Over the past few decades, process mining has emerged as a crucial and powerful approach for businesses to optimize their operations, bringing a novel data-driven perspective to business process management.
By transforming event logs into meaningful insights, process mining allows organizations to uncover efficiencies, streamline workflows, leading to faster and informed decisions that enhance business performance.
Today, with the rapid rise of artificial intelligence (AI) and more specifically generative AI hitting the enterprise application landscape from every angle, the potential of process mining is about to reach a new level. Process mining will experience a profound boost in terms of productivity, dimensions covered and access to stakeholders thanks to the wide range of benefits brought by this AI wave.
This blog post will explore how generative AI is reshaping the field of process mining and what it means for businesses looking to gain a competitive edge. Generative AI, with its ability to analyze vast amounts of data and learn from it to identify patterns, is fundamentally changing the way businesses approach process mining disciplines.
Let’s see more in detail how generative AI is reshaping the world of process mining:
- Lower the barrier to this expert field – The accessibility of insights to non-experts has always been a challenge of process mining. Generative AI can empower different stakeholders, including non-technical business users, to obtain valuable knowledge that can inform decisions by using a conversational approach. With the introduction of co-pilot capabilities, performing certain process mining tasks, such as creating process queries or dashboards, can become significantly easier and faster.
- Unlocking insights with unstructured data: Traditionally, process mining has focused on structured data sources such as transactional logs. However, much of the valuable information from businesses is unstructured. This is where AI can make a huge difference. By leveraging AI and ML, organizations could turn unstructured data, such as images and texts, into structured information that can be used to generate newer and deeper insights. Think about customers' comments on feedback platforms and how these could feed the analysis of customer satisfaction rates, helping spot trends that may otherwise go unnoticed. Also, AI can help structure information contained into pictures or PDF formats, as well as data from desktop applications including Excel files, company reports, risk frameworks, etc. This becomes a new source of contextual knowledge for process mining which complements the information that can be derived out of operational systems execution.
- Faster problem resolution: Generative AI has the potential to speed up data analysis, as well as recognize patterns and deviations from standards or best practices that can cause process delays or issues. It will also help analyze the root causes of low performance to support decisions on how to improve. Organizations will be far more responsive to disruptions but also able to prevent them before they arise. A predictive and proactive approach to problem resolution is facilitated by AI.
- Produce recommendations and tangible value realization: the outcomes of process mining, such as the identification of non-compliant variants, often remain there without appropriate corrective actions being taken. Given a certain issue that has been unveiled with process mining, generative AI technologies can play a significant role by to producing recommendations based on best practices, helping users turn insights into actions and producing tangible value for the company.
- Streamlined data cleaning, formatting, and preparation: Preparing data for analysis has traditionally been a time-intensive process. Before diving into process mining, organizations spend time cleaning and formatting their data. Generative AI has the potential to automate these tasks, making it faster to identify errors and discrepancies and turn data into the right format for analysis. This could lead to greater data readiness for process mining, speeding up the time to insights and, therefore, the benefits that companies can realize from their process mining programs and efforts.
While the potential of generative AI in process mining is enormous, the technology is still maturing. Human creativity and strategic thinking, which are essential to every organization, not only retain their importance but also become even more crucial. Generative AI acts as a catalyst of human potential, allowing people to leverage its capabilities.
To learn more about how SAP Signavio is evolving its process mining capabilities to integrate generative AI, visit our process AI page. Also, read more about SAP’s co-pilot Joule and stay tuned for the start of the SAP Signavio Early Adopter Care program in early November to be one of the first active users of Joule in SAP Signavio.