2023 Process Mining Market Is Booming Across the Globe: Size, Share, Forecasts, & Trends Analysis 2028

This research report categorizes the process mining market based on offering, mining algorithms, data source, vertical, and region

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Northbrook, IL 60062 -- (SBWire) -- 10/30/2023 --The global Process Mining Market size is set to experience rapid growth, projected to surge from USD 1.8 billion in 2023 to USD 12.1 billion by 2028, at a CAGR of 45.6% during the forecast period of 2023–2028, according to research report by MarketsandMarkets™.

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500 - Tables
70 - Figures
450 – Pages

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This remarkable expansion is driven by a confluence of factors. First and foremost, As businesses grow and expand, their processes become more complex and interconnected. This can make it difficult to understand and manage these processes effectively. Moreover, businesses are adopting digital transformation initiatives to improve their efficiency, agility, and customer experience. Additionally, businesses need to have visibility into and control over their processes in order to operate efficiently and effectively. Process mining can help businesses to gain real-time visibility into their processes, identify bottlenecks and inefficiencies, and take corrective action. In this dynamic landscape, process mining is poised to revolutionize the industry, providing agility, efficiency, and innovation on an unprecedented scale.

By offering, continuous monitoring & analytics tools software segment to register the largest market share during the forecast period

Continuous monitoring tools offer real-time insights into business processes, allowing organizations to make immediate and informed decisions. These tools are driven by the need for enhanced operational efficiency and data-driven decision-making. Key trends include integration with robotic process automation (RPA) and organizations demanding transparency and interpretability in AI-driven insights, ensuring that decision-makers can understand and trust the recommendations provided by process mining tools.

By mining algorithms, deep learning algorithms segment is poised for the fastest growth rate during the forecast period

Deep learning algorithms is a rapidly evolving segment within the process mining market, addressing the need for handling complex and large data. It's driven by the need to handle large volumes of data from diverse sources, including unstructured data such as event logs. Moreover, trends like improved accuracy and prediction and integration with advanced technologies, are reshaping the process mining landscape. Deep learning algorithm's ability to model complex structures makes it well-suited for uncovering hidden insights and nuances in processes.

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By region, North America to account for highest growth rate during forecast period

The North America process mining market is witnessing remarkable growth, fueled by several key drivers and trends. The region's enterprises are keen on adopting technologies that enhance operational efficiency and agility, and process mining aligns well with these objectives. Moreover, the region's propensity for fostering strategic partnerships and collaborations between technology providers, consulting firms, and enterprises creates an ecosystem conducive to the growth of process mining.

Some major players in the process mining market include IBM (US), ABBYY (US), Celonis (US), UiPath (US), Software AG (Germany), SAP Signavio (Germany), Pegasystems (US), QPR Software (Finland), Microsoft (US), and Appian (US).

Key Dynamic Factors For Process Mining Market:

Increasing Adoption of Process Automation: As companies look to cut expenses and simplify operations, process automation is becoming more and more popular. Process mining is a useful tool in process automation initiatives since it is frequently used to find bottlenecks and inefficiencies.

Digital Transformation: Organisations that implement digital transformation initiatives produce enormous volumes of data about their internal operations. Organisations can use process mining to make sense of this data, find patterns, and enhance operations.

Risk management and regulatory compliance: Requirements for compliance and regulations are always changing. Process mining, which offers a comprehensive perspective of an organization's processes and highlights areas of concern, can assist organisations in managing risks and ensuring compliance with regulations.

Integration of Business Process Management (BPM): A lot of companies are incorporating process mining into their BPM programmes. BPM becomes more data-driven and effective thanks to this integration, which enables real-time business process monitoring, analysis, and optimisation.

Integration of AI and Machine Learning: Process mining tools become more powerful when AI and Machine Learning are integrated into them. AI can be used to spot abnormalities, forecast process bottlenecks, and provide optimisation techniques.

Cloud-Based Solutions: Process mining solutions that are hosted on the cloud are becoming more and more popular. Because they are accessible, scalable, and flexible, cloud-based solutions are appealing to companies of all kinds.

Emerging Technologies: New technologies are proliferating, such as IoT and blockchain. In order to ensure efficiency and dependability, processes using these technologies can be analysed and optimised via process mining.

Competitive and Segmentation Analysis:

The increasing need for data-driven process optimisation solutions has led to fierce rivalry in the process mining industry over the years. Well-known companies that provide extensive process mining and analytics platforms, such Celonis, UiPath, Signavio, and Software AG, have dominated this market. In order to provide their clients end-to-end solutions, these businesses have broadened their product offerings to incorporate a variety of related technologies like business process management (BPM) and robotic process automation (RPA). They have also been making significant investments in R&D to improve their products, integrating machine learning and artificial intelligence to deliver predictive insights.

Organisation Size: From small and medium-sized businesses (SMEs) to major corporations, all sizes of organisations use process mining solutions. Due to their affordability, cloud-based solutions are frequently chosen by SMEs, but large companies could prefer on-premises solutions for better data protection and control.

Deployment Mode: On-premises, cloud, and hybrid deployments are among the modes of operation for process mining solutions. The organization's IT infrastructure, data security guidelines, and scalability needs all influence the deployment option.

Industry Vertical: The requirements for process mining vary depending on the industry. Process mining has become increasingly popular in the manufacturing, healthcare, finance, and logistics sectors. To meet the unique needs and rules of various areas, industry-specific solutions have been developed.

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