10 UX Design Tips for Process Mining Tools

By Atom
September 10th, 2024

Process mining tools help businesses analyze and improve their operations, but their effectiveness depends on good user experience (UX) design. Here are 10 key UX tips to make process mining tools more user-friendly and impactful:

Focus on user needs
Make data easy to understand
Create intuitive navigation
Tailor interfaces for different users
Add step-by-step guidance
Design for all devices
Simplify data management
Improve team cooperation
Speed up the tool
Make it accessible to everyone

By following these tips, you can create process mining tools that are easier to use and drive real business results. For example, KPMG used process mining to analyze loan applications and cut average wait times from 21.90 days, improving customer satisfaction.

Looking ahead, process mining tools will likely incorporate more AI capabilities to suggest solutions and identify opportunities. This means UX designers will need to present AI insights clearly and actionably.

Tip	Key Benefit
Focus on user needs	Improves tool adoption and effectiveness
Make data understandable	Enables better decision-making
Intuitive navigation	Reduces learning curve
Tailored interfaces	Meets needs of different user groups
Step-by-step guidance	Helps new users get started quickly
Multi-device design	Allows access from anywhere
Simple data management	Saves time on data prep and input
Team cooperation features	Facilitates collaboration
Faster performance	Handles large datasets efficiently
Accessibility	Makes tool usable for everyone

1. Focus on User Needs

To create effective process mining tools, designers must put users at the center of their approach. This means understanding how people interact with these tools and what they need to accomplish their tasks efficiently.

Process mining tools help businesses uncover how users actually work with systems, often revealing unexpected patterns. For example, KPMG used process mining to analyze loan applications and found that the average wait time was 21.90 days for over 31,000 applications. By addressing the main cause of delays – debt restructuring – they were able to speed up the loan closing process and improve customer experience.

To focus on user needs:

Conduct user interviews: Engage with end-users from various roles and departments to understand their pain points and expectations.
Analyze interaction data: Use process mining to identify navigation issues, hard-to-find buttons, and time-consuming pages.
Implement user behavior mining: Track how users interact with the interface to deliver a customized experience.

Here’s a practical example of how user behavior mining can improve UX:

"If we can capture the behavior and then use tools to translate that data into understanding, we could intuit what a user wants to do." – Torsten Zube, Vice President and Head of SAP Cloud Platform Business Services at SAP SE

Consider a user who creates 20-30 product orders daily and repeatedly changes the year value for each order. By recognizing this pattern, the system could predefine the year value for that user, simplifying their workflow.

2. Make Data Easy to Understand

Process mining tools deal with complex data, but their success hinges on presenting this information in a clear, digestible format. To achieve this, focus on creating effective dashboards and reports that condense intricate process data into actionable insights.

Here are key strategies to make data easy to understand:

Use interactive dashboards: Create dashboards that allow users to drill down into specific data points. This empowers users to explore the data at their own pace and focus on areas most relevant to their needs.
Implement clear visualizations: Choose appropriate chart types for different data sets. For example:
- Use bar graphs for comparative analysis
- Employ line charts to show time-series metrics
- Utilize heat maps to differentiate between groups of data
Follow visualization best practices:
- Use consistent color schemes and clear labels
- Avoid clutter to enhance interpretability
- Highlight important data points using contrasting colors
Tailor reports to stakeholders: Customize dashboards and reports for different user roles, ensuring relevance and clarity for each group.
Incorporate process maps: Use flowcharts and process maps to provide a structured overview of complex processes, highlighting dependencies, sequences, and variations.

Let’s look at a real-world example of how effective data visualization can drive significant improvements:

"The main pain point was a lack of standardization of the consumer loan process and multiple inefficient variants of the process." – Piraeus Bank Representative

In 2018, Piraeus Bank implemented QPR Process Analyzer to gain a deeper understanding of their process problems. By visualizing their loan application process, they identified bottlenecks and inefficiencies. As a result, they cut the loan application process from 35 minutes to 5 minutes and reduced the lead time of the entire loan process by 86 percent.

