Baseline Compliance™ is a measure of how many activities fall within the period that they were expected to fall within. Instead a measurement known as Baseline Compliance™ has been developed and is the basis of measurement for this investigation. In short: there is no control of granularity using this type of measurement. A small one-day slip at the start of the project could cause a domino effect along the critical path causing an erroneous report that all activities on the critical path have slipped. The reason being: the measurement is a binary measure that does not take into account how large a slip or acceleration the activity is experiencing. Traditional performance metric analysis uses simple comparisons such as “number of activities that started or finished relative to their corresponding baseline dates.” However, a recent white paper determined that this type of measurement is not suitable for CPM schedules. Earned value is a sound measure of value created relative to effort/time/cost expended but for the purpose of this research project, the focus is around schedule rather than project cost and so a more schedule-centric method is needed. When selecting a measurement technique for execution performance, there are several choices. The Schedule Quality Index™ is based on a 1 to 100% scale with 1% being the lowest quality and 100% being a perfect quality score. Using this approach, individual metrics are combined into a “Schedule Quality Index™.” This index is a combination of the listed metrics weighted based on their contribution to the structural integrity of a sound project plan.
The amount of redundant or unnecessary logic in a schedule Total number of activities that have lags in their predecessors. Total number of activities with total finish float less than 0 working days Number of activities with total float greater than 2 months. Number of activities with hard or two-way constraints Number of activities with soft or one-way constraints This number should not exceed 5%Īverage number of logic links per activity. Total number of activities that are missing a predecessor, a successor, or both.
įor this exercise, Acumen’s extensively used and well-established standard schedule check metric library was used to score the quality of the project plan. Today, there exists several industry standards for schedule metric analysis such as the DCMA 14-Point Assessment as well as thought leaders’ recommended best practices (see Acumen white paper on metric analysis).
Through the use of metric analysis (looking at the likes of quality of logic consistency of detail appropriate use of activity constraints use of leads/lags and the resultant impact on float), we now have a means of actually quantifying the quality of a project schedule. However, it has only been in recent years that the project management community has recognized the value of applying similar analysis to determine the quality of planning. Accepted approaches such as performance tracking, earned value, earned schedule and progress relative to a baseline are all commonplace today. Within the discipline of project management, techniques for quantitative tracking of project execution performance are reasonably well established. To describe this in a more qualitative manner: objectively determine the quality of the plan and compare against the quality of the execution to determine any relationship between the two. If these two core entities can be successfully quantified, then any correlations between them can be determined easily using standard statistical correlation techniques. So as to establish true quantitative measures for the analysis, the objective of the modeling was to quantify two primary attributes of a project: In order to prove or disprove the hypothesis, a quantitative analysis approach was adopted. The alternate hypothesis is that there is indeed a positive correlation between sound project scheduling and successful on-time project execution completion, or, the better the plan, the higher the chance of on-time or early completion and the lesser quality of the plan, the higher the chance of a project overrun. Instead, the success of execution is driven largely by the contractor’s ability to execute to a plan irrespective of its realism or achievability. The null hypothesis for this research exercise is that there is no measurable relationship between quality of planning and quality of execution.