Acumen Fuse’s merge hotspot metric flags tasks for potential delay when they have more than 2 predecessors. To isolate riskier tasks and prioritize them for a more in-depth delay analysis, you can relax this requirement to apply it only to tasks with more than 7 predecessors.
The Merge Hotspot metric examines a schedule for tasks with many predecessors. Activities with a high number of predecessors have cumbersome start criteria: many efforts need to finish before the activity can begin.
These tasks, therefore, have a high risk of delay. And could impede schedule progress: much like a poorly streamlined vehicle that has a hard time moving forward because its restricted air movement impedes its progress. We refer to this hindrance to schedule progress as ‘Schedule Critical Path Drag.’ In the following article, we introduce this critical drag concept:
The Acumen Merge Hotspot metric does not report on critical drag; it identifies areas of the schedule most likely to be delayed by bottlenecks. But because their delay probability is high, you should prioritize these tasks for review in your Schedule Critical Path Drag inspection.
In this article, we demonstrate how to efficiently adjust the merge hotspot threshold to list the merge hotspot tasks most likely to delay.
Merge Hotspot Metric
Schedules that are judged to be of high quality have a much higher probability of success, which, after all, is what you want. The Acumen Fuse software was designed specifically to confirm schedule quality or to expose areas requiring improvement. In the following article, we introduce the core features of Acumen Fuse to support your schedule quality assurance efforts.
One of these core diagnostic features is a playlist of (available) metric groups, including the Schedule Quality metric group.
The Schedule Quality metric group in Acumen Fuse consists of nine metrics that Acumen Fuse developers consider the most important attributes of a quality schedule. The Merge Hotspot metric is one of the nine and identifies activities where delay is highly probable. And where a task delay is likely, the possibility of Schedule Critical Path Drag affecting progress exists.
The Merge Hotspot metric is a measure of the complexity of task merges where delays are likely to occur, rather than the amount of critical drag. Schedules having ten percent or less merge hotspots achieve a passing quality score, and this is your goal.
Further, it makes sense to isolate the merge hotspot tasks where delay is most likely to occur and consider them first for critical drag review. This prioritizes tasks based on the likelihood of delay, a negative characteristic that also increases a task’s critical drag potential.
And reviewing these tasks most at risk for delay makes for good risk assessment. This prioritization of probable critical drag tasks for review is implemented by relaxing the merge hotspot metric from more than 2 predecessors to, say, more than 7 predecessors.
Demonstration
We now demonstrate how to adjust the Merge Hotspot metric to flag tasks with more than 7 predecessors and then generate an Excel spreadsheet listing the captured tasks with their attributes.
The heart of the Acumen Fuse schedule quality assessment tools lies in the software interface tab, ‘S2 // Diagnostics’, as shown in Figure 1.
In Figure 1, S2 // Diagnostics tab, the upper-right panel displays the ribbon analyzer results, which show how each metric performs over the life of the project. The lower-left is the phase analyzer, which indicates how each metric performs at specified intervals. The upper-left is the intersections analyzer, which isolates a single metric and shows its performance for each interval.
At the bottom of the screen, you can select a metric group for analysis from a playlist. The active metric group in Figure 1 is Schedule Quality, and its results are shown in the ribbon, phase, and intersections analyzers views.
We want to adjust the Merge Hotspot metric to capture and list merge hotspot tasks with the most acute risk of not starting on time. This requires familiarity with the Metrics tab, displayed in Figure 2.
Figure 2, above, shows the basic elements that make up a metric definition. These include, as shown for a metric selected in the navigator pane: the Primary Formula, which filters schedule tasks meeting the selected metrics inclusions and filter criteria (either standard and/or advanced formula filters), the Secondary Formula that are all tasks meeting just the Primary Formula’s inclusions criteria, the Tripwire Formula that defines a task listing based on the Primary Formula (inclusions and filters), the Tripwire Thresholds that uses color codes to specify thresholds and the Define Columns tab where you can create a list of variables for output to Microsoft Excel.
These formula outputs are displayed in the S2 // Diagnostics ribbon and phase analyzers, where the ribbon analyzer’s top number in the scorebox is the tasks captured by the primary formula, its bottom percentage in parentheses is the Primary Formula divided by the Secondary Formula times one hundred and the scorebox’s color is dependent on the intervals specified in Tripwire Thresholds.
