According to the latest Forrester report, process intelligence software has been increasingly included in automation and BPM platforms over the last three years.1 On the other hand, the market is complex and confusing for business leaders with numerous vendors involved, prolonging software adoption.
Therefore, we provide a detailed guide explaining process intelligence software categories and the top vendors for each category.
What is process intelligence software?
Process intelligence is a technology used to analyze, visualize, and optimize business processes within an organization. These solutions are employed in process improvement initiatives to ensure positive business outcomes, enhance customer experience or maintain quality standards.
Process intelligence solutions include various tools and software categorized under 5 categories. These tools can be utilized individually or in combination to address the organizations’ unique needs for digital transformation, process analysis and automation.
1.) Process Mining
Process mining focuses on discovering, monitoring, and analyzing real processes by leveraging event logs and data. The main process mining functionalities are event log analysis, process discovery, process conformance checking, root cause analysis, and performance monitoring.
Process mining solutions can be applied to identify bottlenecks and process inefficiencies in purchasing and sourcing process (P2P) or order to cash, discover process variants, optimize workflows, monitor compliance, and improve operational efficiency.
Explore process mining benefits and how to use it in your process improvement efforts by reading:
- 20+ Process Mining Statistics: Market Size & Adoption
- Top 40+ Process Mining Use Cases/ Applications
- 10+ Process Mining Benefits
Compare top process mining tools in detail by checking out our comprehensive articles:
- Analysis of Process Mining Market & Best Software
- Top Free Trial and Open Source Process Mining Tools
- Process Mining Software Comparison
Check out comprehensive and constantly updated list of process mining case studies to find out more process mining real-life examples.
2.) Task Mining
Task mining tools capture and analyze user interactions with software applications and systems to understand tasks’ performance. They provide insights into user behavior and work patterns through user activity monitoring, task analysis, process recording, and user journey mapping.
Task mining can identify manual workarounds, enhance user interfaces, and improve software usability. Process mining vendors provide task mining capabilities as a part of their platform.
Discover more on task mining:
3.) Digital Twin of an Organization (DTO)
DTO is a part of digital twins technology that can create digital replicas or simulations of an organization’s processes, assets, and operations. DTOs provide a holistic view of an organization’s activities.
DTO software applications include process modeling, process simulation, real-time monitoring, and predictive analytics to plan scenarios, optimize processes, assess risk, and forecast performance.
Process mining tools include DTO as an additional process simulation capability in their platforms.
4.) RPA platforms with PM capabilities
RPA tools are designed to automate repetitive and rule-based tasks within business processes through software robots or bots. These bots mimic the actions of human users when interacting with digital systems and applications. RPA software automates repetitive tasks, increases efficiency, and reduce errors to streamline business operations.
RPA tools may offer process intelligence tools to identify and prioritize processes to automate. Some vendors, like Automation Anywhere’s Automation Success Platform, include these APD, DTO or task mining capabilities on their platforms while some others (e.g UiPath and IBM) develop process mining software that can be deployed alone.
Read more on RPA and process intelligence:
- 4-Step Guide For RPA Deployment with Process Mining
- 3 Steps to Implement RPA with Robotic Process Mining.
5.) Automated process discovery
Automated process discovery is a technique to identify and map out business processes automatically, using machine learning and AI techniques. Automated process discovery can streamline documentation, understand undocumented processes, and increase process visibility.
Automated process discovery tools include process discovery, data extraction and pattern recognition features. Automated process discovery is often included in process mining architecture as one of the three main components. Some BPA and RPA vendors also include the tool as a part of their platform.
Check out to learn more on APD:
5.) Process mapping and modeling
Process modeling and mapping tools enable organizations to create visual representations of their processes, including flowcharts, diagrams, and diagrams. Process modeling tools and techniques may include features like visual process design, diagram creation, and documentation.
Process mapping can facilitate communicating process flows and process analysis. Process mining and BPM tools include process mapping and modeling techniques as well.
These categories are inter-related and most vendors offer multiple capabilities under a single platform. AIMultiple categorized products according to vendor claims and mapped each product to a single process intelligence category.
AIMultiple’s process intelligence vendor shortlist
Once companies have defined the specific aspect of process intelligence they wish to focus on, they face the task of evaluating multiple vendors to find the most suitable tool. However, the abundance of market players complicates this assessment.
Hence, we have narrowed down our selection to prominent contenders using three key criteria:
- LinkedIn Employee Count: We have considered vendors with more than 10 employees listed on LinkedIn. Smaller vendors may struggle to support larger enterprises effectively.
- Review Presence: The absence of feedback could indicate a limited adoption rate. Therefore, we excluded the vendors that lack reviews on selected review platforms (See Figure 1).
- External Validation: Our assessment also takes into account evaluations from reputable sources, such as Forrester, to gauge the vendor’s standing in the market.2
How does process intelligence work?
The tools listed above are similar in terms of the way they all operate, which includes the following steps:
The first step is collecting data from various data sources, such as logs, databases, and event records. This data often includes timestamps, user interactions, and other relevant information. Some tools, like process mining, can extract real-time data, while others, like process mapping tools, can utilize historical data.
As the second step, the software automatically discovers and maps out process flow. This way, it helps visually represent how tasks are performed, including deviations and exceptions.
