Process mining continues to mature from a technological perspective. However, despite the increasing number of process mining solutions and services, some barriers still remain to its full adoption in business practice. Like any other technology, process mining relies on efective usage by users to add value. One of the factors afecting the adoption by users and the use of process mining is that users cannot understand and translate process mining outputs into valuable insights. Our hypothesis is that interpretation and explainability are crucial to give users a sense of understanding and actionability. This doctoral project aims to define explainability and interpretability in process mining, investigate diferent factors afecting them and, furthermore, design solutions for improvement. The project follows a mix of empirical and technical approaches. As a pilot study survey-based interviews with PM business users were conducted confirming the relevance of the topic.
Process mining (PM) is a technology that uses event logs from IT systems and applications to reconstruct,
visualize, analyze and improve business processes [
Both the increase in solutions and consultancy seem to be indicative of the demand for PM among
companies within the industry. At the same time, adoption by end users still appears to be an issue.
There are more companies that either already had some experience with PM solution(s) and decided not
to continue with it [
PP1: General PM eXplainability (XPM) - I do not always understand what exactly am I
seeing. PM outcomes can be presented in diferent ways and, depending on the PM solution, may
include process-focused visualizations such as process maps and/or set of diferent visual components
as dashboards. However, users who are not experts in PM may experience reading these visuals and
understanding exactly what is displayed as "overwhelming" and non-trivial[
PP2: General PM iNterpretability (NPM) - It is challenging to understand what should I
do with what I see. Once users understand what they see, e.g. how to read a process map and/or
dashboard, the next step is to interpret what they see and translate it into valuable insights. Depending
on the project setting, diferent approaches and techniques can be used to analyze PM results, for
example exploratory and/or confirmatory approach[
PP3: PM without Process Focus - I miss Process Mining in all this. Because of PP1 and PP2, PM developers may try to avoid complex output and simplify analyses to improve NPM. In some cases, this can lead to better operational use, for example, when a non-expert user is given only a short list of tasks to focus on. However, it can also lead to using PM without a process focus or with a focus only on local questions within the complex end-to-end view, similar to Business Intelligence (BI) tools. The question then arises as to whether such simplification helps to improve XPM and NPM, or whether it risks that actual complex problems remain unsolved.
To investigate pain points mentioned in the previous section, we have formulated the following research questions.
RQ1: How can XPM and NPM be defined for certain stages of the PM journey for certain
user groups? PP1 and PP2 are related to how to explain and interpret PM outputs. Interpretability and
explainability are beneficial to instill feelings of understanding within the system’s users. There are
numerous generic explainability and interpretability definitions [
RQ2: What are the main factors that can drive XPM and NPM within the certain phases of PM journey for certain user groups? There are many diferent drivers that can somehow afect both XPM and NPM. For example, educational aspects and PM experience of individual level during the initial PM phases (e.g. requirements gathering) or choices of visual components by the PM analyst during the technical development phases (e.g. dashboard building) of technological level.
RQ3: How can XPM and NPM be improved for certain PM stages and user groups for more
eficient and insightful use of PM outputs? There are some existing methods and tools proposed by
PM vendors or in the recent research [
We adopt a mixed methodology, combining qualitative and quantitative approaches. To address the research questions, we plan to use the four main phases shown in Figure 1.
To start with definitions (RQ1), we selected the initial scope. We will focus on three main user
groups - business users, analysts, developers. We target planning, requirements and data collection,
data processing and transformation, mining and analysis, evaluation, and process improvement and
support as the most important high-level PM phases [
Once possible definitions per certain stages and certain user groups are clarified (RQ1), we plan to
investigate drivers (RQ2) that can influence both XPM and NPM. For now, we have grouped these
drivers into four categories. The categorization is preliminary and partially based on
TechnologyOrganization-Environmental (TOE) framework [
develop solution Solution and development
methods can vary per specific driver (e.g., new visual can be proposed or framework designed) - Technological - tooling and software (source systems, ETL solutions), visual components within those systems, programming languages and developed algorithms, etc.
After clarifying the definitions (RQ1) and potential drivers (RQ2), we aim to review, assess and
prioritize them with the aim of identifying the drivers with the greatest business impact based on
potential value. For two-three of the most impact drivers, we plan to review available solutions and
evaluate them. Next, we intent to design improved solutions (RQ3) adopting a Design Science Research
(DSR) approach [
As preliminary research to answer RQ1, we conducted survey-based interviews. During the pilot interviews, we asked several process mining experts and 20 PM business users what do they understand by explainability and interpretability within process mining. When asking the questions ‘How would you define explainability in Process Mining?’ and ‘How would you define interpretability in Process Mining?, we obtained the following results: • Some respondents answered that they think explainability and interpretability are very important topics, but that they also find it dificult to answer one or both questions and propose a definition in a ‘constructive’ way. • Others shared that explainability and interpretability are the same and that there is no diference in a definition, meaning they are interchangeable. • In contrast, some emphasised the diference and even highlighted that one or the other is more important (e.g. that without explainability, there is no understandability and consequently no need for interpretability).
Initial results show that participants find XPM and NPM very important topic. However, some of them find it challenging to formulate clear definitions.