Dynamic Project Management Using Simulations.PDF

One of the toughest jobs of a Program Manager is to make decisions to correct the course of a program and ensure that all the projects in the program are following the defined flight path. More often than not, these decisions are based on 30% data, 30% group think, and 40% intuition that is really past experience! In the engineering world, we have been using simulations (computer programs that mimic or model the behavior of physical systems) for years to predict and explore system capabilities and limitations. These simulations have saved millions of dollars and in many cases even lives. Applying the engineering simulation techniques to program plans can have a similar impact on the program. It gives the program manager the ability to model and view the impact of changing any given constraint on a project on the entire program and all related projects. The simulation can also give an insight into the different level of interactions between projects and the intensity of these interactions. Now without actually implementing the new course or even changing the project plans, the program manager can view the new flight path, cost, schedule and quality implications. This paper provides an overview of how simulations assist project managers in decision making and program analysis . This paper also touches upon some leading edge simulation tools and techniques for business scenario analysis and project management that can substantially increase the overall probability of success by creating a program roadmap, managing risks , and making business decisions based on predictive analytics. Dynamic Project Management Using Simulations Most people in the business world expect their projects to be completed on-time, meet their quality objectives, and fall within the allocated budget. To most managers, time and money are critical factors to be carefully considered in any decision. These various factors make project management extremely challenging for organizations. Today's business leaders recognize that advanced decision making capabilities using simulation techniques can directly improve their organization's performance. To do so, however, a project has to be meticulously planned, effectively implemented, and professionally managed to optimally achieve the objectives of time, cost, and performance. Some of the key findings from surveys conducted by different organizations are: • 30% of organizational projects end up being cancelled midstream. • Cost overruns are as high as 190% over the planned budget and 220% over the planned time estimates. • Applied Data Research reported that up to 75% of software projects are cancelled. • The Standish Group reports the average success rate for business-critical application projects is just 9%. • In the Project Management Benchmarking Forum held in the USA, more than 50% of the Fortune 500 companies report having project management offices in place. Many projects experience schedule slippages and cost overruns due to reasons that are both varied and numerous. As there are literally thousands of variables, both human and non-human, in a project, the only way to combat the enormous uncertainties that would be easily generated out of such large varieties is to develop sound systems to manage them. Dynamic project management using simulation is a new trend in streamlining the management of projects. Complex plans can be analyzed by a computer and applied in many critical areas. This practice enables the project manager to address issues by simulating their impact on the project before they become problems. This allows projects of any size and complexity not only to be planned but also modeled to answer 'what if?' questions. © CGN & Associates 888.RING.CGN Dynamic Project Management Using Simulations 1 © CGN & Associates 888.RING.CGN Dynamic Project Management Using Simulations 2 HOW SIMULATION HELPS IN PROJECT DECISION-MAKING Simulation modeling is useful in project decisionmaking by looking at problems as a whole and articulating the complete set of relationships, interactions, and uncertainties. A business simulation model can predict what may happen in the physical system and take necessary steps beforehand, so that the physical system can maintain equilibrium despite various disturbances from both within and outside. Project planning and simulated models can be exploited to provide realtime information, as well as linking to risk-analysis, time recording, costing, estimating, and other aspects of project control. Decision makers can virtually explore future direction opportunities in a safe, cost-effective forum without having to experiment on a real system. This helps in moving from traditional “rear-view” analysis to the ability to see the predictable future, control it, and take actions today to attain tomorrow’s goals. Benefits include providing critical business insight into the project, reducing time, resources and risks; increasing the quality, utility and supportability of systems; and enabling integrated product and process development. In all instances, project work is a dynamic system. However meticulously the model is drawn, it will soon outlive its purpose unless it is continuously updated by obtaining feedback from real life. It is advisable not to build the whole model at once but rather take a modular approach where components are added a little at a time while continuously testing and validating the outputs at each stage. Simulations are effective when you cannot predict what the effects of change will be or how the proposed line might work, when you need to further understand a line or factory, when you need to test a new or proposed system before investing in the equipment, or when you have to refine an existing process. For example, an engineering program may have a complex set of varieties. The varieties are in terms of technology, equipment, materials, people, work culture, and ethics. These varieties can be combined to create a predictive model that can be used to simulate forecasts of how the program would behave over time. The intelligence of the model comes from careful definition of the business conditions, the behavior rules of the independent varieties, the dynamics of the interactions between these varieties, the frequency of such interactions, and a whole slew of other patterns that must be programmed into the model. Dynamic simulation also helps visualize multiple organizational processes simultaneously, resulting in a quantifiable solution set that is matrixed against organizational value drivers. Consequently, organizations can derive benefits from improved strategies, policies, and risk-mitigation plans; allowing management to make proactive and intelligent decisions. Exhibit 1 explains the advantages and issues in using simulations.