- Visualizations: These tools use various visualization techniques, such as process maps, flowcharts, and diagrams, to present process data in a comprehensible and user-friendly manner. These visualizations make it easier to identify bottlenecks, deviations, and areas for improvement.
- Process analysis: The software employs algorithms and analytical techniques to analyze process data. This intelligent process analytics helps discover patterns, trends, and anomalies in how processes are executed, allowing analysts to understand the underlying dynamics of business operations, point out intelligent automation opportunities and boost operational efficiencies.
- Predictive Analysis: Some advanced process intelligence tools incorporate predictive analytics to forecast future process performance based on historical data. This enables organizations to address issues and make data-driven decisions proactively.
These tools help organizations reduce costs and enhance overall performance by identifying inefficiencies and areas for improvement through
- Performance metrics: Process intelligence software provides key performance indicators (KPIs) and metrics to assess process efficiency and effectiveness. This includes metrics like cycle time, throughput, and resource utilization.
- Compliance and audit trail: It can assist organizations in ensuring compliance with regulatory requirements by tracking and auditing process execution. This is especially valuable in industries with strict compliance standards, such as healthcare and finance.
What are the key benefits of process intelligence tools?
Process intelligence tools offer numerous benefits to organizations:
1. Process Visibility: These tools provide a clear view of how processes are executed, enhancing operational transparency.
2. Data-Driven Insights: Analyzing large process data volumes empowers data-driven decision-making, revealing hidden patterns and inefficiencies.
3. Boosting Efficiency: By identifying bottlenecks and inefficiencies, organizations can streamline processes, reducing cycle times.
4. Cost Reduction: Optimized processes often lead to cost savings through the elimination of unnecessary steps and resource overuse.
5. Quality Improvement: Process intelligence identifies deviations, enhancing product or service quality through corrective actions.
6. Compliance: In regulated industries, these solutions ensure compliance by tracking and auditing process execution.
7. Enhanced Customer Satisfaction: Optimized processes result in better customer experiences, increasing satisfaction and loyalty.
8. Continuous Improvement: Valuable for ongoing monitoring and refining of processes to adapt to changing conditions.
9. Resource Allocation: Informed resource decisions are made through resource utilization analysis.
10. Cross-Functional Collaboration: Facilitates collaboration among departments to improve end-to-end processes.
11. Faster Decision-Making: Real-time insights enable faster decision-making in today’s rapidly changing business environment.
12. ROI: Significant ROI is realized through cost savings, increased revenue, and improved operational performance.
13. Competitive Advantage: Effective use of process intelligence provides a competitive edge in agility and efficiency.
14. Risk Mitigation: Identifying and addressing deviations helps mitigate operational risks, compliance issues, and customer dissatisfaction.
How to choose a process intelligence tool
In the quest for the most suitable process intelligence software for your organization, weighing several critical factors is essential. These considerations can significantly influence your choice:
1. Comprehensive Analytics and Reporting Capabilities:
To fully harness the potential of process intelligence, prioritize solutions offering robust data analysis, real-time reporting, and customizable reporting options. These features empower data-driven decision-making.
2. User-Friendly Interface and Accessibility:
Opt for software that boasts an intuitive and accessible user interface. Features like drag-and-drop functionality, customizable dashboards, and clear data visualizations enhance user adoption and engagement.
3. Customization and Adaptability:
Recognize the uniqueness of your organization’s processes and requirements. Seek out process intelligence software that can be easily customized and adapted to align with your needs, ensuring a tailored solution.
4. Scalability and Flexibility:
As your organization evolves and expands, the chosen software must be capable of scaling to accommodate increasing demands. Look for scalability and flexibility solutions, enabling seamless adjustment to developing business prerequisites while maintaining functionality and performance.
5. Security and Regulatory Compliance:
Safeguarding sensitive business data is paramount. Ensure that the selected process intelligence software incorporates robust security features such as data encryption, access control mechanisms, and timely security updates to maintain compliance with regulations.
6. Total Cost of Ownership (TCO):
Assess the complete cost of ownership (TCO) associated with the software. This extends beyond the initial purchase price to encompass ongoing expenses such as maintenance, support, and upgrades. Consider factors like licensing fees, implementation and training expenditures when calculating TCO.
AI in process intelligence
Beyond its robust discovery capabilities, process intelligence harnesses the potential of artificial intelligence and cognitive algorithms to unlock additional advantages. These encompass cutting-edge technologies like:
Natural Language Processing (NLP): This technology excels at extracting and structuring data from diverse sources, including unstructured data, as a prelude to analysis.
Optical Character Recognition (OCR): OCR empowers the text extraction from images, facilitating the incorporation of visual information into the analytical process.
Natural Language Generation (NLG): NLG transforms data into human-readable language, enhancing the interpretability of insights.
Given the wide scope of process intelligence encompassing diverse tools, AIMultiple has not included essential business process automation technologies such as intelligent process automation, robotic process automation (RPA), workflow automation, and associated disciplines like Business Process Management (BPM) in its current vendor list. AIMultiple intends to enhance the vendor list and classification in the future.
The tools presented in the list above are organized based on the number of reviews they received.
Explore more on process intelligence and process mining by checking out:
- 6 Easy Process Mining Digital Transformation Tips
- How to implement process improvement
- 4 Fueling Trends Shaping the Future of Process Mining
If you still have questions about process intelligence software and landscape, we are happy to help:
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