1. Project Management Part 7 Project Risk Management

2. Topic Outline: Risk Management
Project risks and risk management
Identification of risks
Risk assessment and risk analysis
Contingency planning
Time and cost padding
Expected values
Risk management exercise
PERT analysis
Computer simulation analysis

3. Project Risks
Uncertainty a random chance that something will happen, with no way to control whether it happens
Risk an uncertain event or condition that could negatively impact project performance
Each risk has a likelihood, or probability, of occurring and possible outcomes if it does occur

4. Managing Risks
Since the project manager is responsible for project success, he or she can increase the likelihood of success by better managing risks
Risk management is a proactive approach to dealing with uncertainties rather than a reactive approach
Some risks can be disregarded and some can be avoided, but others should be planned for

5. Project Risk Management
Risk management in projects involves:
Identifying risks
Assessing and analyzing the likelihood and impacts of risks
Trying to reduce the uncertainties (by gathering more information or making different decisions)
Trying to lessen the impacts of risks
Developing contingency plans for critical risks
Monitoring risks as the project progresses

6. PMI’s View of Risk Management
Risk management consists of 6 subprocesses:
Risk Management Planning
How to approach and conduct risk mgmt. activities
Risk Identification
Qualitative Risk Analysis
Assessing likelihoods and possible outcomes
Quantitative Risk Analysis
Computer simulations; decision tree analysis; etc.
Risk Response Planning
Risk Monitoring and Control

7. Identification of Risks
Identifying all of the possible events or conditions that might occur and may negatively impact project performance
A brainstorming session with the project team can be a helpful way to ensure that all important risks are identified
Determining symptoms or warning signs that indicate when the risk is about to occur
Determining root causes of the risk

8. Risk Assessment This info. should be developed for each risk:
Description of risk
All the possible outcomes of the risk
The magnitude or severity of the outcomes
Likelihood (probability) of the risk occurring, and likelihood of each possible outcome
When the risk might occur during the project
Interaction of the risk outcomes with other parts of this project or other projects

9. Risk Assessment Matrix
Likelihood
Severity
Detection Difficulty
When
System Crash
Low
High
Startup
Software Glitches
Medium
Post-Startup
Users Dissatisfied
Hardware Malfunction

10. Risk Analysis Tools Probability analysis Decision tree analysis
Monte Carlo simulation analysis
Life-cycle cost analysis
Delphi techniques for consensus
Technology forecasting
Game theory analysis
PERT analysis
Sensitivity analysis
Expected value analysis

11. Reducing Risks
Try to reduce uncertainties (collect more information, use more reliable vendors, design for easy production, don’t use leading edge technologies, etc.)
Try to reduce the severity of potential outcomes (purchase insurance, convince customer to share the risk impacts, train employees how to respond quickly, etc.)

12. Contingency Planning
A contingency plan is an alternative plan used if a risk event or condition occurs.
Examples:
Having a backup supplier for a key material
Carrying a safety stock for a key part
Having an alternate distribution channel to send products to China (air instead of boat)
Having hurricane evacuation plans

13. Time and Cost Padding
Padding is a commonly used approach to address risks, since it is very easy to implement and since it protects against most minor risks
Padding refers to inflating the original time or cost estimates for activities or for the project
Unfortunately, this leads to longer project durations and higher costs

14. Time and Cost Padding
People will generally use up as much time and money as they are allowed (if you don’t use it you lose it!)
Student syndrome if extra padding is built into activity time estimates, some people are likely to procrastinate getting started, and then the protection against risk is lost
Although padding can be useful in reducing the severity of risk, it can also lead to inefficiencies and waste

15. Expected Values
A construction manager is trying to decide what size crew to schedule for tomorrow based on weather:
Weather
Probability: 10% 20% 30% 40% Expected
Alternative Nice Cold Rain Snow Value
Large crew $860 $710 $160 $ $136
Med. crew $147
Small crew $179
sample calculation:
Large  .10(860)+.20(710)+.30(160)+.40(-350) = 136

16. Risk Management Exercise
Nelson Mandela Bridge case (25 minutes)
Divide into small groups
Read case
Discuss the issues and answer these questions:
How would you have identified the risks?
Using the table provided, discuss how the risks were addressed and/or how risks could have been addressed. Also, indicate any additional risks you can think of.
Indicate whether the risks listed are internal or external.
Describe how you would determine the expected values of the risks listed.
Do you think that risk was adequately managed in this project? Why?

17. Uncertain Task Durations
Probability distributions
Discrete, uniform, triangular, normal, beta, etc.
Most common way to consider task uncertainty is to estimate the most likely, pessimistic, and optimistic durations.
PERT analysis assumes a Beta distribution for each task

18. Estimating Task Times (with PERT)
Activity duration estimates:
a=optimistic, m=most likely, b=pessimistic time
Expected task duration:
Te = (a + 4m + b)/6
Variance of task duration:
Var = [(b – a)/6]2

19. PERT Example Task Pred. Opt. Most Likely Pess. Te Varb
c a
d a
e b
f b
g c,d
h e
i f
j e,g
k h,i
Te = (a + 4m + b)/6 Var = [(b – a)/6]2

20. PERT Example
Use Te values for task durations on project network to compute slack values.
The results of the new computations still shows path b-e-j as the critical path, with an expected project duration of
Tcp = =
Varcp = =
StdDevcp = sqrt(2.833) =
MS Project with 3 task durations

21. Computer Simulation Analysis
General purpose simulation software can model how many products flow through all the machines in a factory and on to the warehouse. This capability is much more than what is needed to simulate projects.
Monte Carlo simulation is much simpler type of simulation analysis that we can use to model the uncertainty of task durations and costs.
Crystal Ball are two such packages.

22. Crystal Ball and Project Analysis
Crystal Ball allows you to specify any type of probability distribution for each task.
You specify all precedence relationships.
It then “shoots” random numbers into your probability distributions to simulate thousands of completions of the project.
The result is a probability distribution of the total duration of the project, from which you can answer the what-if questions about how long the project might actually take.

23. Goldratt’s Critical Chain
Assuming that an activity duration is known leads to underestimating project durations
Because of this, people tend to pad their time estimates
This may result in the “student syndrome”
What is that?
This in turn leads to procrastination, which can then result in missing the finish date

24. Goldratt’s Critical Chain
Add safety time buffers at strategic points in the project network
Safety time buffer at end of critical path is called a project buffer
Safety time buffer just before where noncritical paths feed into the critical path is called a feeding buffer.