This type of feedback concerned mainly issues with several acronyms used in the level definitions, such as SOP (Standard Operational Procedure) and PDCA (Plan-Do-Check-Action), which were not spelled out in the interview materials. One concern raised by several experts was the definition of the levels in the Consistency sub-dimension of Culture. This dimension focuses on the extent to which the organizational culture is seen as being consistent regarding PM practices. At least two experts asked the interviewer to clarify the meaning of this dimension, and both agreed that, after the provided explanation, the meaning of the sub-dimension was clear. Hence, we decided to improve the wording of this sub-dimension in β-P3M, without changing its meaning.

• Code. Tooling in the Pipeline dimension.

Action taken. Remove any reference to ad-hoc and commercial tools in the definition of maturity levels. Focus the level definitions on PM functionality only.

• Code. Management involvement in the Culture dimension

Action taken. Rephrase the levels of the culture sub-dimension to consider also the operational management support.

• Code. Business contribution in the Strategic Alignment dimension.

Action taken. We clearly separated business contributions and budgeting in the definition of the levels. Business contributions evaluate the organisational improvement achieved through PM, while Bugdeting concerns only the issue of allocating financial resources for the execution of PM activities.

• Code. Responsibility in the People dimension.

Action taken. The issue of the responsibility of the PM initiatives was renamed Ownership and moved to the definition of the levels of the Governance dimension.

• Code. Include Deployment in the Pipeline dimension.

Action taken. Conceptually, the deployment of PM techniques is already included in the sub-dimension Integration with Operational Application of the Pipeline dimension. This sub-dimension focuses explicitly on the level of integration between PM functionality and operational support in business process execution. In β-P3M, the levels of this sub-dimensions have been updated to include explicit references to the deployment of PM insights.

• Code. Analytic Process sub-dimension in the Technology dimension.

Action taken. We removed the Analytic Process sub-dimension from α-P3M and integrated into its content into the definition of the levels of the Information Capability sub-dimension.

• Code. Data Explainability in the Data dimension.

Action taken. We added a new sub-dimension about Data Explainability to the Data dimension. The levels in this dimension track the extent to which an explanation of the data in input to PM is available to PM users.

• Code. Ownership in the Governance dimension.

Action taken. We added a new sub-dimension about Ownership to the Governance dimension. This sub-dimension captures the ownership of all the aspects of PM initiatives, including the data that are used as input for PM analyses.

• Code. Data Privacy in the Data dimension.

Action taken. We clarified in the model that the Data Security sub-dimension concerns only the way in which event data for PM and insights generated buy PM are stored. At the same time, we created a Data Privacy sub-dimension to consider all the issues related with the privacy of event data for PM and insights obtain from PM analyses.

Assess the information capability in process mining 

Information Capability : Information capability in process mining refers to the ability to gather and analyze data from various sources in order to gain insights into a business process. The different levels of process mining analysis - descriptive, diagnostic, predictive, and prescriptive - each represent a different level of information capability 

Assess the state and availability of data for process mining as an analytic capability as well as the associated data security, privacy, and data quality policies and standards 

Data Availability: Data availability in process mining refers to the accessibility and reliability of the data that is used to analyze business processes. Process mining relies on data from various sources, such as event logs, databases, and other IT systems, to discover and analyze process patterns and performance indicators. High data availability means that the necessary data is readily accessible and in a format that can be analyzed efficiently. This includes having the required data attributes captured consistently and accurately. In contrast, low data availability can result in incomplete or inaccurate analysis, making it difficult to gain insights into the process.

Data Security: Data security in process mining refers to the measures taken to protect sensitive or confidential information from unauthorized access, modification, or disclosure during the process mining process. 

Data Quality: Data quality in process mining refers to the degree to which the data used for process mining accurately reflects the actual processes being analyzed. High-quality data is essential for effective process mining because inaccurate, incomplete, or inconsistent data can lead to incorrect process analysis and suboptimal process improvements 

Data Explainability: Data explainability refers to the ability to understand the data type meaning and how each variable impacts the process is critical for ensuring that the data is complete and accurate and for explaining the process mining results to stakeholders 

Data Privacy: Data privacy in process mining refers to the protection of sensitive or confidential information during the process of analyzing large volumes of data to identify and improve business processes. this data may contain sensitive or confidential information, such as personally identifiable information (PII) or financial data, that must be protected to comply with data privacy regulations and prevent data breaches. 

Assess the state of Process Mining workflow automated (from data gathering to their analysis and diffusion of the results) and how the data are gathered to be integrated and transformed into an event log that can be used for the workflow.  

