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Comparing PROAct
Comparison with Other Risk Analysis Tools
PROAct is often confused with other tools that incorporate Monte Carlo simulation.
Monte Carlo (simulation) is simple, elegant process that allows probability distributions to be combined. Thus, a project model can have judgments about uncertain inputs expressed as probability distributions. When some inputs are probability distributions, the outcome forecasts are also distributions. Simulation allows characterizing project performance uncertainties and also provides a more accurate forecast.
The discussion below compares and contrasts PROAct with two other classes of tools:
Crystal Ball® and @RISK® are general-purpose simulation add-ins for Excel and 1-2-3* spreadsheets. They add features to use Monte Carlo simulation with most anything that can be modeled in a spreadsheet.
*Such products are increasingly unlikely to be compatible with Lotus 1-2-3; it appears Microsoft has won the spreadsheet war.
Project Scheduling Tools are gradually being equipped with simulation capabilities. While not as flexible as a spreadsheet, most projects are adequately modeled with the structure of the given tool. The activity network is solved with probability distributions for completion times and, perhaps, constraints. Example tools include @RISK and Risk+ add-ins for Microsoft Project and a "Monte Carlo" supplement for Primavera Project Planner (P3).
PROAct Complements Project Planning and Scheduling Software
Traditional project planning and scheduling software does little with risks.
PROAct complements rather than competes with the above tools.
- PROAct is, foremost, a system to help with project risk management. Identified uncertainties and actions are captured and tracked. The risk management inventory is maintained throughout the project cycle, not just in initial project planning.
- Candidate risk abatement actions are prioritized with a structured cost/benefit/risk analysis.
- A simple Monte Carlo simulation calculates a distribution of project cost uncertainty about the base line projection. While not as accurate as a full project simulation model, the PROAct analysis is much easier to perform.
PROAct Data.
Most project planning is built upon best-estimates for activity costs and completion times. PROAct provides a means for simplifying uncertainty estimation by performing a Monte Carlo simulation about the baseline cost (or schedule). PROAct generates distributions for the project cost (or schedule) uncertainty. The judgements about uncertainty include:
- Probability that a contingency event will occur (risks as well as opportunities, uncertainties with positive impact).
- Probability distribution for the cost (alternately, schedule) impact if the contingency occurs.
- These above two items are adjusted for the result of management actions selected for implementation.
- Probability distribution for the cost of risk management actions.
A cost/benefit analysis helps the manager decide what actions are most effective and should be implemented.
A logical sequence of project risk management evolution would be:
- Project planning and scheduling with conventional scheduling software. Limited formal risk analysis.
- Adding PROAct for facilitating a program of project risk management. The distribution of project cost uncertainty can be forecast and used for contingency planning.
- Stepping up to a full Monte Carlo simulation of the project activities network. PROAct is retained for risk management, but the detailed project model is used for evaluating key project decisions.
Even with a Monte Carlo project scheduling tool, PROAct provides important risk management functions. It features a repository of identified risks and candidate actions. These can are tagged with fields identifying responsible departments, teams, persons, technology, location, etc. The inventory of risks and actions is designed to be updated, tracked, and periodically reported. PROAct's export functions enable the organization to integrate the risk management database into other project management information systems.