The Acumen Fuse ribbon analyzer is an efficient and effective way to measure schedule quality. It has 300+ metrics and many metric groups to assess the quality of your schedule.
Based on considerable real-world feedback, the Acumen Fuse developers created the Schedule Quality metric group as having the most important metrics to consider for schedule quality. Schedules judged high quality by the Acumen Fuse Schedule Quality metric group are deemed to have a much higher probability of success.
The ideal situation is for your team and scheduler, with schedule quality assessment know-how, to work together and develop the initial project schedule. The Acumen Fuse software was designed to provide a quick and iterative way to check schedule quality as schedule planning progresses. The Acumen Fuse ribbon analyzer helps to measure metrics throughout the project’s life.
This article demonstrates the Acumen Fuse ribbon analyzer and iteratively measuring schedule quality during schedule planning.
Demonstration
Figure 1 displays our demonstration project, the initial draft of an HVAC (Heating, Ventilation, and Air Conditioning) improvement plan.
Figure 1
This fictitious plan has similar scheduling attributes often found in real-life projects. Let us perform an Acumen Fuse v8.9 update 11 schedule quality metric group analysis of this schedule.
Import Schedule
In Acumen Fuse, we choose Oracle Primavera | Single Project from a P6 XER file, Figure 2.
Figure 2
We locate the XER file of our initial project plan and click open. Another dialog box appears, asking us to select the schedule we want to import again, Figure 3.
Figure 3
You can save multiple schedules to an XER file; we must tell Acumen which schedule to import. Our XER file has one schedule, so we choose it and click OK, Figure 3. Our schedule appears in the navigator pane, Figure 4.
Figure 4
The number zero in parentheses is the number of scheduled tasks that are read in; it is zero because, at this stage, the schedule is linked to Workbook1 but has not been imported. We followed through with the import by clicking the top portion of the Import All Projects button, Figure 4.
The schedule appears in the Figure 5 navigator pane with the classic Oracle Primavera red icon and the number twenty-five in parenthesis, telling us how many tasks were imported.
Figure 5
Great! Our schedule is imported into Acumen Fuse.
View Schedule
To view it in S1 projects, we (1) select our HVAC schedule in the navigator pane, then (2) click the display-level scroll and slide it to level three, Figure 5. When we collapse the bottom dock, the schedule activity table and Gantt chart appear, as in Figure 6.
Figure 6
We can examine the attributes of a deliverable or task in the activity table by expanding the bottom dock, selecting the item in the task table, and viewing its attributes in the bottom dock.
Schedule Quality Analysis
To run a schedule quality metric group analysis of our schedule, we (1) select the S2 //Diagnostics tab, (2) choose the Schedule Quality metric group in the playlist and (3) click the top portion of the Fuse button, Figure 7.
Figure 7
The Schedule Quality ribbon analyzer results for the HVAC project’s initial plan appear in Figure 8.
Figure 8
On the far left in Figure 8 is the project name, followed by a timeline and the Schedule Quality metric group results for the project’s life. Our schedule has a failing metric group score of 16%; it has room for improvement. The Acumen Fuse ribbon analyzer highlights the following issues:
- Missing Logic: Several tasks are missing a predecessor, successor or both.
- Insufficient Detail: One task requires more details on the effort.
- Number of Lags: Too many tasks have positive lags.
- Number of Leads: A few tasks have leads or negative float.
The number of lags metric, Figure 8, flagged tasks with lag. A few lags are acceptable (usually, the number of relationships in the schedule with lag should be 5% or less), but we need to inspect the magnitude of these lags; tasks having excessive duration are problematic.
The lags metrics’ yellow scorebox below the title, Number of Lags, lists the number of activities flagged for lag, eleven. The percentage in parenthesis tells us the percentage of tasks flagged for lag out of those scheduled tasks included in the inspection. The yellow scorebox color tells us that the schedule scores average on this metric and has room for improvement.
When we click on the Number of Lags yellow scorebox, the bottom activity browser displays a list of tasks with lags, Figure 9.
Figure 9
When we inspect the original schedule, Figure 1, we observe a significant gap between the Receive Performance and Payment Bonds (H1020) and HVAC Material (H1100). This connection requires further review. Back in S1 // Projects we select the HVAC Material (H1100) effort in the task table and view its relationships in the bottom dock relationships tab, Figure 10.
Figure 10
Figure 10 shows that HVAC Material’s predecessor relationship has an excessive 100-day lag.
The Schedule Quality metric group in S2 // Diagnostics flags all tasks having lag but does not specify the magnitude of each task’s lag. However, the Number of Lags metric did provide a bottom browser list of tasks with lags and we are further able to inspect each of these task’s lag magnitude in S1 // Projects.
When we take a closer look at the HVAC plan, we further define significant problems with the schedule:
- Insufficient Detail: We need to provide more details for the HVAC material procurement process.
- Number of Lags: An investigation of the list of lags revealed an excessive 100-day lag between tasks H1020 and 1100, which defines the time for procurement of the HVAC material.
- Insufficient Detail: Task H1210, Task Order Contract Period of Performance, extends the project’s life and is non-driving. Its purpose is to track the overall progress of the schedule. It flags for insufficient detail
- Missing Logic: Task H1210 is missing a successor.
We update the schedule as follows:
- Insufficient Detail: We inserted three tasks to better detail the procurement effort.
- Number of Lags: We removed the 100-day lag and extended the duration of the HVAC material task to the vendor procurement task, which was inserted as part of step one improvement of insufficient detail.
