Full Monte™ Features

**Full Monte’s risk analysis software includes the following features:**- Support for normal, lognormal, beta, triangular, and uniform distributions.
- Probabilistic and conditional branching
- Unlimited correlations between task durations
- Fast and comprehensive sensitivity analysis, including “tornado” chart
- Distributions can be specified with optimistic and pessimistic values.
- Customizable s-curve/histogram.
- Bar charts produced for duration, numeric, and cost fields.
- Calculation of expected value and standard deviation of early and late start, early and late finish, free and total slack, and cost for each task.
- Histograms and s-curves of early and late start, early and late finish, free and total slack, and cost for each task.
- Calculation of active percentage (for branching), critical percentage, sensitivity index, and project finish dates based upon optimistic and pessimistic durations (sensitivity analysis) for each task.
- Calculation of delay due to merge bias at each merge point.
- Data in tabular reports can be exported to CSV format (suitable to import into Excel).
- Customizable reports can include Full Monte and Project fields.
- User-configurable mapping of data to MSP fields to allow coexistence with other add-Ins.
- Easy to use (no VBA or similar programming required for any of these features).
- Fast (3,614 task network, 1,000 simulations, about 30 seconds on a fast laptop).
- Utility to migrate data from Deltek Risk+.
- Compatible with all Windows® Operating Systems.

Sensitivity

Sensitivity analysis pinpoints those tasks or outside influences which most critically affect the finish date and cost of the project, or part of the project. Full Monte’s sophisticated sensitivity analysis tools produce a short-list of the most likely candidates during the risk analysis, in the form of a tornado chart. From this you are a mouse-click away from a more thorough analysis for any task, which among other things can tell you the influence of that task on any percentile (e.g. “P-80”) of the project finish date or cost.

“Everything should be made as simple as possible, but not simpler.” — (Albert Einstein, as quoted by Roger Sessions.)

Some tools try to make risk analysis “simpler than possible.” Barbecana has gone to great lengths to make sure Full Monte is easy to use, but it is not “dumbed down.” For example, some products produce symmetrical tornado charts, based just on a standard deviation; they look pretty but are generally not correct. Full Monte estimates the true values of the bar ends resulting from the optimistic and pessimistic durations respectively.

“Everything should be made as simple as possible, but not simpler.” — (Albert Einstein, as quoted by Roger Sessions.)

Some tools try to make risk analysis “simpler than possible.” Barbecana has gone to great lengths to make sure Full Monte is easy to use, but it is not “dumbed down.” For example, some products produce symmetrical tornado charts, based just on a standard deviation; they look pretty but are generally not correct. Full Monte estimates the true values of the bar ends resulting from the optimistic and pessimistic durations respectively.

*Monte Carlo tornado chart (above) is showing approximate sensitivity of project early finish to various tasks, and a much more realistic non-symmetrical spread.*

Clicking on a bar in the tornado chart creates this more detailed picture of the sensitivity, showing two cumulative distributions of project finish date, based upon optimistic and pessimistic values for the duration of the selected task.

Clicking on a bar in the tornado chart creates this more detailed picture of the sensitivity, showing two cumulative distributions of project finish date, based upon optimistic and pessimistic values for the duration of the selected task.

Monte Carlo Simulation

Full Monte uses Monte Carlo simulation – named after the famous casino – to produce more realistic schedules by modeling the uncertainties inherent in any prediction of the future. Monte Carlo works by simulating the project thousands of times, each time using a different set of duration estimates sampled from distributions specified by you. Results are presented in terms of histograms and s-curves of early and late dates, free and total float, and cost, for every task in the network.

Full Monte uses Monte Carlo simulation – named after the famous casino – to produce more realistic schedules by modeling the uncertainties inherent in any prediction of the future. Monte Carlo works by simulating the project thousands of times, each time using a different set of duration estimates sampled from distributions specified by you. Results are presented in terms of histograms and s-curves of early and late dates, free and total float, and cost, for every task in the network.

Correlations

Full Monte’s uniquely simple implementation of correlations through “correlation sources” allows multiple tasks to be correlated due to one or more outside influences, while precisely maintaining their specified distributions. Furthermore, it requires no extra data other than the name of the source.

This is more powerful than specifying correlations directly between task durations, and contrasts with the much more complicated idea of multiplicative “drivers,” which require additional data entry.

Full Monte’s uniquely simple implementation of correlations through “correlation sources” allows multiple tasks to be correlated due to one or more outside influences, while precisely maintaining their specified distributions. Furthermore, it requires no extra data other than the name of the source.

This is more powerful than specifying correlations directly between task durations, and contrasts with the much more complicated idea of multiplicative “drivers,” which require additional data entry.

Full Monte, MS Project and Primavera

Full Monte is a Microsoft Project (2007 and above) and Oracle Primavera P6 Add-In. It is so closely integrated with each of these programs that it seems like part of the product. All Full Monte functionality is accessed from the MS Project / Primavera menu system, with no need for awkward imports or exports.

The Need for Speed

Full Monte is over 100 times faster than competing systems. For example, 10,000 trials on a 3,600 task network takes about three minutes. (Users have run Full Monte on networks as large as 54,000 tasks.) What’s more, it does a sophisticated sensitivity analysis at the same time!

Speed matters because it is important to do a large number of trials in order to get reliable results. And the reason that Full Monte is so fast is that it was developed by CPM scheduling experts. Unlike competitors, Barbecana specializes in risk analysis in the project scheduling context. Full Monte performs all the CPM calculations itself instead of relying on Project to do them.

If risk analysis is worth doing it’s worth doing properly, so if you don’t want to have to leave your simulations running overnight Full Monte is your clear choice.

What’s wrong with PERT?

The Program Evaluation and Review Technique (PERT) was the first attempt to address uncertainty in project networks. It is seriously flawed because it considers only a single critical path and hence does not account for the phenomenon of merge bias, which is arguably the biggest single reason for modeling risk in the first place. This simplistic approach could perhaps be excused in view of the limited computing capacity available at the time (the late 50’s) but there is absolutely no reason to settle for this flawed approach in the 21st century