Visual Data Flow 3. 20 things you can do with Celonis.

PART 1

Here’s a list of 20 things you can do with Celonis, inspired by the tasks, skills, and tools mentioned in your example. These activities highlight the versatility of the Celonis platform in process mining, data analysis, and business optimization:

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1. Process Mining

• Visualize and analyze end-to-end business processes using event logs from systems like SAP, Oracle, or Salesforce.

2. Identify Bottlenecks

• Detect inefficiencies and bottlenecks in workflows to improve process performance.

3. Automate Repetitive Tasks

• Use Celonis Task Mining to identify manual tasks that can be automated with RPA (Robotic Process Automation).

4. Optimize Supply Chain Operations

• Analyze and optimize procurement, inventory management, and order fulfillment processes.

5. Improve Order-to-Cash (O2C) Processes

• Streamline invoicing, payment collection, and customer order processing.

6. Enhance Procure-to-Pay (P2P) Processes

• Optimize vendor management, purchase orders, and payment workflows.

7. Monitor Process Compliance

• Ensure adherence to regulatory and organizational policies by tracking process deviations.

8. Predict Process Outcomes

• Use Celonis’ AI-powered insights to forecast process performance and outcomes.

9. Create Custom Dashboards

• Build interactive dashboards to monitor key performance indicators (KPIs) in real time.

10. Integrate with Enterprise Systems

• Connect Celonis to ERP, CRM, and other systems for seamless data flow and analysis.

11. Perform Root Cause Analysis

• Investigate the underlying causes of process inefficiencies and failures.

12. Simulate Process Improvements

• Test and simulate the impact of process changes before implementation.

13. Track Process Variants

• Identify and analyze different process variants to standardize workflows.

14. Improve Customer Service

• Analyze and optimize customer support workflows to reduce response times and improve satisfaction.

15. Enhance Financial Processes

• Optimize accounts payable, accounts receivable, and financial reporting workflows.

16. Conduct Data Quality Checks

• Ensure high-quality data by identifying and resolving inconsistencies in process logs.

17. Collaborate with Cross-Functional Teams

• Share insights and recommendations with stakeholders to drive process improvements.

18. Leverage Machine Learning

• Use Celonis’ ML capabilities to uncover hidden patterns and trends in process data.

19. Monitor Real-Time Process Performance

• Track live process data to make immediate adjustments and improvements.

20. Drive Digital Transformation

• Use Celonis as a foundation for transforming manual processes into automated, data-driven workflows.

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Skills and Tools You Can Use with Celonis

To achieve the above tasks, you can leverage the following skills and tools, inspired by your example:

1. Programming Languages: Python, SQL for custom data analysis and scripting.

2. Data Integration: Connect Celonis to systems like SAP, Salesforce, or Oracle.

3. Process Optimization: Use Celonis’ Execution Management to implement improvements.

4. Data Visualization: Build custom dashboards and reports in Celonis.

5. AI/ML: Leverage Celonis’ predictive analytics for process forecasting.

6. Task Mining: Identify automation opportunities with Celonis Task Mining.

7. Cloud Integration: Use Celonis with cloud platforms like AWS, Azure, or Google Cloud.

8. Data Governance: Ensure data quality and compliance within Celonis.

9. Collaboration Tools: Share insights with teams using Celonis’ collaboration features.

10. Custom Connectors: Build or use connectors to integrate Celonis with other systems.

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Example Workflow with Celonis

1. Data Collection: Extract event logs from your ERP or CRM system.

2. Process Mining: Visualize the process flow in Celonis.

3. Analysis: Identify bottlenecks, deviations, and inefficiencies.

4. Optimization: Simulate and implement process improvements.

5. Monitoring: Track real-time performance using Celonis dashboards.

6. Automation: Use Task Mining to automate repetitive tasks with RPA.

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Celonis is a powerful platform for transforming raw process data into actionable insights and driving measurable business outcomes.

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Yes, many of the 20 operations listed above can be performed programmatically using the Celonis API. The Celonis API allows you to interact with the platform programmatically, enabling automation, integration, and customization of workflows. Below, I’ll map each of the 20 tasks to its feasibility via the Celonis API and provide examples of how you can achieve them.

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1. Process Mining

• API Feasibility: Yes

• How: Use the API to upload event logs (e.g., CSV, XES) and trigger process mining analyses.

• Example: POST /api/v2/import/event-log to upload event logs.

2. Identify Bottlenecks

• API Feasibility: Yes

• How: Retrieve process analysis results (e.g., bottlenecks, inefficiencies) via API.

• Example: GET /api/v2/analysis/results to fetch bottleneck data.

3. Automate Repetitive Tasks

• API Feasibility: Partially

• How: Use Task Mining APIs to extract task data and integrate with RPA tools like UiPath or Automation Anywhere.

• Example: GET /api/v2/task-mining/tasks to retrieve task data.

