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Enhanced BPMN and Case-Level Predictions with QPR ProcessAnalyzer 2019.5

Are you ready for enhanced BPMN and case-level predictions? QPR 2019.5 introduces the following improvements:

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Process Mining Proof-of-Concept Success in 4 Steps

It’s been amazing to see the development of the process mining field - how more and more organizations are improving their process efficiency with process mining technology by releasing capitals from manual BPM work and focusing internal resources on actual process improvement work. If your organization has yet to see how process mining can help to cut costs, improve customer satisfaction and profit, now would be the perfect moment to run a process mining PoC to show the business value and guarantee an allocation in the budgeting for next year.

This blog post gives you insight into a successful process mining PoC in 4 steps based on QPR's experience from 400+ process mining projects.

  1. Set clear targets
  2. Choose correct stakeholders
  3. Execute as planned
  4. Close with great results

The initial two steps are basically planning with a different focus, then followed by straight-forward execution and finally closing with the key targets achieved.


1. Set Clear Targets for Your Process Mining PoC

This is the most important step of a PoC. Naturally, it is not just a process mining specific topic, but it is very much highlighted as a process mining methodology supporting many different use cases and business functions throughout the company. Therefore, super clear targets should be decided and documented. Otherwise, the PoC results would be difficult to measure. We suggest that the project charter should cover at least the following two main topics:


Process Mining Main Drivers

It is crucial to select a compact scope that fits into the project timeline targets. The scopes could be, for example:

Potentially, you can also include a couple of other important areas as you see necessary. You can find inspiration by checking out our process mining use cases and application areas.


Targets, Metrics, Data Required for Process Mining

Having determined the main drivers for process mining in your organization, you can think about the metrics for measuring the success of the chosen scope. By setting the metrics, you can show process mining benefits for the chosen scope that highlight the business value. Based on what your organization hopes to achieve using process mining, that determines the size of your process mining PoC as well as the data required for the project.


Showing the applicability of process mining

A small process mining PoC project using a single MS Excel data sheet would be enough for the visualization. With the process flowcharts, you can show your organization the benefits of a simple flat file visualization.


Driving data-driven decision making with process mining

A medium process mining PoC project with data connections to your organization's major IT system, such as SAP or Salesforce, would be needed for this purpose. The expected results are to show your organization how easy it is to connect the data in the existing IT system and how it helps with deriving new and useful information for better decision making. Since the data connection is key to the success of the PoC in this case, the technical applicability of the selected process mining tool should be reviewed.


Scaling and benchmarking process performance

This requires a large process mining PoC project with data connections to multiple IT systems with analysis. The large project takes the medium project a bit further by potentially connecting to multiple data sources and executing further analysis of the process models. Perhaps regarding how the selected processes could be improved or how process efficiency compares to industry benchmarks.


It may seem like a daunting task connecting the data in multiple IT systems of your organization. Worry not, you can easily outsource the technical work, as process mining vendors can run data extractions with ready-made data connectors for you. 


2. Choose Correct Stakeholders for Your Process Mining PoC

The selection of stakeholders and participants is always vital to the success of a project. It is especially important in ensuring success for a process mining PoC, since end-to-end processes often involve multiple process owners, business owners, IT, finance, and process excellence stakeholders.


Project Sponsor

No projects can be executed without a budget or official mandate for resourcing. A project sponsor is a vital role, and in the case of a process mining PoC, typically someone who values data-driven decision making and knows the organization’s core drivers and future strategic roadmap.



As process mining is a data-driven methodology, the representation of IT in the process mining PoC is very important. However, there is a misunderstanding that since process mining involves an enormous amount of data, it would require a lot of time and efforts from IT for the extraction, transformation, and load (ETL) work. When in reality, the latest process mining solutions do the magic using data connectors without requiring any installations, IT system configurations, data table mappings, or difficult old-school server installations.


Business Representatives

The context for the process mining PoC should be determined and verified by the business in regards to how valuable process mining insights are for business operations. In other words, what information business currently lacks and how process mining can help to deliver more value with fewer efforts.


