculate the contingency reserves that you need to give your sponsor that level of confidence.
Quantitative analysis gives you the ability to rank and assess the factors that cause the most uncertainty. This sensitivity analysis enables you to create plans to reduce or eliminate one or more of the most impactful factors to reduce the overall project risk.
Quantitative risk analysis is the only dependable way to evaluate overall project risk. Quantitative risk analysis enables this assessment by aggregating the effect of all individual project risks on project outcomes.
Quantitative evaluation of schemes after implementation is vital for producing realistic estimates of optimism bias to be used in the future. Monitoring and evaluating will also support improvements in costs, benefits, and timing for use in appraisals.
"
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