This guest contribution on Innovation Intelligence is written by Guy Shtub, Co-Founder and CEO at SandboxModel LTD. Project Team Builder software by SandboxModel uses simulation technology to predict the project outcome resulting in better decision making, more accurate forecasts and ultimately better project results. Project Team Builder is available through the Altair Partner Alliance.
Companies, across different industries, realize that managing projects in a more structured methodology, leads to better results.
Traditionally, project tools are used to create a basic project plan. This plan includes a Gantt chart with the tasks, a basic project schedule, budget and resources. The plan is then presented to management for approval before the project starts. During the project’s life cycle, the plan is continually updated with current information and is used to monitor and control the project.
The above method is lacking in three important aspects:
1. Project Alternatives
First, alternative methods for performing the project are not considered on a project level basis. Modern projects are complex and there are many different ways to perform them. These include technological alternatives and operational alternatives at the task/module level. A single project plan already assumes different choices for how to perform each activity without considering the effect on other tasks and on the entire project. Moreover, the decision for how to perform a single task cannot be considered without seeing the “big picture”. For example, consider a software development project. A specific software module within the product might be developed in house, outsourced or possibly bought “off the shelf”. In the traditional method the decision is made independently, that is without taking into consideration similar decisions made for other modules. Such a decision has implications on the project in terms of duration, cost and quality of the software module.
Second, risks and probabilities are not taken into account. The traditional approach assumes that tasks have a deterministic duration, resources always show up and things always go as planned. By adding probabilities and risk events, which in many cases can be predicted, we can create a much more accurate model of the project. An example would be duration of tasks. If we add a simple three-point estimate, that is the optimistic, pessimistic and most likely duration for each activity, we can then run Monte Carlo simulations to understand how likely our project is to finish by a given date. Similarly, we can better predict the cash flow, the project value and the critical activities.
Third, in the traditional approach, the value that will be generated by the project is not measured. If it’s not measured it makes it impossible to consider the tradeoffs between project duration, cost and value. For example, spending an additional $30,000 on the project will increase the value, let’s say by offering three more important features to our new product. Should we do this? Perhaps. However, we can’t make that decision if we don’t have all the information available to us in one tool, at the project planning stage.
By considering and comparing different project alternatives, trading off project cost, duration and quality and by taking probabilities and risk into account, we can achieve significantly better project results.
At the project planning stage, the project team creates an advanced project model that includes:
- Alternative methods for performing each task. The information includes the impact on the project in terms of duration, cost, resource usage, risk and value.
- Probabilities and risks. This includes possible risk events, probabilities for them to occur, and the cost to mitigate the risk when applicable. Additionally, deterministic variables such as task duration and available resources are replaced with estimates and probabilities.
- Value and quality requirements for the project. This information deals with the goals of the project in terms of the value that it creates along with measurable requirements. An example in a radar development project would be the range of the radar, the energy efficiency and the reliability.
Once we have this advanced model in place, we can evaluate different project alternative plans. We can also consider the probabilities that a specific plan will satisfy the project goals.
The PTB Simulator is based on this methodology. It supports project teams and allows for better decision making.
Using an advanced methodology for project planning allows project teams to answer questions like:
- What is the preferred way to execute my project?
- What are the risks involved?
- How can the risks be mitigated?
- Is the project likely to finish on time and on budget satisfying the stakeholder’s expectations?
Improving decision making at the project planning phase results in significantly improved project results.
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