Process Mining as a Service (PROMaaS): Benefits & Challenges [2024]

Updated on Jan 3

3 min read

Table of contents

What is process mining as a service?What are the benefits of process mining as a service?What is the difference between implementing process mining on-premise and as a service?What are the challenges of process mining as a service?Further Reading

In a survey, 61% of businesses stated that they consider process mining beneficial since they can use factual process data to identify bottlenecks and optimize their processes. Despite its benefits, process mining is challenging to implement due to limited process mining tooling or expertise (52%) and complex IT landscape (30%). However, such limitations can be tackled with process mining as a service solutions.

In this article, we explore process mining as a service, benefits, challenges, and comparison with on-premise process mining implementation.

What is process mining as a service?

Process mining as a service (PROMaaS) refers to the outsourcing of process mining by hiring service providers to discover and monitor business processes. PROMaaS allows businesses to use process mining without additional cost of building a process mining CoE.

PROMaaS is a new terminology which is used by consultancy companies (e.g. PwC and Coberg) and some process mining vendors (e.g. IBM). By referring to the delivery of processes through the cloud, consultants and vendors aim to position their offerings as a new market category. Yet, the term is not yet clearly defined. Therefore, in this article, PROMaaS is not evaluated as a new category but rather an equivalent word for process mining outsourcing efforts.

What are the benefits of process mining as a service?

Some of the advantages of process mining as a service includes:

Cost reduction:
- By implementing process mining on the cloud, businesses can avoid the infrastructure cost and other associated implementation and IT costs.
- Companies can also avoid licensing costs since it is included in the costs of the service.
- They will not be in need of hiring process mining experts to apply and maintain process mining
Fast deployment:
- Since there is no need to hire experts and install the tool on premise, the adoption of process mining can be faster.

What is the difference between implementing process mining on-premise and as a service?

Some of differences between PROMaas and process mining on-premise include:

	PROMaas	On-premise
Deployment	On the service providers' hardware (workstation, 64-bit operating system, server configuration)	Businesses rent or buy the hardware to employ
Access	Providers can access with any device from any location	Only businesses can access via their hardware, via VPN access
Maintenance and updates	Providers are responsible for updates and maintenance	Businesses are responsible for maintenance and updates of software and hardware
Costs	All used software, environment and maintenance are included in a yearly license	Costs for hardware, running costs for maintenance, electricity, and expert employees
Security	Data security is the PROMaaS providers' responsibility	Businesses have to fulfill the security requirements and standards

What are the challenges of process mining as a service?

PROMaaS can be challenging because of:

Data privacy: To benefit from PROMaaS, businesses have to share their data that contains information about employees, clients and entire business with a third-party. Yet, companies can overcome this issue by addressing permissions and credentials through privacy enhancing technologies.
Cloud migration: To employ process mining as a service, businesses are required to complete their data migration and cloud adoption. Businesses may postpone their cloud migration due to high costs and the lack of skills required to execute the migration. Some companies provide cloud solutions that include process mining in the solution package that help companies to overcome the challenge of cloud integration.

Hazal is an industry analyst in AIMultiple. She is experienced in market research, quantitative research and data analytics. She received her master’s degree in Social Sciences from the University of Carlos III of Madrid and her bachelor’s degree in International Relations from Bilkent University.