4. Optimize Supply Chain Operations

• API Feasibility: Yes

• How: Fetch supply chain process data and apply optimizations via API.

• Example: GET /api/v2/processes/supply-chain to retrieve data.

5. Improve Order-to-Cash (O2C) Processes

• API Feasibility: Yes

• How: Analyze O2C processes and implement improvements via API.

• Example: POST /api/v2/processes/o2c/optimize to trigger optimizations.

6. Enhance Procure-to-Pay (P2P) Processes

• API Feasibility: Yes

• How: Retrieve P2P process data and apply optimizations.

• Example: GET /api/v2/processes/p2p to fetch P2P data.

7. Monitor Process Compliance

• API Feasibility: Yes

• How: Use the API to track compliance metrics and deviations.

• Example: GET /api/v2/compliance/metrics to monitor compliance.

8. Predict Process Outcomes

• API Feasibility: Yes

• How: Leverage Celonis’ AI/ML capabilities via API to predict outcomes.

• Example: POST /api/v2/predictions to generate predictions.

9. Create Custom Dashboards

• API Feasibility: Yes

• How: Use the API to fetch data and build custom dashboards externally (e.g., using Tableau or Power BI).

• Example: GET /api/v2/dashboards/data to retrieve dashboard data.

10. Integrate with Enterprise Systems

• API Feasibility: Yes

• How: Use the API to connect Celonis with ERP, CRM, or other systems.

• Example: POST /api/v2/integrations to set up integrations.

11. Perform Root Cause Analysis

• API Feasibility: Yes

• How: Retrieve root cause analysis results via API.

• Example: GET /api/v2/analysis/root-cause to fetch root cause data.

12. Simulate Process Improvements

• API Feasibility: Yes

• How: Trigger simulations and retrieve results via API.

• Example: POST /api/v2/simulations to run simulations.

13. Track Process Variants

• API Feasibility: Yes

• How: Fetch process variant data via API.

• Example: GET /api/v2/processes/variants to retrieve variant data.

14. Improve Customer Service

• API Feasibility: Yes

• How: Analyze customer service workflows and apply optimizations via API.

• Example: GET /api/v2/processes/customer-service to fetch data.

15. Enhance Financial Processes

• API Feasibility: Yes

• How: Retrieve financial process data and apply optimizations.

• Example: GET /api/v2/processes/finance to fetch financial data.

16. Conduct Data Quality Checks

• API Feasibility: Yes

• How: Use the API to validate and clean data.

• Example: POST /api/v2/data-quality/checks to run data quality checks.

17. Collaborate with Cross-Functional Teams

• API Feasibility: Partially

• How: Share insights programmatically by exporting data or reports via API.

• Example: GET /api/v2/reports to export reports.

18. Leverage Machine Learning

• API Feasibility: Yes

• How: Use the API to access Celonis’ ML models and predictions.

• Example: POST /api/v2/ml/models to trigger ML analysis.

19. Monitor Real-Time Process Performance

• API Feasibility: Yes

• How: Fetch real-time process metrics via API.

• Example: GET /api/v2/processes/real-time to monitor live data.

20. Drive Digital Transformation

• API Feasibility: Yes

• How: Use the API to automate and integrate Celonis with other digital tools.

• Example: POST /api/v2/automations to trigger automated workflows.

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Celonis API Overview

• Authentication: Use OAuth2 or API tokens for authentication.

• Endpoints: Celonis provides RESTful APIs for data integration, process mining, analysis, and more.

• Documentation: Refer to the Celonis API documentation for detailed endpoint specifications and examples.

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Example API Workflow

1. Authenticate: Obtain an API token.

    POST /api/v2/auth/token
   

2. Upload Event Logs:

    POST /api/v2/import/event-log
   

3. Trigger Process Mining:

    POST /api/v2/analysis/start
   

4. Fetch Results:

    GET /api/v2/analysis/results
   

5. Export Data:

    GET /api/v2/export/data
   

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Limitations

• Some tasks (e.g., Task Mining automation) may require integration with external tools.

• Advanced features like custom ML models may need additional setup.

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By leveraging the Celonis API, you can automate and integrate most of the 20 tasks into your workflows, enabling a seamless and data-driven approach to process optimization.

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PART 2.

Below are Python code examples for the first five tasks using the Celonis API, along with qualitative and technical explanations. Each example includes input and output examples.

