Enhanced Filtering using QPR ProcessAnalyzer 2020.2

QPR ProcessAnalyzer 2020.2 makes a giant leap in process mining, introducing new powerful filtering functionalities to make faster and more extensive analyses. Read more to learn about Enhanced Process Mining Filtering for making extensive analysis faster, Dashboard On-Screen Settings that make the most important selections directly accessible as drop down lists and check boxes, Path Analysis using ChartViews to analyse process variations, advanced Flow Duration using ChartViews to find and improve long lasting flows, as well as an improved Navigation Menu to get easy access to QPR ProcessAnalyzer views.

You can find our release webinar recording here and release notes in pdf here.

Enhanced Process Mining Filtering

Enhanced Process Mining Filtering for making extensive analysis faster. 

Filters are super important - but WHY? Here are my top 5 use cases for process mining filtering:

  • Large models can contain a lot of event types. Analyzing one business problem is easier within a filter that shows only a limited amount of event types.
  • Whenever the analyst makes a business finding - like bottlenecks, repeating cases, unnecessary work, or a RPA automation opportunity - it is convenient to store the business finding as a filter for later use.
  • Saved filters use the most recent data loaded into the model. This allows the analyst to instantly review useful analysis findings once the new data has loaded.
  • The favorite filters can be stored and loaded into other models.  

Enhanced filtering in 2020.2 supports all of the above use cases, as well as these advanced features:

  • Filters can easily be saved with privacy level settings "Private" (visible to the current user only), "Public" (visible to all) and "Model Default" (default filter when a model is opened)
  • Each filter has a name that can be edited
  • Filters may contain unlimited amount of filter rules
  • Filter rules are visible in the top menu. Individual filter rules can be edited or deleted directly from the menu. 
  • Filter rules can be created by selecting objects from any analysis view or manually by entering the filtering rules.
  • Filters support QPR ProcessAnalyzer Expression Language, which allows usage of fully customized filtering conditions.
  • Filters can be exported and imported. It is even possible to edit the exported filter commands or create the filter files automatically.

2020_02_Filtering

Path Analysis

QPR ProcessAnalyzer has extensive functionality for detecting, analyzing and removing unnecessary process steps for maximizing process efficiency. In 2020.2, we have added two new useful preset views for analyzing process paths starting from (ending to) any given event.

The picture below shows what happens to the the 479 cases that end up in the "Returned with claim" event. We can clearly see that the process stops at this stage for 379 cases, and all the other cases continue to the "Purchase order to supplier created" step. However, after that step, there are a total of three process variants involving "Invoice sent", "Payment received# and "Confirmed Delivery" date steps. With this information, it is easy to see what happens after an exception in any business process.         

2020_02_PathsStartingFromReturnedWithClaim

Well... the picture above shows what happens after any process exception, but what about being proactive and discovering the steps that lead to the problems? Below you see exactly this: the most common process variant that leads to "Returned with Claim" contains the "Customer pick-up" event in 164 cases. The second most common variant is coming from the event "Shipment sent". By using these Path analysis views together with filtering, it is easy to get a complete and  transparent view on events leading to problems and actions taken after the problem occurs.    

2020_02_PathsUntilReturnedWithClaim

Flow Duration

Duration analysis is one important cornerstone in process mining for:

  • Understanding the lead-times between activities.
  • Identifying too LONG lead-times and finding the related root causes for making the process faster
  • Identifying too SHORT lead-times and finding the related root causes for discovering malicious cases
  • Identifying RPA (Robotic Process Automation) opportunities - long lead times have bigger potential for saving time
  • Improving the customer experience by shortening the total end-to-end process duration. 

The new Flow Duration preset helps to achieve these goals. You just select the Start and End event types using the drop-down controls (implemented as on-screen settings). Alternatively, you can select the corresponding flow from Flowchart and the start and end event types will be updated accordingly. The third setting in the default column chart view is the "Time unit" that lets you select the best scale for the graph.

2020_02_FlowDuration

While Flow Duration lets you analyze any given direct flow in a process mining model, the extended "Duration between events" preset shows the total time spent between any two events regardless of the other events occurring in between.   

Dashboard On-Screen Settings

QPR ProcessAnalyzer's Dashboard concept is very powerful and can easily be customized. For a business user using the dashboards, it is important to have easy functionality for selecting parameters for the dashboards. On-Screen setting are the easy way to present the wanted selections for business users.

Dashboards shown in improved Navigation Menu

The improved Navigation Menu now shows the custom dashboards stored to the same project with the process model. In the example below, the "RPA Automation View" is shown right after the main eight analysis views and the workspace, followed by more technical views. 

2020_02_NavigationMenu

 

QPR ProcessAnalyzer Memory Reporting

QPR ProcessAnalyzer 2020.2 includes advanced memory reporting available in the web user interface to users with administrator rights. It is now easy to check the amount of free memory available in the QPR ProcessAnalyzer statistics control. When you click the control, it first displays Cases, then Events, then Variations, Event Types, Flows, and then Memory Available. Memory available mode shows the amount of physical memory available in the server, for example the test system below has 285MB memory available from a total of 4.0GB, ie. 7.0%. Further details available in the tool-tip tell that QPR ProcessAnalyzer is using 813M of memory. QPR ProcessAnalyzer uses optimized .Net Memory management and dropping a process model from memory using the QPR ProcessAnalyzer Model Manager does not immediately shows as a free memory available only after the memory cleanup completes. To run the cleanup immediately press Alt and click the QPR ProcessAnalyzer statistics control (in memory available mode). 

2020_02_MemoryCache Control

QPR ProcessAnalyzer 2020.2 also includes a new ChartView preset Memory Cache to show actual memory contents including process mining model specific event logs, cached analysis results and cached filters.   

  • Memory Cache shows columns Model, Cache Entry ad Additional data:

2020_02_MemoryCache

 

This is the new QPR ProcessAnalyzer 2020.2 😀👍

If you’re already using QPR ProcessAnalyzer, go ahead and try these new features when you get a chance. If not, and if you’re new to Process Mining, read more on this page. If you want to know more about QPR ProcessAnalyzer, go here. Also, don’t hesitate to book a live QPR ProcessAnalyzer demo:

It’s a good time to take a look at Process Mining if your company hasn’t already. The capabilities and usability of Process Mining software are improving rapidly, and the market is quickly becoming mature, though there’s still much work to be done. If you think your company is ready to step it up with the future of as-is process modeling and process efficiency maximization, the fastest way to get things moving is to send our Process Mining team a direct message:

Contact Us

 

Webinar Recording

Release Note

See QPR ProcessAnalyzer 2020.2 Release Note here.

 

 

Written by
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Teemu Lehto

Dr. Teemu Lehto, holding a Ph.D. in process mining, has spent more than two decades advancing the field of Digital Twin of an Organization (DTO). Teemu has helped hundreds of companies achieve unprecedented visibility into their business operations throughout his career. With a passion for this field, Teemu’s mission is to empower organizations to make data-driven decisions, optimize processes, and discover untapped potential within their businesses.

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