We encourage you to analyze your schedule updates with our secure, no-obligation demo.
Schedule metrics should be considered self-evident
Aggregated metrics, most commonly represented by the DCMA 14-Point Assessment, are often used for diagnosing schedules at the enterprise level. These diagnostics are important for identifying risk trends across a large number of projects, but they should be considered self-evident at the project level where analysis should be proactive. Stakeholders should expect more meaningful evidence that management is invested into planning and controlling their project. Schedules result from collaborative narratives unique to each project and analysis requires context beyond aggregatable data. For example, a project’s dashboard may indicate good schedule performance, despite an emerging bottleneck or improperly integrated scope. It’s time to shift perspective away from “some information is better than no information”.
Drill-down analysis is isolated from context
Metric-based assessments are attractive because they are technical and measurable against benchmarks. Metrics that indicate potential problems can be drilled down to view the data (e.g. changed logic), but evaluating isolated data, with no context to upstream causes and downstream effects, doesn’t tell a story. These drill-down reviews can best be described as not seeing the forest for the trees, often resulting in analysts facing limitations, including:
- Metrics are not able to provide evidence of properly modeled networks that resulted from project collaboration.
- Schedule integrity and performance indicators are not measurable against the whole schedule, including key milestones.
- Schedule quality metrics frequently promote superficial fixes to the project plan.
- Dashboards cannot indicate if schedules are rational and planned in logical sequence.
Our software reconstructs schedules to make them easier to read and analyze
Even though we provide metrics that summarize the overall schedule, as traditional software warrants, we believe real compliance and accountability depends on understanding the integrity of the plan. Our technology allows users to read project schedules naturally during planning efforts, and then analyze causes and effects during forensic efforts. Cause and effect analysis is only possible when the entire schedule network is charted, enabling you to compare each schedule update to expose root causes and as-sequenced effects on the plan. Plan analysis promotes a better, collective understanding of the project and improves the modeling of how the team can get it done.
Our technology advances schedule analysis
Improving the plan and evaluating the true quality score of a schedule requires project collaboration, not relying on dashboards and expecting them to tell the story. Metric-based analysis software evaluates changes between lists of activities and relationships, but is not able to evaluate changes to the underlying plan. Now that plan-based analysis is achievable, schedule-based analytics becomes a routine consequence of the all-inclusive context. Dashboards provide information, but often fail to tell enough of the story. Project management must understand their schedule, and analysis should ensure each component contributes to the overall story of the plan.