Energer
Perform a Monte Carlo Simulation
Our monte carlo simulation runs with a single click. Watch the tutorial video on how to generate probability forecasts for your project schedule or feel free to read the instructions and follow along.
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How do I perform a Monte Carlo for my project?
Probability Distributions in Energer
Explore Energer's three distinct probability distributions – normal, triangular, and uniform. These can be selected under the project settings page as shown.
In this step, we delve into the intricacies of Energer's three probability distributions and understand the specific task data they require.
Normal Distribution:
- Description: A statistical term defining a symmetric bell-shaped curve where data clusters around the mean.
- In Energer: Requires your project's best case and worst case durations. Random durations are distributed around the average of these two durations.
Triangular Distribution:
- Description: Represents a probability distribution with values concentrated around a central point, forming a triangle-shaped curve.
- In Energer: Requires your project's most likely date. Duration is centered around this point, using best case and worst case durations as the extremes.
Uniform Distribution:
- Description: Represents a probability distribution where all values within a given range are equally likely to occur.
- In Energer: Requires your project's best case and worst case durations. A random value is picked anywhere between these dates for task duration.
Understanding the histogram bins and number of simulations is crucial for interpreting results. Adjusting the number of bins refines the granularity of data representation, while the number of simulations directly influences the accuracy of Monte Carlo predictions.
Navigating to the Monte Carlo Section
Navigate to the monte carlo page from the Network editor or the project dashboard page. Do note that this is a Elite feature and is only available on Elite subscription types.
Initiating Monte Carlo Simulation
To initiate a Monte Carlo simulation for your project, add a description, then click "Start a New Simulation". Depending on your network complexity, the simulation may take a few minutes or in the case of some large projects cases, this might take a few hours. Energer will notify you once the simulation is complete.Given the high server resources it takes to perform a Monte Carlo Simulation, you receive few credits each month along with your monthly subscription, each time you run a simulation, you use one of the credits. You can always purchase additional credits from the Account Dashboard page.
Review Results
The results are available on the same Monte Carlo pages that you used to start the simulation.
Once the simulation is complete, you'll be presented with key projected dates for your project. Energer will show you the best-case completion date, the most likely completion date, and the worst-case completion date. This information, coupled with the histogram presented below, will give you a comprehensive insight into the potential outcomes of your project.
The histogram illustrates the distribution of completion dates across all simulations. The probability curves on the histogram represent cumulative probabilities, such as the P30 and P80 dates (which can be used to communicate a probability of completion by a certain date for your project ). Hover over any column in the histogram to view specific data for that scenario. Analyzing these curves and dates helps you make informed decisions, estimate probabilities, and assess risks effectively.
Managing Risks in Monte Carlo Simulations
In typical project management software, you would model risks by creating 'redo' loops or by adding additional tasks to account for risks (such as a failure during formal testing and having to redo some development and testing).
Energer accounts for risks in your schedule and offers a seamless way to attach risks to specific tasks. To add a risk to any task (think of the task as the trigger for the risk to be realized), click on the icon on the top right of any task. Add a description, the duration impact it'll have following this task an include the probability of the risk's occurrence .
Energer will factor this risk into the completion date during Monte Carlo simulations, providing a more realistic projection of potential outcomes and giving you full confidence on your projected completion dates. Adding key risks and re-running the simulations give you a clear picture how a risk might impact the project's outcomes.
Multiple Simulations
After major program events or updates, it's advisable to rerun the simulation to see how these changes impact your project's completion dates. Simply click on the Monte Carlo icon or use the "Monte Carlo Simulations" button and start a new simulation with the updated parameters.
You'll see a list of the latest as well as all the past results at the bottom of the page, clicking "Show" will display the data and graphs associated with the specific simulation.
Frequently Asked Questions
Monte Carlo Simulation is particularly beneficial when dealing with project uncertainties and risks. Consider using it when you have variable task durations, dependencies, and potential risks that can impact project outcomes. It provides a more comprehensive understanding of the range of possible completion dates, enabling better decision-making and risk management. If your project involves complex schedules with inherent uncertainty, Monte Carlo Simulation becomes a valuable tool for realistic project planning.
Task Data Requirements:
Energer's Monte Carlo simulations rely on accurate task data input for robust outcomes. Ensure the following details are correctly entered in the network editor or project settings:
- Best Case Duration: The optimistic estimate for task completion.
- Most Likely Duration: The most probable estimate for task completion.
- Worst Case Duration: The pessimistic estimate for task completion.
Choosing the appropriate distribution type and providing precise task data sets the foundation for a reliable Monte Carlo simulation in Energer. This step ensures that the randomness injected into the simulation aligns with the characteristics of your project's tasks, leading to a more insightful analysis of potential outcomes.
Energer uses different probability distributions – normal, triangular, or uniform – based on the user's selection. For the normal distribution, it utilizes the best case and worst case durations to generate random durations around their average. Triangular distribution centers durations around the most likely date, while uniform distribution picks a random value between the best and worst case durations.
Yes, you can customize the number of simulations and histogram bins in Energer. Adjusting the number of simulations refines the accuracy of Monte Carlo predictions, while modifying the bins provides a more granular representation of data in the histogram. Additionally, the probability curves can change how Energer picks duration values for each tasks. Each option having it's unique characteristics. However, it's essential to strike a balance, as increasing these parameters may impact simulation runtime.
Rerunning the simulation is essential after significant project events or updates to reflect changes accurately. It helps assess the impact of modifications on completion dates. The frequency depends on project dynamics; typically, it's recommended after major milestones, schedule adjustments, or when new risks are identified.
For daily use, Fever charts might be the best visual to show how your project is trending. For how often to rerun Monte Carlo Simulations, consider its strengths in handling uncertainty, intricate dependencies, and when the need for a comprehensive outlook on potential project completion dates arises. Typically we recommend running it monthly or for each formal phase exit of your program.