Analysts / Process Experts

They form the backbone of the process mining PoC. They typically have a good understanding of numbers and some underlying process-related methodologies, such as lean six sigma, RPA, or BPI, while questioning the past operational habits to improve core KPIs with 2+ digit figures. After the process mining PoC, these stakeholders often take ownership of developing the process mining capability within the organization and might provide it as a service or sprints for projects and programs executed in any parts of the company.


Project Manager

Finally, we need someone to keep the process mining PoC on track. When the process mining model is up and running for the first time, dozens of new opportunities will be immediately identified - how and where process mining could be applied within the organization. This is because companies haven’t harnessed process-related data logs before. New opportunities and application areas are excellent in showing the understanding of process mining, and they should be documented for the future roadmap to guarantee the success of the process mining PoC.


3. Execute the Process Mining PoC as Planned

After carefully planning the process mining PoC project, this part is just following the plan and enjoying the quick wins. Typically, in process mining PoCs, there is a basic training provided simultaneously about both the process mining tool and methodology. In our experience, customers often initiate the flexible SaaS subscription directly from process mining PoC test period, so the business has no cutoff times from enjoying the process mining benefits.

Typical activities in the execution part of a process mining PoC:

  • seeing the real as-is process (often for the first time ever)
  • hands-on analysis and findings
  • creating dashboards with process KPIs
  • identifying a happy process and getting benchmarks
  • calculating automation rates for RPA
  • root-causes findings for any process deviations and bottlenecks


4. Close the Process Mining PoC with Great Results

Finally, the process mining PoC project work should be well-documented, so the project scope and results can be easily communicated to the rest of the organization, especially if you would like to get more buy-in and scale process mining within your organization.

While you deserve to celebrate your process mining PoC success, you should also plan for the future of process mining in your organization. Some important dimensions to consider include:

  • finetuning the full process mining implementation roadmap based on the finding related to the IT landscape
  • setting responsibilities for next steps
  • designing effective process mining governance model

These dimensions ensure a successful and smooth transition from a process mining PoC to a continuous process mining model. A process mining PoC delivers great business value to organizations. You can achieve even greater benefits by having full process mining implementation with always up-to-date data records in your organization. With full implementation of process mining, an organization can measure the performance before and after a specific improvement or automation project. For example, you can leverage the data from deploying a RPA solution in a country, and then calculating how much could be saved by rolling out the same solution globally.


I hope you enjoyed reading these 4 simple steps to achieve a successful process mining PoC that delivers real business value. Check out my webinar where you can learn more tips and tricks in ensuring the success of a process mining PoC.

Connect with me on LinkedIn


Still unsure about how to plan your process mining PoC?

Get inspired by Nokia's process mining journey from proof of concept, proof of value, implementation, to benefits realization.



Fauzia Khan from Nokia also gave us an insight into how to use process mining to accelerate business results, track improvements, shortlist projects, and drive change management.

Let's dive in!

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Folders and Dashboards with QPR ProcessAnalyzer 2019.4

Operational Process Mining is done by monitoring real-time data with dashboards, alerts, and analyses. QPR ProcessAnalyzer 2019.4 introduces several features for managing and developing the growing amount of dashboards and analyses. With these features, it is easy to share business process findings with other team members and within the whole organization.

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What is Process Mining?

When people hear the words data mining, they nowadays have an idea of what it means. We often define data mining as a process of analyzing data from several perspectives and summarizing it into useful information. With support from this information, we can then make decisions that affect the success of a company. However, even when data mining is familiar to people, process mining still seems to be a new topic for many. Very often, I encounter questions like, “What is process mining? How does it work?”.

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Process Mining Clustering Analysis with QPR ProcessAnalyzer 2019.3

QPR ProcessAnalyzer 2019.3 introduces lightning-fast, easy-to-use, built-in Machine Learning and Artificial Intelligence based Clustering Analysis. Clustering is an unsupervised machine learning technique for finding similarities within process mining cases, in order to better understand the differences from process behavior and case attribute point-of-view, as well as detecting problems in process execution and source data quality. Other major improvements in 2019.3 include Calculated Case and Event Attributes to easily augment the process mining data, calculate KPI variables and enable further business relevant analysis. In QPR ProcessAnalyzer 2019.3, we also introduce enhanced grouping for ChartView.