To further enhance data understanding, consider using a KPI bar at the top of your dashboard. This table shows how to effectively display KPI information:

Element	Description
Black numbers	Figures for the selected period
Up arrow numbers	Positive difference compared to the previous period
Down arrow numbers	Negative difference compared to the previous period

In process mining tools, helping users find what they need quickly is key to a smooth user experience. Here are some tips to create easy-to-use navigation:

Keep it simple: Limit navigation options to essential elements. This prevents users from feeling overwhelmed when using your process mining tool.
Use clear labels: Opt for straightforward language that accurately describes each section or function. For example, use "Process Analysis" instead of "Data Exploration Suite".

Implement a logical structure: Organize content into categories that make sense to your users. For instance:

Main Category	Subcategories
Process Discovery	– Event Log Upload – Process Map Generation – Variant Analysis
Performance Analysis	– Bottleneck Detection – Cycle Time Analysis – Resource Utilization
Conformance Checking	– Rule Compliance – Deviation Analysis – Root Cause Identification

Add visual cues: Use color changes or underlines to highlight active pages or clickable elements. This helps users understand where they are and where they can go.
Optimize for all devices: Ensure your navigation works well on desktops, tablets, and smartphones. Consider using a hamburger menu for mobile versions to save space.
Include a search function: Add a search bar to help users find specific information quickly. Make sure it’s visible and easy to use.
Use breadcrumbs: Implement breadcrumb navigation to show users their current location within the tool’s structure. For example: Home > Process Analysis > Bottleneck Detection

4. Tailor Interfaces for Different Users

Process mining tools often serve diverse user groups with varying needs and skill levels. To improve user experience, it’s crucial to customize interfaces based on user roles and requirements.

Here’s how to effectively tailor interfaces:

Identify user roles: Determine the main user groups for your process mining tool. Common roles include:

Role	Primary Focus
Analysts	Detailed data exploration and advanced analytics
Managers	High-level process overviews and KPI tracking
Process owners	Specific process performance and improvement areas
IT administrators	System configuration and user management

Customize dashboards: Create role-specific dashboards that highlight the most relevant information for each user group. For example, managers might need a summary of process performance, while analysts require detailed data visualizations.
Adjust feature access: Limit or expand feature access based on user roles. This helps prevent overwhelm for less technical users and provides advanced capabilities for power users.
Simplify data input: For users who need to upload data, provide clear instructions and user-friendly interfaces. As noted in the Custom Process App wizard, allow users to upload data files and define parameters based on their business requirements.
Offer guided workflows: Implement step-by-step guidance for complex tasks. This is particularly helpful for new users or those performing infrequent actions.
Use role-based navigation: Customize the navigation menu to show only relevant options for each user role. This reduces clutter and helps users find what they need quickly.
Provide customization options: Allow users to personalize their interface, such as rearranging dashboard widgets or saving favorite views.
Consider skill levels: Design interfaces that cater to both novice and expert users. Include tooltips and help resources for beginners, while offering shortcuts and advanced settings for experienced users.

By tailoring interfaces to different users, you can improve the overall effectiveness of your process mining tool. As Henrik Olsson, Global Head of Process Excellence at TeliaCompany, points out:

"Successful projects often come down to stakeholder buy-in, process mining is no different."

Customized interfaces that meet the specific needs of each user group can significantly boost user adoption and satisfaction, leading to more successful process mining initiatives.

5. Add Step-by-Step Guidance

Process mining tools can be complex, especially for new users. Adding step-by-step guidance helps users analyze data more effectively by breaking down complex processes into manageable parts. Here’s how to implement this feature:

Implement a guided setup: When users first access the tool, provide a quick-start guide. For example, Apromore’s Portal offers a "Quick start" section with features like "Discover a Process" and "Launch a Dashboard".

