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The Loops Report Page focusses on those variants and individual cases where a specific activity or a sequence of activities had to be redone before it went forward in the process.

A loop is the repetition of one or more activities and often leads to unnecessary extra work and costs. The loop analysis distinguishes between Loops and Selfloops.


  • Next to the menu, you can see the Process Explorer which gives you the opportunity to take a closer look at Loops in your process.
  • You can see an overview using three different cards, right next to it. Furthermore, the distribution of your (Self-)Loops over time is visualized in an area chart. By clicking on one or more points of that area chart you can activate the PAFnow Root Cause Analyzer, which is located right underneath.
  • On the right side, there is a navigation bar (similar to the other pages) including different visual filter and selection elements.

Theoretical Definition


A Selfloop is an activity/process step that repeats itself. It is depicted as a circle (⟳) in the node of the activity.

In this example Approve PO Level 2 was conducted more than once.


In contrast to a Selfloop, a Loop is a repetition of a sequence of process steps.

In this example, the sequence of Post GR and Post neg. GR was repeated.


A (Self-)Loop combines information of process steps having at least one Loop or Selfloop. You will find two attributes in the data model indicating whether there is a loop or selfloop (=1) or not (=0). The two attributes can be found in the Event Log (namely ActivityHasLoopsOrSelfLoops) and in the Cases Table (as HasLoopsOrSelfLoops).

Process Explorer

The PAFnow Process Explorer visualizes your business process in a process flow; on the Loops Page the Loops and Selfloops in your process are shown.

The edges highlighted in red are the ones with Loops. To get a clearer picture of the Loops in your process just click on the green button right beside the Process Explorer. This will switch between highlighted selections and only Loops or only Selfloops will be highlighted.

In this example only Loops are highlighted in red in the process flow graph. A total of two Loops are found.

Loops Overview


Next to the Process Explorer you can see three different cards which are explained in the table below.

Card Meaning
This key figure shows your absolute number of cases which either have Loops, Selfloops or both.
This key figure shows the absolute number of Loops in your process.
This key figure shows the absolute number of Selfloops in your process.

Area Chart

# Cases with (Self-)Loops over Time and Trend

In this Area Chart you can see the development of Loops over time. You can recognize trends or noticeable deviations. The green dashed line is the trend line.

Root Cause Analyzer

In case of a process anomaly, you can use the PAFnow Root Cause Analyzer to deliver automatically generated principle insights on root causes of specific process behaviors (such as Duration Times or Loops). Here, you can use it to directly derive actions against the causes of Loops.

The Root Cause Analyzer only starts an analysis when you make a selection in the Report. This ranges from a specific process behavior, choosing an anomaly in a report element (table, pie chart, bar chart, etc.) or the PAFnow Process Explorer. Then the Root Cause Analyzer starts its AI-supported calculation of the causes.

The PAFnow Root Cause Analyzer is explained in detail in the PAFnow Root Cause Analyzer documentation. Below, you find an example on how to use it on the Loops Report Page:


To activate the Root Cause Analyzer just click on one behavior you want to explain, such as the increase of (Self-)Loops at a particular point in time.

In the example, we wanted to find the root cause for having 52 (Self-)Loops on 01.02.2014.

The Root Cause Analyzer shows many bubbles with one bigger bubble in the center. Here we can see that one specific resource can explain the behavior with 67.4 percent. When you hover over a bubble a tooltip appears helping you to better understand the root cause.

Ø Lead Time of Cases: PAFnow Duration Card

With (Self-)Loops:

Without (Self-)Loops:

These key figures compare the average lead time (LT=LEAD TIME) for the entire process, for business transactions with Loops, and for business transactions without Loops.

This comparison shows you how strongly Loops affect your lead time and if they cause major delays in your process. More information about the PAFnow Duration Card can be found in the PAFnow Duration Card documentation.

Treemap: # CASES by YEAR¶

The Treemap can be used to filter your Loop Page by several attributes, see Discovery Page for detailed explanation.


This table lists Loops and Selfloops per variant. If you select a column header, the whole table is sorted by this column.


You can use this table to activate the Root Cause Analyzer. For example, you can sort the table by the loops column and select the variant with most loops to have the PAFnow Root Cause Analyzer display the most likely causes of these loops.