Updated: Sep. 18, 2023
This case study shows an example of how to manage schedule risk that could affect the realization of different strategic and tactical goals of a manufacturing company.
Addressing Schedule Risk
Different factory units need regular maintenance. During the maintenance work the production has to be shut down, which causes a reduction fall in the company’s income and profit.
The goal of applying risk management was to determine how a manufacturing company can ensure the highest level of income / profit by assessing and tackling different risks that occur during maintenance work.
The Szigma IntegRisk® method, developed by Hungarian Risk Management Company SzigmaSzervíz Ltd, uses Microsoft Project® 2013 and @RISK (risk analysis add-in for Microsoft Excel and Project) for the analysis (now known as ScheduleRiskAnalysis from a 2022 feature update included in DecisionTools Suite).
The Szigma IntegRisk® method is an integrated risk assessment, treatment and monitoring technique for supporting management decisions on strategic, tactic and operational level.
Dr. István Fekete, Managing Director for SzigmaSzervíz, believes that a combination of @RISK and Szigma IntegRisk® facilitates an integrated approach to quantifying schedule risks in case there are not historical data available.
The project managers had prepared a schedule for maintenance work with the help of Microsoft Project®. The length of the simplified project schedule’s critical path was calculated. In this example, the original duration before risk assessment is 26 days. (See Figure 1.) This same approach can be used with the new ScheduleRiskAnalysis which also features the ability to upload your Primavera P6 or Microsoft Project files to @RISK.
The next step was to assign potential schedule risk sources/risk events for each project activity in a series of workshops. A risk database compiled on the basis of several years of experience was used (included in Szigma IntegRisk® method). An example can be seen in Table 1.
Scenario analysis was performed as the next step to describe a series of impacts and the probability of their occurrence for each identified risk event. (An impact refers to a risk event that can affect the original duration of a project activity). Scenario analysis is a useful tool to describe the perception of different experts and produces more reliable input data for Monte-Carlo simulation, if historical data are not available.
Selection of the critical risks was based on the previously defined threshold values. If the calculated mean value and/or standard deviation overrun the threshold, that risk is labelled as critical risk.
Following that, risk treatment actions were created for all critical risks. (See Table 1)
The next step was to run Monte Carlo simulation using @RISK. During the simulation, lognormal distributions have been included by using mean value and standard deviation from the scenario analysis (see Table 1). SzigmaSzerviz’s experience shows that lognormal distribution is the best way to describe the nature of the revised activity duration once identified risks have occurred. This identifies the risk events that might cause huge deviation, but have a very low probability of occurrence compared to original activities’ duration. As a result, the probability distribution of the modified length of critical path was calculated. (See Figure 2.)
After finishing Monte Carlo simulation, a Tornado-diagram was generated to show the activities most likely to be responsible for delays to the project. The identified risk events assigned to most of these activities might cause the biggest deviation compared to the original length of critical path so the risk treatment actions for these activities are first carried out. (See Figure 3)
As a result of Monte Carlo Simulation the difference between mean and original value of the length of critical path is roughly 4 days. (26 versus 30, 258 see Figure 2). If the duration of maintenance activities is longer than planned the restart of the production is delayed which causes significant income/profit deficit for the manufacturing company. For this reason it is vital to model the impact of the results of the risk assessment on production and income/profit plan of the company, as illustrated in Figure 4.
The result demonstrates that, if the maintenance work is delayed by 4 days from the scheduled date due to inadequately managed risks, the profit before tax might decrease with HUF (24,981 – 23 606) = 1.375 Bn (€ 5M). However, undertaking risk management activity opens up the possibility of meeting the original deadline of maintenance works and avoiding the € 5M loss.
According to Mr. Fekete the key benefits of @RISK are as follows:
- A wide distribution gallery can be chosen for defining the probability distributions of input parameters
- Good communication between Microsoft Project® and @RISK
- Easy application
- Useful reporting opportunities for decision makers
- Combining Szigma Integrisk® and @RISK makes it possible to produce reliable output data if no historical data is available
About SzigmaSzervíz Ltd
SzigmaSzerviz Ltd., established in 2006, is the first Hungarian company engaged in integrated risk management. Szigma IntegRisk® risk management system and software is unique on the international market. This system gives an effective method for decision-makers, to support decisions ranging from strategic planning, to project management and annual planning, to internal auditing. SzigmaSzerviz Ltd. aims to foster risk awareness in organizations. Szigma IntegRisk® is not just software, but a complex business solution, which can provide a significant competitive edge to companies in the current economic environment.
New ScheduleRiskAnalysis with DecisionTools Suite
Solve schedule problems like one demonstrated in this SzigmaSzerviz Ltd. case study with the new ScheduleRiskAnalysis in DecisionTools Suite. Apply Monte Carlo simulation to Microsoft Project and Oracle Primavera P6 models, generate probabilistic Gantt charts, and easily calculate and report the Critical Index – all within Microsoft Excel! With probabilistic Gantt charts, you can see the likelihood of various durations and finish dates for tasks and entire projects. Plus, with critical indices, you can easily locate the tasks that matter most to your project’s critical path. Learn more about ScheduleRisksAnalysis.