Break down the analysis process: Use this structure to guide users:

Step	Description
Data Collection	Help users gather event logs from various IT systems
Data Preparation	Guide users through cleaning and preparing the data
Process Discovery	Show how to use algorithms to create visual process models
Conformance Checking	Explain how to compare discovered models with standards
Performance Analysis	Walk users through evaluating key metrics
Improvement Implementation	Assist in redesigning workflows based on findings

Use interactive tooltips: Add hover-over explanations for complex features or terms.
Provide contextual help: Offer relevant tips and explanations as users navigate through different sections of the tool.
Create guided workflows: For complex tasks, implement step-by-step wizards. For instance, in data preparation:
- Validate data to fix outliers or missing values
- Clean the data (remove extra spaces, commas, etc.)
- Add or rename columns as needed
- Standardize data like currencies or dates
- Combine data from multiple sources
Offer prebuilt dashboards: Include ready-to-use dashboards for common analyses. For example, an End-to-End Dashboard can help users visualize process flows and identify unexpected patterns.
Teach filtering techniques: Show users how to slice and dice data effectively. Explain how applying filters from charts can update entire dashboards for a holistic view.
Encourage iterative learning: Promote a cycle of continuous monitoring and optimization. Start with smaller, manageable projects to build momentum and deliver quick results.

6. Design for All Devices

In today’s mobile-first world, process mining tools must work well on computers, tablets, and phones. This approach ensures users can access and use the tool no matter where they are or what device they’re using.

Here’s how to make your process mining tool work across devices:

Use responsive design: Make sure your tool’s layout adjusts to fit different screen sizes. This means buttons, text, and images should resize and reposition themselves based on the device.
Simplify for mobile: On smaller screens, focus on the most important features. For example, Celonis, a leading process mining tool, offers a simplified mobile view that highlights key metrics and alerts.
Optimize touch interactions: Design larger, easy-to-tap buttons and controls for touchscreens. Avoid hover-based interactions that don’t work well on mobile devices.
Test on real devices: Don’t rely solely on emulators. Test your tool on actual phones and tablets to catch usability issues.
Consider offline capabilities: Allow users to download and view process maps or reports offline, especially useful for field workers or those with limited connectivity.

Here’s a comparison of how features might differ across devices:

Feature	Desktop	Tablet	Mobile
Process map view	Full interactive view	Zoomable view	Simplified, key points only
Data input	Full keyboard support	On-screen keyboard	Voice input option
Reporting	Detailed dashboards	Summarized views	Key metrics only
Collaboration	Real-time editing	Comment and review	Notifications and quick approvals

7. Simplify Data Management

Process mining tools handle large amounts of data, so making data management easy is key for a good user experience. Here’s how to simplify data handling in your process mining tool:

Streamline data input: Use AI-assisted semantic mapping to speed up data ingestion. This feature automatically suggests how to map data to the required schema, saving time and reducing errors. For example, Celonis introduced an auto-mapping feature that lets users map attributes to the data schema with one click.
Organize data clearly: Break down complex data into separate pages or views. This helps users understand information step-by-step without feeling overwhelmed. Use drop-down menus to reveal additional details when needed.
Enable easy updates: Make sure users can update data without deep IT knowledge. As Henrik Olsson, Global Head of Process Excellence at TeliaCompany, noted: "None", he told them. He didn’t need additional licenses and had his own data." This highlights the importance of user control in data management.
Support various data formats: Allow importing data in common formats like CSV, XLS, and MXML. This flexibility makes it easier for organizations to work with their existing data.
Provide data visualization: Use charts, graphs, and process maps to make complex data more understandable. For instance, Piraeus Bank used QPR Process Analyzer to visualize their loan application process, helping them cut processing time from 35 to 5 minutes.
Integrate with other systems: Enable smooth data transfer between the process mining tool and other business systems. This reduces manual data entry and keeps information up-to-date.

8. Improve Team Cooperation

Process mining tools can boost team cooperation by offering shared insights and collaborative features. Here’s how to enhance teamwork in your UX design:

Add shared bookmarks: Let users save and share specific process views. For example, ARIS Process Mining allows teams to create bookmarks with annotations, helping focus discussions on key process areas.
Enable real-time collaboration: Implement features that allow multiple users to work on the same analysis simultaneously. ARIS Process Mining’s dynamic permissions system lets users assign access on the fly, promoting instant collaboration.
Implement task queues and notifications: Streamline workflow by adding task queues and automatic notifications. This addresses issues like those found in a claims approval process where approvers weren’t notified of pending claims, causing delays.
Create collaborative dashboards: Design dashboards that multiple team members can view and edit together. Signavio‘s Process Intelligence tool allows teams to jointly model workflows and set alert thresholds, fostering a collaborative environment.
Provide transparency in team performance: Use process mining data to give clear insights into individual and team performance. This transparency helps identify areas for improvement and quick wins, as noted by attendees at a recent Operational Excellence event.
Facilitate fact-based meetings: Design features that support data-driven team discussions. As one user reported, "Now, team meetings and monthly reports are fact-based, accurate and definitive."

9. Speed Up the Tool

Process mining tools handle large amounts of data, making speed a key factor in user experience. Here’s how to boost your tool’s performance:

Optimize data processing: Use efficient algorithms to handle large datasets. For example, KPMG improved loan application analysis by processing 31,000 applications, reducing average wait time from 21.90 days.
Implement caching: Store frequently accessed data in memory to reduce database queries and speed up load times.
Use asynchronous loading: Load non-essential elements after the main content to improve perceived speed.
Minimize API calls: Reduce the number of server requests by batching API calls and using GraphQL for more efficient data fetching.
Employ lazy loading: Load images and data only when needed, improving initial page load times.
Optimize database queries: Use indexing and query optimization techniques to speed up data retrieval.
Implement data compression: Reduce the size of data transferred between the server and client to improve load times.
Use content delivery networks (CDNs): Distribute static assets across multiple servers to reduce latency for users in different locations.
Automate repetitive tasks: Use macros, scripts, or formulas to speed up calculations and data transformations.
Regular performance audits: Conduct periodic speed tests to identify and address bottlenecks in the tool’s performance.

10. Make the Tool Usable for Everyone

Process mining tools should be accessible to all users, including those with disabilities. This approach not only broadens your user base but also aligns with the core goal of process mining: making business processes more transparent and efficient for everyone.

Here are key steps to make your process mining tool more inclusive:

Implement keyboard navigation: Ensure users can access all features without a mouse. This helps those with motor impairments and power users alike.
Use high contrast and adjustable text sizes: Allow users to customize the interface to their visual needs. For example, Twitter’s accessibility panel lets users increase color contrast and reduce motion.
Add alt text to images and graphs: Describe visual elements for screen reader users. This is crucial for process mining tools that often rely heavily on charts and diagrams.
Provide captions for video content: If your tool includes video tutorials or explanations, add captions to make them accessible to deaf or hard-of-hearing users.
Design with voice control in mind: Ensure that all functions can be accessed via voice commands for users who can’t use traditional input methods.
Test with diverse user groups: Include people with various disabilities in your user testing process to identify and address accessibility issues.
Follow WCAG guidelines: Adhere to Web Content Accessibility Guidelines to ensure your tool meets international accessibility standards.
Offer keyboard shortcuts: Implement shortcuts for common actions to improve efficiency for all users, especially those with motor impairments.
Provide clear error messages: Use simple language to explain errors and how to fix them, helping users with cognitive disabilities navigate issues.
Create an accessibility statement: Clearly communicate your commitment to accessibility and provide contact information for users who encounter issues.

Conclusion

Process mining tools are powerful, but their impact hinges on how well users can interact with them. Good UX design isn’t just a nice-to-have—it’s a must for these complex tools.

By following the tips we’ve covered, you can make your process mining tool more user-friendly and effective:

Focus on user needs
Make data easy to understand
Create intuitive navigation
Tailor interfaces for different users
Add step-by-step guidance
Design for all devices
Simplify data management
Improve team cooperation
Speed up the tool
Make it accessible to everyone

These improvements can lead to real business results. For example, KPMG used process mining to analyze loan applications and found that the average wait time was 21.90 days for over 31,000 applications. By addressing bottlenecks, they cut loan closing times and improved customer satisfaction.

Looking ahead, process mining tools are set to become even more powerful and user-friendly. Wil van der Aalst, Chief Scientist at Celonis, predicts:

"Generative and predictive AI will start showing you where more opportunities or issues might arise, and may even be able to propose solutions to problems."

This means UX designers will need to think about how to present AI-generated insights in a clear, actionable way.

Other trends to watch include:

Hybrid intelligence: Blending human and machine capabilities
Object-centric process mining: Offering a more complete view of processes across systems
Data sharing: Increasing collaboration between organizations
Sustainability: Using process mining to drive both efficiency and eco-friendly outcomes

Last updated on September 10th, 2024.