Tooling : Tooling in the context of pipeline for process mining used to design, execute, and manage the various stages of the process mining pipeline. The process mining pipeline typically consists of several stages, including data collection, data preprocessing, data analysis, visualization, and reporting. Each stage of the pipeline requires specific tools and techniques to be applied to the data, and tooling is required to automate and streamline these activities.

Integration with Data Source : Integration with data sources for process mining refers to the process of connecting to various data sources and collecting data from them for process mining purposes. 

Integration with Operational Application: integration with operational applications in the context of pipeline workflow for process mining involves connecting the process mining results and insights to the operational systems and applications that run the business processes. This integration enables the operational applications to leverage the process mining insights to improve process efficiency and effectiveness, including the deployment of AI models to automate or optimize the identified process areas. 

Assess the strategy that examines the plan of action and roadmap support of process mining as an analytic capability 

Strategy : Strategy measurement in the strategic alignment dimension of process mining refers to the process of measuring the degree to which operational processes are aligned with the strategic objectives of an organization. 

Budgeting: It refers to the process of measuring the effectiveness of an organization's budgeting process in supporting its strategic objectives. The budgeting process involves the preparation, allocation, and management of financial resources to support the achievement of an organization's strategic objectives. The effectiveness of the budgeting process depends on how well it aligns with the strategic objectives and how efficiently it is executed. 

Business Contribution: It refers to the process of measuring the effectiveness of an organization's business contribution to achieving its strategic objectives. The business contribution process involves the alignment of business activities with strategic objectives, the identification and execution of value-creating initiatives, and the monitoring of performance against strategic goals 

Assess how an organization sets the formal rules and structures, including their documentation, regarding process mining as an analytical capability  

Communication : It refers to the process of measuring the effectiveness of an organization's communication practices in supporting its process mining initiatives. The communication process in process mining involves the dissemination of process mining insights and results to stakeholders, such as executives, process owners, and analysts. 

Quality Metric: It refers to the process of measuring the effectiveness of an organization's metrics in supporting its process mining initiatives. This measurement is concerned with assessing the quality of the metrics used to measure process performance and the effectiveness of the process for implementing and updating these metrics. 

Documentation System and Compliance Check: It refers to the process of measuring the effectiveness of an organization's document compliance and check process in supporting its process mining initiatives. This measurement is concerned with assessing the organization's ability to maintain accurate and up-to-date process documentation and to conduct regular compliance checks to ensure that the process documentation is complete and correct. 

Ownership: It refers to the process of measuring the effectiveness of an organization's ownership structure in supporting its process mining initiatives. This measurement is concerned with assessing the organization's ability to establish clear roles and responsibilities for process ownership, and to ensure that process owners are effectively managing and improving their processes. 

Assess the collective values shaping the attitude and behavior when human resources use process mining as analytical capability in their job 

Use Case Availability : It refers to the process of measuring the availability and accessibility of process mining use cases within an organization. This measurement is concerned with assessing the organization's ability to share and promote the use of process mining for process improvement and decision-making. 

Management Involvement: It refers to the process of measuring the level of involvement of top and operational management in the organization's process mining initiatives. This measurement is concerned with assessing the extent to which management supports and drives process mining initiatives and is actively involved in process improvement efforts. 

Adaptability: It refers to the ability of an organization to adapt its processes and operations to changing customer needs and market conditions. This measurement is concerned with assessing the extent to which the organization is customer-oriented and is able to respond quickly and effectively to changing customer needs and market demands. 

Consistency: refers to the degree to which an organization is able to maintain consistent processes and practices over time, even in the face of change. This measurement is concerned with assessing the organization's ability to manage change and to maintain process consistency and quality throughout the change process. 

Assess how the human resources are managed in the organization to support process mining as an analytic capability 

Skill : refers to the degree to which an organization has the necessary skills and knowledge to support process mining initiatives. This measurement is concerned with assessing the organization's ability to transfer skills and knowledge related to process mining to its employees, both in terms of core knowledge and tacit knowledge. Core knowledge refers to the formal knowledge areas that employees need to have in order to support process mining initiatives, such as data analysis, statistics, process modeling, process optimization or AI. Tacit knowledge, on the other hand, refers to the informal knowledge that employees gain through experience and interaction with others, such as understanding the nuances of particular processes or how to effectively communicate findings to stakeholders.

Responsibility:refers to the degree to which an organization has established clear roles and responsibilities for process mining initiatives. This measurement is concerned with assessing the organization's ability to create a reliable and consistent structure for process mining that can be sustained over time. 

From our measurements, our maturity model can visualize two company measurements as shown in Figure 2. This measurement is based on six dimensions that have five levels, as for technology, it was shown in Figure 3.