Project Management Part 7 Project Risk Management

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

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

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

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

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

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

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

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

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

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.)

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

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

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

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 $-350 $136 Med. crew 520 430 190 -120 $147 Small crew 280 240 170 130 $179 sample calculation: Large  .10(860)+.20(710)+.30(160)+.40(-350) = 136

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?

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

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

PERT Example Task Pred. Opt. Most Likely Pess. Te Var b -- 2 3 4 3.000 0.111 c a 3 3 5 3.333 0.111 d a 2 2 2 2.000 0.000 e b 4 6 11 6.500 1.361 f b 3 4 4 3.833 0.028 g c,d 1 1 2 1.167 0.028 h e 4 4 4 4.000 0.000 i f 3 5 8 5.167 0.694 j e,g 3 6 10 6.167 1.361 k h,i 1 1 2 1.167 0.028 Te = (a + 4m + b)/6 Var = [(b – a)/6]2

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 = 3.000 + 6.500 + 6.167 = Varcp = 0.111 + 1.361 + 1.361 = StdDevcp = sqrt(2.833) = MS Project with 3 task durations

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 and @RISK are two such packages.

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.

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

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.