Process Mining Maturity Model

Process Mining Maturity Model as an Analytic Capability

Alpha Version (α-P3M)

Process mining is vital in enabling data-driven analysis in BPM. BPM allows process owners to visualize business flows and analyze business process performance. Process flows can be used to analyze operations according to business strategy, improve processes, assess business process performance, and identify obstacles that interfere with business efficiency.

With the rapid advancement of process mining technology in various fields, there is also a significant opportunity for AI infusion in process mining to reduce costs or provide a better user experience[1]. When applying process mining, various challenges will be faced from a management standpoint, including the readiness of the organization to start or accept the new challenge. Assessing this readiness requires methods and tools to evaluate an organization’s capability and guide the change management plan to improve process mining implementation as analytic capability. In short, the notion of a ”maturity model” fit the organization's needs in this context. A maturity model will represent the progressions in a particular focus area and the required steps to increase an organization’s capabilities in such a focus area.

Maturity Model

Maturity is a measurement of the ability of an organization for continuous improvement in a particular discipline (as defined in O-ISM3)[2].The higher the maturity, the higher will be the chances that incidents or errors will lead to improvements either in the quality or in the use of the resources of the discipline as implemented by the organization.

Two approaches for implementing maturity models exist. With a top-down approach, such as proposed by Becker et al.[3], or bottom-up approach, such as suggested by Lahrmann et al.[4].

Maturity Model in Process Mining as an Analytic Capability

This maturity model's purpose is to evaluate the performance of company in using process mining as an analytic capability. The model consists of 7 dimensions (see Figure 1) capturing management aspects and 3 capturing the Information Technology aspects. To make visualization easier, blue shades will represent the dimensions of the management side, and orange shades will represent the dimensions of the IT side.

Besides the dimensions, the model considers sub-dimension capabilities (see Table 1). Each sub-dimensional capability is associated with a level of implementation maturity. Six dimensions use the 5 maturity levels represented in the Capability Maturity Model Integration (CMMI). Based on our preliminary study, one dimension (Technology) uses 4 levels defined specifically based on the process mining academic literature.

Technology Dimension

Assess the information capability and analytic process in process mining

Data Dimension

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

Pipeline Dimension

Assess the state of PM 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.

Strategic Alignment Dimension

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

Governance Dimension

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

Culture Dimension

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

People Dimension

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

References

[1] S. T. Jan, V. Ishakian, V. Muthusamy, Ai trust in business processes: the need for process-aware explanations, in Proceedings of the AAAI Conference on Artificial Intelligence, volume 34, 2020, pp. 13403–13404.

[2]Aceituno, Vicente. "Open Information Security Maturity Model". Retrieved 12 February 2017.

[3] Becker, J., Knackstedt, R., Pöppelbuß, J. (2009) Developing Maturity Models for IT Management – A Procedure Model and its Application. Business & Information Systems Engineering 1(3), 213-222

[4] Lahrmann G, Marx F, Mettler T, Winter R, Wortmann F (2011). "Inductive Design of Maturity Models: Applying the Rasch Algorithm for Design Science Research". Service-Oriented Perspectives in Design Science Research. Lecture Notes in Computer Science. Vol. 6629. Springer. pp. 176–191. doi:10.1007/978-3-642-20633-7_13. ISBN 978-3-642-20632-0.

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