Analyzing Process Flows


After completing this lesson, you will be able to:

  • Utilize different analytical widgets to gain more insights on your process

Analyzing Process Flows

With Flow Widgets, an Analyst can understand and explore the "as-is" process flow.

In SAP Signavio Process Intelligence, every analysis is built by using analytical widgets. This lesson focuses on the two widgets that visualize process flows (variants) by backtracking the executed events.

Process Discovery

Every analysis starts with the most important part, the discovery of a process! Within SAP Signavio Process Intelligence, the Process Discovery Widget focuses on visualizing the different executed flows (variants) of a process and providing an overview of the actual AS-IS state.

Select the play button to watch the video on the Process Discovery Widget.

The first widget of every investigation provides a view of the actual process flow from the standpoint of events. It can also be a good entry point go get an initial understanding of the sequence of events.

Let's look at the image below of a process flow. Explore this main process flow in the Process discovery and try to answer the following question.

Case Study (optional)

Let's look at the image below of a process flow or explore this main process flow in the Process discovery by adding some activities and sequences. Then, try to answer the following questions:

  • How many T-Shirts were delivered in total?
  • How often did the shipments fail? What kind of shipment failed more, express or standard shipments?
  • What is the least common activity?
  • Do you already notice some problems in the process flow?

Findings from our Case Study!

Apparently, not everything went as smooth as intended.

Findings about delivery amount

We see that in total 805 T-Shirts were delivered.

Findings about failed shipments

We found that out of 551 standard shipments 106 of them failed and that 55 express shipments (out of 415) failed. Which indicates that standard shipments go wrong more often.

Finding about least common activity

The activity order canceled counts only 72 events and therefore is the least common in our data set.

Findings about problems in the process flow

Things did not go as planned. We see that goods are already shipped before the payment is done and that orders are canceled after the printing.

Apparently, not everything went as smooth as intended. Among others, we already observed failed shipments and canceled orders. Now that we gained initial insights into the process data, we want to further expand our analysis by determining important key parameters and KPIs.

Now we know there are many ways of how the process has been executed. Which of them was the most time-consuming one? And how many exist at all? These questions can be answered by using the Variant Explorer!

Variant Explorer

Each different flow of events can be considered a process variant. The variant explorer, lists them up and provides insights to the most common/most expensive variant. 

While creating this widget, you can decide between with conformance or without conformance to filter the result, but this requires a linked BPMN to your data (we explain how to do this in the Process Conformance section).

Check out the Variant Explorer Widget

Select each button for more details.

Case Study (optional)

To investigate the process flow based on variants, the variant explorer widget would be the right choice!

  • Reopen you investigation.
  • Create a variant explorer widget (Make sure it's set to Occurences and Case) and answer the following questions:
    • What is the most common variant? Describe the process flow.
    • How many percent of cases belong to the most common variant? Tip: Change the settings from Number to Ratio
    • Among the top 3 variants what is the process step with the highest duration? Can you make a assumption, why it takes so long? Tip: You have to set it to Cycle time

Findings from the case study!

Findings about most common variant

We see that the most common variant includes the standard shipment and 228 (26%) of all cases in the data set. It looks as follows: StartReceive Customer OrderReceive PaymentShip Goods StandardReceive Delivery ConfirmationEnd

Findings about variant with the longest duration

We also spotted that the time between Ship Goods Standard  and Receive Delivery Confirmation takes at longest (12 days), considering all cases included in the top 3 variants. A possible explanation could be that the first shipment fails, and a looping in this activity occurs which makes it take so long.

Now that we learned how our process works and which variants there are, we want to review what we've learned so far.

Wrap Up: What have we learned so far?

Process Discovery

The entry point for getting an initial understanding of sequence of events. It provides a view of the actual process flow from the standpoint of events.

Variant Explorer

A process can take different paths. The variant explorer lets you investigate them and find interesting behaviors.

Now we want to understand the filtering options in SAP Signavio Process Intelligence. For example, maybe we want to narrow down our data set to a specific set of cases. In addition, we will briefly look at the time aspect of our process with the help of more widgets.

Using Filters

We already had a look at Process Discovery and the Variance widget. Filters are a great way to dive deeper into investigations. For example, could we filter for just the cases where a shipment faults or investigate only the cases with high order amounts? Since filters apply to every widget they can also be used with all other widgets. Let's have a look at them.

Simple Filters

Filters can be used to reduce the data set and focus on certain criteria. They help create a refined view of your process data and focus on aspects you're most interested in. Here are some key points about filters:

  • Filters are additive.
  • Filters can be applied on the investigation, chapter, or even widget level.
  • Filters add or remove cases from the data.
  • Filtering impacts the widgets in the investigation.
  • For example, I want to filter cases for "premium" customers on a chapter. 

Watch the video below on how to apply simple filters on chapter level.

Case Study (optional)

As you have learned, each chapter represents typically an analysis with a certain focus and filters can be used to reduce the data set and focus on cases fulfilling certain criteria.

Now, it's time to get hands-on and get back to our case study!

  • Reopen you own investigation. Create a chapter "analyze customers" and set the chapter filter to premium customers.
  • Answer the following questions:
    • How many orders of premium customers did we receive? Tip: Use the process discovery!
    • What is the most common flow of events? Tip: Use the variant explorer!
  • Apply a additional filter for T-shirts with printand answer the first question again.

Findings from the case study!

You used simple filters to further investigate you data based on certain conditions. By using chapter level filters your filtered results applied to all widgets in the same chapter.

Findings about order amounts

By applying filters we found that out of all orders received (877), 320 of them are from premium customers. Further, 154 T-shirt with print orders came from premium customers.

Findings about process flow

For premium customers, the most common process flow is described as follows: Receive Customer OrderReceive PaymentShip Goods ExpressReceive Delivery Confirmation

Now that we learned about process flows and filter conditions, let's continue on to learn about the widgets that analyze process performance!

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