Monte Carlo: How Many
The "Monte Carlo: How Many" chart helps you answer the question "How many can we finish by then?" for a particular date. You'll be able to make statements like "There's an 85% chance that we can finish 27 items or more by March 12th, 2024."
What you'll find in this article
How it works
This chart uses your historical throughput data to determine the rate at which you finish work. You provide start and end dates in the simulation control. The simulation uses this information, along with your throughput data, to forecast how many items you are likely to finish by your end date.
It does this by running thousands of simulations taking into account the variation in your historical data to surface all of the potential outcomes and, most importantly, the likelihood that you'll finish a specific number of items.
Which historical data is used to forecast?
By default the chart will use all the historical data which has been loaded into ActionableAgile. To refine this search, make sure to select Throughput Basis in the Layout options in the top right corner, the Daily Throughput Chart will then appear and allow you to select any date range of your choosing.
In this example, the date range selected goes from 20240219 to 20240306, which means that the chart will only use the historical data from this date range to forecast.
How to read the chart
The throughput basis and throughput date control provide the data for the Monte Carlo simulation, and the results are shown in the histogram and the percentile boxes. The areas in the chart - histogram, percentile boxes and throughput basis - can be toggled on or off via the Layout chart control in the top right corner.
The throughput basis is the bottom graph where you can see what data is used for the simulations. The throughput basis shows a daily throughput (the number of items finished on a particular calendar day). You can hover the dots in this chart to see the number of items finished on a given day just as in on the Throughput Histogram.
The throughput date control is integrated within the throughput bases, so you can select a section of time by clicking on the throughput basis itself. It is similar to that of other charts in that you can select sections of the data with your mouse in order to reduce the data that is used for forecasting your upcoming work. This can be useful if some of your data was generated in conditions unlike that for which your future work will be completed in (for example you now have a different: team size, set of organizational constraints, balance of work, etc.)
The histogram is the top graph, showing the results from the simulations. It gives a picture of the likely outcomes, that is, various numbers of finished items and how often they occurred. That information provides us a likelihood that you'll achieve any particular outcome (aka the number of items finished). In the picture below, you can see that 84% of the trials finished 36 items or more, so there is a 84% chance that you'll finish 36 items or more by your target date.
Toggle on the percentile boxes to clearly see how many items could be completed in each default percentile by your chosen date.
Pro tip
If the chances of completing the desired number of items are less than you hoped for, have a conversation about what could improve the chances. If you are talking to someone who doesn't like the answers provided by the data, ask what you will do differently this time to get a result that is different than what you could achieve in the past. Keep conversations focused on how you can change the result.
Key Chart Controls
Simulation Controls
This is where you control the information needed for the Monte Carlo simulation to run:
The start date. The default setting is the current date. This is because one of the best practices is to forecast how much you can get done in the time remaining. Then, come back often as time progresses to get an updated forecast.
However, if your start date is in the past or future, you can click on the calendar icon to choose your preferred start date.
Getting the start date right is very important to the forecast. Often we misjudge when the actual start date will be. Fortunately, reforecasting often - especially as you have new information - will keep you from any late surprises!
Start date in the past:
If you use a past date you have to remember that the forecast includes all the work that is left to be done, plus the work that was already done in that timeframe. We recommend that you avoid this approach and instead choose to forecast continually using today’s date or future dates for work that still remains to be done.
The end date. Again, by clicking on the calendar icon, select the date that you need to be finished by.
Scale throughput by X. Are you thinking about making an improvement and want to see how it affects your outcomes? Play with this field to see how an improvement in your throughput will impact your forecasts. You can use decimal points here. So, if you think getting a bit of help will improve your throughput by 10% you can update this to 1.1 and see how that changes your forecast.
When using the “Scale Throughput By” feature, users can account for both an increase and decrease in throughput output e.g. if your team of four has two members on vacation for the next sprint that you’re forecasting for, set the number to 0.5 to signify working at half capacity.
Number of trials. You can increase the number of trials that the simulation runs to see how that changes your forecast. You do this by clicking on the More button and then clicking again when you want it to stop. (It will keep going until you click the button to stop.) Surprisingly you'll see that adding more trials doesn't often significantly change the range of outcomes that are likely.
Percentiles
When you choose this option, the chart looks at all of the outcomes that occurred and draws lines at the point at which that percentage of trials have finished. In this chart, these lines tell you the likelihood that you will finish a certain number of items by a specific date. So, if there is an 85% line at 36 items, that can be translated to "there's an 85% likelihood that we will finish 36 items or more by your target date." It means that 85% of the trials finished that many items or more in that time period.
Item Filter
You can filter down the items used for your throughput basis by choosing one or more available filters.
This might be useful if you want to forecast a certain type of work, say an issue type of "Story", and you would like the simulation to use only Stories from your past throughput to generate the forecast. Meaning you are filtering out all other issue types like Bugs, Tasks, Epics, etc. This can help you make sure you are comparing apples to apples, as they say.
If you want to clear your filters so that all past work is used, you click the Reset button.
Additional Chart Controls
Date Range
The Date Range control allows you to select a specific date range for your completed items across all charts.
Selecting the dates opens a calendar window where you can choose the date range that you want to see.
There are presets to select from, such as Last 30 Days, Last Quarter, etc.
Workflow Stages
Generally, the chart defines your past throughput as Items that have gone through the entire workflow, all the way to the final stage. However, you can redefine that definition for the purposes of this chart. If you deselect the Done workflow stage(s) at the end of the workflow, you will be redefining throughput as items that made it through the workflow to the Testing stage. This can be useful to find out when a body of work will likely have completed that smaller part of the workflow.
We’ve removed the option to change the throughput chart from line to bar.
If you have any questions, please submit them to our help desk.
Related Articles
Other Monte Carlo Simulations
Charts related to Throughput