Data is necessary for project management. It serves as the backbone for all types of decisions to be made by the project manager. It is, therefore, important to collect, organize and present data clearly so that all stakeholders will understand the status of the project. This is the reason why it is so important for good project managers to not only know and understand but also utilize data gathering and representation techniques. These techniques are used to collect, organize and present data and other information involved in the project life cycle.
There are two types of data gathering and representation techniques used in project management and these include (1) interviewing and (2) probability distribution. Interviewing is a technique that draws the historical data to quantify the impact of risks on the objectives of the project. The information that needs to be collected and organized depends on the type of probability distributions used. It is also important to create the necessary documents such as the risk ranges to provide important insight on the credibility of the analysis of the data.
The second method uses extensive simulation and modeling. It represents uncertain values like duration of scheduled activities as well as the cost of the different components of the project. The probability distribution may include discrete and uniform depending on the data that is available. Distribution methods are used to depict that shapes compatible with the data developed during a quantitative risk analysis. Aside from the two methods, simulation is also another method used to estimate the risk and probability distribution.
In project management, the data gathering and representation techniques are very important in performing quantitative risk analysis and management plans. It is, therefore, crucial for the project manager to use these techniques to shed light on what the collected data is all about.
This term is defined in the 5th edition of the PMBOK.