| In this article, I shall be dealing with the topic - | | | | entropy of the systems. Selective information |
| Project Risk Management and demonstrate how one | | | | processing and the indices available from the existing |
| could find mathematical equivalents for an abstract | | | | project management literature is no longer adequate. |
| methodology. Any project, large or small is associated | | | | I'll provide my standard IT example here. IT projects |
| with expected and unexpected problems. The | | | | are technically much more demanding than the |
| analogy mentioned above could be derived from the | | | | projects from the classical industry standard projects. |
| Second Law of Thermodynamics. The Second law of | | | | We are talking about professional project |
| thermodynamics deals with a concept : Entropy. | | | | management efforts in a very highly complicated and |
| Entropy, in short, is the amount of disorderliness of | | | | abstract technology, which has several abstract |
| the system. Entropy is also a measure on the | | | | interfaces that could take any form depending upon |
| information contained in an system. In information | | | | the sub set of parameters that influence the |
| technology, entropy is considered as the amount of | | | | outcome at any particular moment. Thus, studying |
| uncertainty in an given system. This has a defined | | | | entropy of such systems and observing the behavior |
| relation, "As the amount of information increases, the | | | | to fit any standard distribution would help you close |
| disorderliness of a system (entropy) decreases". | | | | the gap between the existing high level of |
| Considering our project management scenario as a | | | | abstraction and the level of information to properly |
| system, one could come up with a model system, | | | | direct the project effort. |
| comprising of micro and macro phases, each having a | | | | Compliance is another project in IT projects, if not |
| certain amount of entropy. Considering the | | | | for no other reason, than the trotting status of IT |
| information to be inversely proportional to the | | | | projects. Technology has traditionally kept building |
| entropy (okay, almost inversely!), means to increase | | | | itself over the existing infrastructure, but IT projects |
| the information, through careful planning | | | | have proven to refute this standard behavior. Thus, |
| communication and monitoring the project progress | | | | compliance to the proven methodologies may need |
| would increase the information available to a project | | | | necessarily not prove a good project standing. An IT |
| manager. This way, the entropy decreases. As | | | | project may fall short of the expectations a day |
| uncertainty is proportional to risk, decreasing the | | | | before going live. The kind of data available and its |
| entropy or increasing the information available, one | | | | consumption as well as decision making also has a |
| could decrease surprises. | | | | definitive complexity, which multiplies the project risk. |
| Projects typically follow a certain distribution, which is | | | | Add to it, the fact that the computer programs have |
| unique to the project as the project itself. This lends | | | | a life cycle of their own and that these programs |
| well to modeling the project using one of the several | | | | "evolve" with time, its almost next to impossible to |
| proven mathematical models of Information theory | | | | assign one particular behavior to IT projects. |
| and study the progress to follow the distribution. If | | | | Additionally, the project team working on the |
| the project exhibits a pattern, then using the | | | | program development may or may not outlive the |
| statistics, one could directly plug the values such as | | | | software life time. There is a "human factor" to |
| cost/schedule variances and/or other indites to | | | | these projects, which is not time proven. We do not |
| monitor, track and optimistically, predict the project | | | | have the "legacy" as with other application areas. |
| behavior. | | | | Segmenting the project into micro and macro states, |
| The situation is much more complicated than the | | | | studying the individual parts and gathering the |
| classical project management from the technological | | | | parameters of these and analyzing their fit in the |
| advancements, which are both a boon and a bane. | | | | "whole" such as a fine grained approach, without |
| With the Internet and Networking technology, the | | | | losing the information from the "coarse grained" |
| amount of information available has exponentially | | | | paradigm would complement each other in projects |
| increased over the years, thereby increasing the | | | | of complexity as those mentioned above. |