In Figure 2, we 1) click the Metrics tab, 2) select the Merge Hotspot metric in the navigator pane and Schedule Quality metric group, 3) click the Primary Formula tab, and 4) edit this metric’s advanced formula. We modified the advanced formula, changing the flag criterion for the number of predecessors from more than 2 to more than 7, see Figure 2.
The merge hotspot formula Excel syntax, Figure 3, then reads as follows: in the yellow box, the logic test checks if the number of predecessors is greater than 7; in the green box, true conditions become the integer 1 and false the integer 0; in the blue box, the 1s and 0s are summed to compute the number of tasks for which the condition (total predecessors > 7) is true.
Then, to generate the listing of these (more than 7 predecessors) tasks, we click 1) Metrics, 2) choose Merge Hotspot in the navigator pane, 3) click the Tripwire Formula tab, and 4) edit the tripwire’s advanced formula, Figure 4.
We change the threshold for listing a task from more than 2 to more than 7 predecessors, as shown in Figure 4. In Figure 5, the Excel syntax in the yellow box checks whether the computed sum is greater than 7 and returns true or false; the blue box’s Excel syntax AND function ensures the output is explicitly treated as a logical TRUE/FALSE data type.
Back in S2 // Diagnostics, we 1) click the top portion of the Fuse button to run the Schedule Quality Fuse analysis, 2) click the Merge Hotspot yellow scorebox, 3) confirm the output is Tabular, and 4) in the bottom activity browser, see the listing, which includes for our demonstration schedule 5 tasks flagged with more than 7 predecessors, Figure 6.
It would be nice to see which of these tasks are critical, so we can narrow our critical drag analysis to those most likely to delay and are on the critical path. To add a critical column, we right-click the description header and choose Show Column Chooser from the pop-up menu, as shown in Figure 7.
From the column chooser, we locate and left-click the Critical option, drag and drop it between Original Duration and Number of Predecessors.
Our Tripwire Formula output now lists, for each, the attributes: number of predecessors and criticality, as shown in Figure 9.
We want to create a Microsoft Excel spreadsheet from this list, including the attributes of each captured task. To have the Excel spreadsheet include each task’s critical attribute, we do the following: 1) click Metrics, 2) select Merge Hotspot in the navigator pane, 3) click the Define Columns tab (for Excel output), 4) choose the placement (we click between Original Duration and Number of Predecessors variables), and 5) click Add, Figure 10.
From the dropdown menu, we select the Critical option in Figure 11.
Figure 12 shows the columns, including the Critical attribute, that will be output with our Excel spreadsheet.
Back in S2 //Diagnostics, we click the bottom portion labeled To Microsoft Excel, then click To Microsoft Excel, as shown in Figure 13.
Acumen generates the Excel spreadsheet shown in Figure 14, which lists the flagged, most likely-to-delay Merge Hotspot tasks and their attributes, including Critical and Number of Predecessors.
Based on this output listing, the schedulers in our demonstration should prioritize their Schedule Critical Path Drag investigation on the task ID EC2440 ‘Complete Building 1’; it has the most predecessors and is on the critical path.
After you complete your merge hotspot and critical drag investigation, remember to change the Merge Hotspot metric back to the more stringent requirement, flagging and listing tasks with more than 2 predecessors. Relaxing the merge hotspot criteria helps assess and make incremental improvements to your schedule. But you want to report using the more conservative Schedule Quality metrics developed by the Acumen Fuse inventors; these are their proprietary metrics for a quality schedule.
To report on your schedule based on an industry standard, run the Fuse analysis for the Defense Contract Management Agencies (DCMA) 14-Point Assessment metric group. But this metric group includes neither merge hotspots nor critical tasks metrics.
Summary
The Merge Hotspot metric flags tasks with predecessors exceeding a specified threshold. Acumen developers determined that the best criterion is to flag tasks with more than 2 predecessors. This threshold can be adjusted by modifying the Merge Hotspots metric’s advanced and tripwire formulas to narrow your merge hotspots listing to those tasks with more predecessors. And you can output these results, along with the critical attribute for each flagged task. This supports a prioritized, focused Schedule Critical Path Drag task analysis of the tasks most likely to delay and are on the critical path.
With an understanding of the elements that make up an Acumen Fuse metric and a rudimentary knowledge of Excel syntax, schedulers can perform “minimally evasive surgery” on the Merge Hotspots metric. And in this way, narrow and prioritize their tasks for critical drag analysis and review. Further, a handy tool for calculating a task’s critical drag is introduced in the article at the following link: