Creating a Project

Projects are focused analysis workspaces where you explore specific aspects of your process data. Each project lets you select which objects and events to analyze, keeping your analysis focused and performant.

What is a Project?

A project is an analysis workspace that provides a focused view of your process data. While your workspace stores all your raw data, projects let you:

• Select specific data: Choose which object types and event types to analyze
• Focus your analysis: Work with a manageable subset of your full dataset
• Create multiple views: Analyze the same data from different angles
• Share insights: Collaborate with teammates on specific analyses

Project vs. Workspace vs. Dataset

Understanding these three concepts:

Workspace

• Your data warehouse
• Stores all datasets
• Shared by all team members
• Contains multiple projects

Dataset

• Raw data you've uploaded
• Contains objects, events, and relationships
• Multiple datasets can exist in one workspace

Project

• Analysis view of dataset(s)
• Selects specific object and event types
• Has its own process map, variants, insights
• Multiple projects can use the same dataset

Think of it this way:

• Workspace: Company-wide database
• Dataset: Uploaded data files
• Project: Specific analysis or report

Creating Your First Project

After uploading your data, you're ready to create a project. Here's the step-by-step process:

Step 1: Navigate to Project Creation

From your workspace:

1. Go to the "Projects" section
2. Click "Create New Project"
3. Project creation wizard appears

Alternatively, after dataset upload:

• Click "Create Project" from success screen
• Dataset is pre-selected for you

Step 2: Enter Project Details

Fill in the basic information:

# Example project configuration
Project Name: "Loan Approval Analysis"
Description: "Analyzing approval times and bottlenecks for standard loans"
Workspace: "Acme Financial Services" (auto-selected)

Project Name

• Required field
• Should be descriptive and specific
• Examples:
  • "Q1 2024 High-Value Loan Analysis"
  • "Standard Loan Approval Process"
  • "Rejected Applications Investigation"

Description (Optional)

• Explain what you're analyzing
• Note any specific focus areas
• Helps team members understand the project purpose
• Example: "Focusing on standard loans over $50K to identify approval bottlenecks"

Step 3: Select Object Types

Choose which object types to include in your analysis.

What are object types? The "things" in your process. From our loan example:

• Loans (your primary case objects)
• Customers (related entities)
• Officers (people involved)
• Documents (supporting materials)

Your choice:

• ✅ Select "Loans" (primary - always include)
• ✅ Select "Customers" (to analyze customer patterns)
• ⬜ Skip "Officers" (not needed for this analysis)

Why this matters:

• Including fewer object types makes the process map clearer
• You can always create another project with different selections
• Start focused and expand later if needed

Step 4: Select Event Types

Choose which event types (activities) to include.

What are event types? The activities that happen in your process. From our loan example:

• Application Submitted
• Credit Check Complete
• Risk Assessment
• Manager Approval
• Loan Disbursed
• Application Rejected

Your options:

Include All Events (Recommended for first project)

• See the complete process flow
• Identify all activities and their frequencies
• Good starting point for exploration

Select Specific Events

• Focus on particular activities
• Remove noise from rarely-used events
• Create cleaner, more focused process maps

Example selection for loan approval focus:

• ✅ Application Submitted
• ✅ Credit Check Complete
• ✅ Risk Assessment
• ✅ Manager Approval
• ✅ Loan Disbursed
• ⬜ Application Withdrawn (rare, skip for now)
• ⬜ Document Resubmitted (detail not needed yet)

Step 5: Define Process End Points

The final step uses AI to help you identify which events mark the end of your process. This is important for accurate case analysis and variant detection.

What happens: Our AI analyzes your data patterns and suggests which event types are likely terminal events (where processes end).

AI-Powered Suggestions: The AI examines your data to identify terminal events based on:

• Last Event percentage: How often this event is the final event in a case
• Position percentage: Where this event typically occurs in the process flow
• Confidence level: How certain the AI is about its suggestion

You have the final say:

• Review the AI suggestions (shown with "AI Selected" badge)
• Check or uncheck events to override the AI's recommendations
• Events with high "Last Event" and "Position" percentages are strong candidates
• The confidence indicator helps you make informed decisions

Example:

• Payment Completed: 99% Last Event, 100% Position, 100% confidence → Strong terminal event
• Order Cancelled: 99% Last Event, 100% Position, 100% confidence → Strong terminal event
• Payment Processed: 0% Last Event, 91% Position, 60% confidence → Likely not a terminal event

Your actions:

1. Review the AI-suggested terminal events
2. Adjust selections based on your process knowledge
3. Click "Create Project" to proceed
4. Project is created and you're navigated to analyze your process

Project Dashboard

Once created, your project dashboard is your central hub for analysis:

Overview Section

Key Metrics

• Total cases (e.g., 250 loans)
• Total events (e.g., 1,247 events)
• Unique variants (e.g., 12 different process paths)
• Average case duration

Recent Activity

• Latest insights generated
• Recent co-pilot conversations
• Team member actions

Quick Actions

Explore Process

• View Process Map
• Analyze Variants
• Check Insights

Ask Questions

• Open AI Co-Pilot
• View starter questions

Understanding Data Scope

Projects use a concept called "data scope" to define what's included in the analysis:

What is Data Scope?

Data scope determines:

• Which object types are visible
• Which event types are included
• What relationships are analyzed
• What appears in process maps

Example: Loan Project Scope

Full Dataset (in workspace)

• 250 loan applications
• 180 customers
• 45 officers
• 1,500 total events including all activity types

Project Scope (focused view)

• 250 loan applications (included)
• 180 customers (included)
• Officers (excluded)
• 8 primary event types (excluded 4 rare activities)
• Result: 1,247 events in process map

Modifying Data Scope

You can adjust project scope anytime:

1. Go to project settings
2. Navigate to "Data Scope" tab
3. Add or remove object types
4. Add or remove event types
5. Save changes
6. Process map updates automatically

When to modify scope:

• Process map is too complex (remove detail events)
• Want to focus on specific process phase (select only those events)
• Need to include previously excluded objects
• Want to analyze different process aspects

Project Settings

Configure your project through the settings panel:

General Settings

Project Information

• Update project name
• Modify description
• View creation date
• See last modified date

Data Scope

• Adjust included object types
• Modify included event types
• See current scope summary

Event Groups

Create logical groupings of related events:

Example: Loan Process Phases

• Application Phase: Application Submitted, Document Upload
• Review Phase: Credit Check, Risk Assessment, Background Verification
• Decision Phase: Manager Approval, Director Approval, Final Decision
• Fulfillment Phase: Loan Disbursed, Confirmation Sent

Event groups help simplify complex process maps by showing high-level phases instead of every individual activity.

Learn more: Event Groups

Sharing and Permissions

Project Visibility

• Private to you (default)
• Shared with specific team members
• Visible to entire workspace

Collaboration

• Invite specific collaborators
• Set view-only or edit permissions
• Share specific filtered views

Managing Multiple Projects

As your analysis needs grow, you'll create multiple projects:

When to Create Multiple Projects

Good reasons for separate projects:

• Different process phases (approval vs. fulfillment)
• Different object focus (customer-centric vs. loan-centric)
• Different stakeholder audiences (executives vs. operations)
• Different time periods for comparison (Q1 vs. Q2)
• Different process variants (standard vs. expedited)

Use filters instead of new projects for:

• Different value ranges (high-value vs. low-value)
• Different statuses (approved vs. rejected)
• Different time windows (this month vs. last month)
• Different attributes (risk levels, regions, etc.)

Project Workspace Tips

Naming Convention

• Include focus area: "Loan Approval - High Value"
• Include time period if relevant: "Q1 2024 Analysis"
• Be specific: "Rejected Applications Study" not "Analysis 2"

Project Descriptions

• Explain the focus
• Note key findings or goals
• Update as you discover insights
• Include links to related projects

Workspace Hygiene

• Archive completed projects
• Delete test/experimental projects
• Keep active project count manageable (5-10 is ideal)

Best Practices

Start Broad, Then Focus

First Project: Include everything

• All object types
• All event types
• Explore the full process

Subsequent Projects: Get specific

• Focus on problem areas
• Narrow to specific process phases
• Target specific stakeholder needs

Document Your Findings

Use project descriptions to track:

• Key insights discovered
• Questions answered
• Questions still open
• Recommended actions

Use Consistent Naming

Establish a naming pattern:

• [Process Area] - [Focus] - [Time Period]
• Example: "Loan Approval - Bottlenecks - Q1 2024"
• Makes it easy to find related projects

Review and Cleanup Regularly

Monthly maintenance:

• Archive old projects no longer needed
• Update project descriptions with current status
• Consolidate insights across projects
• Delete duplicate or test projects

Troubleshooting

Can't Create Project

Issue: Create project button is disabled or you get an error.

Solutions:

• Verify you have at least one dataset uploaded
• Check that dataset transformation completed successfully
• Ensure you have permissions to create projects
• Try refreshing the page

Project Appears Empty

Issue: Created project but process map shows no data.

Solutions:

• Verify you selected at least one object type
• Check that you selected at least one event type
• Ensure the dataset has data matching your selections
• Review data scope settings

Process Map Too Complex

Issue: Too many nodes and edges, can't make sense of it.

Solutions:

• Narrow event type selection (exclude rare activities)
• Use event groups to combine similar events
• Create a focused project on specific process phase
• Use filters to narrow down to specific cases

Multiple People Need Different Views

Issue: Team members want to analyze different aspects.

Solutions:

• Create multiple projects with different scopes
• Use project sharing to give access
• Each person can create their own focused projects
• Use filters within shared projects for personal views

Next Steps

Now that you have a project, you're ready to explore your process:

Visualize Your Process

• Process Map - See your process flow visually
• Process Variants - Analyze different execution paths

Get AI Insights

• AI-Generated Insights - Let AI identify bottlenecks and opportunities
• AI Co-Pilot - Ask questions in natural language

Advanced Analysis

• Filters & Exploration - Drill down into specific scenarios
• Event Groups - Simplify complex processes