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Easy-to-define KPIs with ChartView Filters in QPR ProcessAnalyzer 2019.2

QPR ProcessAnalyzer 2019.2 makes defining the Key Performance Indicators (KPIs) fun and easy with the new ChartView Filters functionality. Other major improvement include improved search for projects and models in QPR UI as well as the compatibility with Microsoft Excel 2019. And as icing on the cake we launch the new QPR ProcessAnalyzer Training Video Library with more than 20 training videos to help you become a process mining champion in a few hours!

Easy-to-define KPIs with ChartView Filters

With new ChartView 2019.2 everybody can make business relevant KPI measures and charts within minutes! Improvements include:

Multiple KPIs in the same chart with different right & left axis definitions. Picture below shows Case Count using left axis and median case duration using right axis:



ChartView Filters focusing the analysis to relevant cases and flows. The chart below shows 

  • Average Case Duration in days using left vertical Y axis.
  • Case start month on horizontal X axis
  • Purchase Order Cost as the bubble chart radius
  • Purchase Organization as the bubble chart series specifying the color or the bubbles

As the specific chart view filters we have used:

  • Case must start with Event Type PR Created
  • Case must make a flow from  PO Created to PO Changed [Value]
  • Case must belong to receiving plant AU1, GB1 or HK9


Well...how does this whole setup work? The great news is that this is all covered by the flexible QPR UI with a few clicks. This is the 3-component KPI Designer with settings for General, Measures and Dimensions. 



The new Filter settings are easily controlled with the additional Edit Filter functionality:

Quick search for Projects and Models

QPR ProcessAnalyzer is compatible with enterprise level process mining with advanced user administration, process mining model management and folders. In 2019.2 we added a new quick search for easily finding the relevant process model directly from the main analysis title bar. Key functionalities visible in the picture below contain:

  • Model name and active filter name visible in the title bar. Example below shows the model name "OrderToCash" and filter name "Main ProcessFlow".
  • Quick search - just type in a few letters contained in a project or model name and the list is filtered instantly
  • In-memory status and amount of cases shown in the list to help choosing the right model


In addition to providing a quick list of project and models for selection purposes the list gives easy access to model information with the (i) button on the right. It is possible to customize the info screen and by default it shows the information below:


Support for Microsoft Excel 2019

QPR ProcessAnalyzer is the only process mining tool in the market with native Microsoft Excel add-on client. This integration gives every business analyst the choice of extending their process mining analysis with familiar Microsoft Excel functionalities and delivering the enhanced results to others as Excel files, email attachments and Sharepoint sites. Supported Excel versions now include MS Excel 2019, 2016, 2013 and 2010. 

Icing on the cake: QPR ProcessAnalyzer Training Video Library

QPR ProcessAnalyzer Training Videos turn any process mining beginner to a process mining champion capable of conducting high-quality process analysis and findings with root causes. Example videos include:

Getting started: How to log in

Process Discovery: Flowchart analysis, Duration Analysis, Profiling Case Analysis, Event Type Analysis, Case Analysis, Event Analysis, Creating Filters

Process Analysis: Influence Analysis for Case Attributes, Influence Analysis for Flowchart, Conformance Analysis, Conformance Analysis with Model Autocreation, How to create a basic dashboard

Click here to access the training videos! :)



We are super excited about QPR ProcessAnalyzer 2019.2 and are eager to hear your comments!

Check out the recording of our release webinar to learn more!


Best regards,


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Find Root Causes for Conformance Deviations with QPR ProcessAnalyzer 2019.1

QPR ProcessAnalyzer 2019.1 takes you to the new year 2019 by integrating QPR's game-changing Root Cause functionality with Conformance Analytics.

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Process Mining Benchmarking with QPR ProcessAnalyzer 2018.7

QPR ProcessAnalyzer 2018.7 brings new features for benchmarking, model management and analytics. To see what the new features and improvements look like in practice, check out our release webinar here or below for a brief overview:

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