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1. Process Mining

Qualitative Explanation:

1. Purpose: Visualize and analyze business processes using event logs.

2. Use Case: Identify inefficiencies in workflows like order processing or customer service.

3. Outcome: Gain insights into process flows, variants, and bottlenecks.

Technical Explanation:

1. Upload Event Log: Upload a CSV or XES file to Celonis.

    files = {"file": open("event-log.csv", "rb")}
    response = requests.post(url, headers=HEADERS, files=files)
   

2. Trigger Process Mining: Start the analysis using the event log ID.

    payload = {"eventLogId": event_log_id, "analysisType": "process-mining"}
    response = requests.post(url, headers=HEADERS, json=payload)
   

3. Fetch Results: Retrieve process mining results.

    response = requests.get(url, headers=HEADERS, params={"analysisId": analysis_id})
   

4. Visualize Results: Print process variants.

    for variant in results["variants"]:
        print(f"Variant ID: {variant['id']}, Frequency: {variant['frequency']}")
   

Input Example:

Case ID,Activity,Timestamp,Resource
1,Order Received,2023-10-01 09:00,User A
1,Payment Processed,2023-10-01 10:00,User B
1,Order Shipped,2023-10-02 11:00,User C

Output Example:

Variant ID: 1, Frequency: 2
Variant ID: 2, Frequency: 1

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2. Identify Bottlenecks

Qualitative Explanation:

1. Purpose: Detect inefficiencies in workflows.

2. Use Case: Improve process performance by resolving bottlenecks.

3. Outcome: Reduced cycle times and improved resource utilization.

Technical Explanation:

1. Fetch Bottleneck Data: Retrieve bottleneck analysis results.

    response = requests.get(url, headers=HEADERS, params={"analysisId": analysis_id})
   

2. Filter Bottlenecks: Extract bottleneck details.

    bottlenecks = [b for b in results["bottlenecks"] if b["severity"] == "high"]
   

3. Print Bottlenecks: Display bottleneck information.

    for bottleneck in bottlenecks:
        print(f"Bottleneck: {bottleneck['activity']}, Severity: {bottleneck['severity']}")
   

4. Export Results: Save bottlenecks to a file.

    with open("bottlenecks.json", "w") as f:
        json.dump(bottlenecks, f)
   

Input Example:

{"bottlenecks": [{"activity": "Payment Processed", "severity": "high"}]}

Output Example:

Bottleneck: Payment Processed, Severity: high

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3. Automate Repetitive Tasks

Qualitative Explanation:

1. Purpose: Identify manual tasks for automation.

2. Use Case: Use Task Mining to analyze user interactions.

3. Outcome: Automate repetitive tasks using RPA tools.

Technical Explanation:

1. Fetch Task Data: Retrieve task mining data.

    response = requests.get(url, headers=HEADERS, params={"taskType": "manual"})
   

2. Filter Tasks: Identify repetitive tasks.

    repetitive_tasks = [t for t in tasks if t["frequency"] > 10]
   

3. Export Tasks: Save tasks for RPA automation.

    with open("repetitive_tasks.csv", "w") as f:
        f.write("Task, Frequency\n")
        for task in repetitive_tasks:
            f.write(f"{task['name']}, {task['frequency']}\n")
   

4. Trigger RPA: Send tasks to an RPA tool.

    rpa_payload = {"tasks": repetitive_tasks}
    requests.post(rpa_url, json=rpa_payload)
   

Input Example:

{"tasks": [{"name": "Data Entry", "frequency": 15}]}

Output Example:

Task, Frequency
Data Entry, 15

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4. Optimize Supply Chain Operations

Qualitative Explanation:

1. Purpose: Analyze and optimize supply chain processes.

2. Use Case: Improve procurement, inventory, and order fulfillment.

3. Outcome: Reduced costs and faster delivery times.

Technical Explanation:

1. Fetch Supply Chain Data: Retrieve process data.

    response = requests.get(url, headers=HEADERS, params={"processType": "supply-chain"})
   

2. Analyze Data: Identify inefficiencies.

    inefficiencies = [i for i in results["inefficiencies"] if i["impact"] == "high"]
   

3. Optimize Processes: Apply optimizations.

    payload = {"optimizations": inefficiencies}
    requests.post(optimize_url, json=payload)
   

4. Monitor Results: Track improvements.

    response = requests.get(monitor_url, headers=HEADERS)
   

Input Example:

{"inefficiencies": [{"process": "Procurement", "impact": "high"}]}

Output Example:

Optimized Process: Procurement

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5. Improve Order-to-Cash (O2C) Processes

Qualitative Explanation:

1. Purpose: Streamline invoicing and payment collection.

2. Use Case: Reduce delays in customer order processing.

3. Outcome: Faster cash flow and improved customer satisfaction.

Technical Explanation:

1. Fetch O2C Data: Retrieve O2C process data.

    response = requests.get(url, headers=HEADERS, params={"processType": "o2c"})
   

2. Identify Delays: Find delays in the process.

    delays = [d for d in results["delays"] if d["duration"] > 7]
   

3. Apply Fixes: Implement process improvements.

    payload = {"fixes": delays}
    requests.post(fix_url, json=payload)
   

4. Track Metrics: Monitor O2C performance.

    response = requests.get(metrics_url, headers=HEADERS)
   

Input Example:

{"delays": [{"activity": "Payment Collection", "duration": 10}]}

Output Example:

Fixed Delay: Payment Collection

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