- Insufficient Detail: We make the H1210 task a level of effort (LOE) activity type and rename it H1002 to relocate this period of performance task in the pre-construction deliverable.
- Missing Logic: we tie H1210 into the contract award and project complete tasks.
Our updated schedule appears in Figure 11.
Figure 11
We then return to S1 // Projects, select Workbook 1, and repeat the steps to import the updated schedule, Figure 12.
Figure 12
The navigator pane for Workbook 1 and two versions (HVAC initial schedule and HVAC 2 update) of the schedule appear in Figure 13.
Figure 13
We enter S2 // Diagnostics and rerun the Fuse analysis; the ribbon analyzer results of the initial and updated schedules appear in Figure 14.
Figure 14
Schedule Quality Improvement
The updated schedule, HVAC 2, Figure 14, improved the Schedule Quality metric group score; it increased to 29%. Investigate the insufficient detail metric for the initial and updated schedule. You will find that the HVAC ‘Task Order Contract Period of Performance’ is no longer flagged for this metric.
However, because we extended the HVAC Material task, it now flags for having a duration greater than ten percent of the project life. That explains why this Insufficient Detail metric did not improve.
We did, however, remove the one-hundred-day lag on HVAC Material’s predecessor, which benefited the Number of Lags metric on this task. Connecting the Task Order Contract Period of Performance to the Project Complete milestone slightly improved the missing logic metric.
This was also reflected in the Logic Density above two, which is what we want. Each task should have at least one predecessor and successor, and a Logic Density just above two indicates this criterion is met.
The ribbon analyzer also highlights the following remaining problems with the schedule quality;
- Number of Leads: Too many tasks have leads or negative lag. Most government agencies forbid the use of any leads.
- Missing Logic: Too many tasks are missing logic.
- Insufficient Detail: As mentioned above, our HVAC Material task has insufficient details
- Number of Lags: Too many tasks have lag.
We update the schedule as follows:
- Number of Leads: We removed all the leads on the following tasks: Demo HVAC, Electrical Material, Pump Foundation & Mounting, and Obtain Basis of Design (BOD) Letter.
Most government agencies forbid leads, so you want to remove them from your schedule. Often, you can replace leads with start-to-start (SS) relationships and positive lags. However, guidelines limit positive lags, too, so look for ways to describe the actual schedule situation without lag. A good plan is to replace a lag with a task defining a known scope of work and using finish-to-start (FS) relationships will help you do this.
- Missing Logic: We provide successors to Demo HVAC, Demo Pumps, Demo Piping, Demo Ductwork, Electrical Labor, Pump Labor, and Piping Labor.
- Insufficient Detail: We accept this metric result as an agreeable exception for a long-lead procurement item.
- Number of Lags: We remove as many positive lags as possible.
Most of these lags were with SS relationships. What is most important is defining the order of precedence between the two tasks; the magnitude of the delay is often arbitrary. Instead of specifying a concise delay to start the successor, having both tasks start together while defining the order of precedence is better.
You will want to consult with your industry subject matter expert on this approach and the necessity of each lag. A few are acceptable, and most are not necessary. As mentioned in (1), a good approach is to replace positive lags with tasks defining known scopes of work and FS relationships.
The updated schedule is displayed in Figure 15.
Figure 15
We then return to S1 // Projects, select Workbook 1, and repeat the steps to import the updated schedule, Figure 16.
Figure 16
We enter S2 // Diagnostics and rerun the Fuse analysis; the ribbon analyzer results of the initial HVAC, first improvement HVAC 2, and final update HVAC 3 schedules appear in Figure 17.
Figure 17
The second schedule update, HVAC 3, delivered an agreeable 82% Schedule Quality metric group score. But we need to consider the ribbon analyzer’s major highlighted issues as follows:
- Missing Logic: As we would not expect the first task to have a predecessor and the last a successor, we accept these two missing logic tasks as agreeable.
- Insufficient Detail: We accept this as agreeable for a long-lead procurement item.
- Number of Lags: A few positive lags are acceptable.
- Merge Hotspot: One task has a high number of predecessors. This means much must happen on time for this effort to commence on schedule. Merge hotpots are discouraged, but one in the schedule is fine.
Remember that this demonstration was primarily to show the utility of the Acumen Fuse ribbon analyzer after each schedule update to measure the improvement in schedule quality. Any changes schedulers make in the project plan must be closely coordinated with the project team.
Summary
The Acumen Fuse ribbon analyzer provides an efficient, effective and iterative utility for measuring schedule quality as the project plan develops. The Schedule Quality metric group contains the metrics Acumen Fuse developers thought were most important.
Another vital metric group in the Acumen Fuse playlist is the Defense Contract Management Agencies (DCMA) Fourteen Point Assessment; it is an industry-standard. The DCMA 14-Point metric group requires a baseline and at least one snapshot to review all fourteen assessments in this metric group. For more discussion on the DCMA 14 Point assessment, check out the following Ten Six blog and free E-book below:
The Schedule Quality and DCMA 14–Point metric groups are “gatekeepers” for starting your schedule metric analyses. After filtering your schedule tasks through these two “gatekeeper” metric groups, consider the Logic metric group, as sound logic is the backbone of a healthy schedule. The logic metric group output for our demonstration is shown below in Figure 18.
Figure 18
The Logic metric group Scores show improvement through each schedule iteration, but there is still room for improvement. So, Acumen Fuse is a handy iterative utility that supports a review of overarching schedule quality metrics and other more in-depth logic diagnostic analyses throughout the planning process.