Deck 4 Process Intelligence Mining Analytics Flashcards
SAP Signavio Process Intelligence uses event log data to:
A) Create random guesses about processes
B) Reconstruct actual process flows, identify bottlenecks, and find improvement areas
C) Replace BPMN with spreadsheets
D) Hide inefficiencies
B) Reconstruct actual process flows, identify bottlenecks, and find improvement areas.
Explanation: Process mining leverages event logs to uncover how processes are executed in reality, revealing inefficiencies.
Process mining involves analysing:
A) Fake data
B) Actual event logs from IT systems that record who did what, when
C) Only manual notes from employees
D) Unrelated financial forecasts
B) Actual event logs from IT systems that record who did what, when.
Explanation: Event logs provide the data backbone for process mining, capturing user interactions with systems.
A common KPI analysed with Process Intelligence might be:
A) Cycle time (how long a process takes)
B) The font used in diagrams
C) Random guesses at success rates
D) Personal opinions from staff
A) Cycle time (how long a process takes).
Explanation: Cycle time is a key metric used to measure process efficiency and identify delays.
By comparing designed BPMN models with mined models, organisations can:
A) See if their documented processes match actual practice
B) Eliminate process modelling altogether
C) Reduce compliance
D) Guess process performance
A) See if their documented processes match actual practice.
Explanation: Comparing ‘as-is’ and ‘to-be’ models reveals discrepancies that may hinder efficiency or compliance.
Process Intelligence dashboards allow teams to:
A) Focus only on historical data with no insights
B) Monitor KPIs in real-time, set alerts, and track improvements over time
C) Hide performance metrics from leadership
D) Only display static charts with no context
B) Monitor KPIs in real-time, set alerts, and track improvements over time.
Explanation: Real-time monitoring allows for proactive management and continuous improvement.
Bottleneck analysis in Process Intelligence helps identify:
A) Steps that have no impact on performance
B) Tasks causing delays, rework, or high costs
C) Random improvements without data
D) Where to add more complexity
B) Tasks causing delays, rework, or high costs.
Explanation: Bottleneck analysis pinpoints inefficient steps that slow down overall process performance.
Process conformance checking is:
A) Verifying that executed processes conform to the modelled ‘ideal’ processes
B) Irrelevant to process mining
C) Only applicable to manual processes
D) About changing the BPMN standard
A) Verifying that executed processes conform to the modelled ‘ideal’ processes.
Explanation: Conformance checking ensures that actual execution aligns with intended design.
Root cause analysis in process mining might involve:
A) Ignoring data and guessing solutions
B) Investigating which conditions lead to delays, errors, or compliance breaches
C) Removing all KPIs
D) Adding more gateways at random
B) Investigating which conditions lead to delays, errors, or compliance breaches.
Explanation: Root cause analysis identifies factors behind inefficiencies to drive targeted improvements.
Simulation in Signavio Process Intelligence can help:
A) Predict outcomes of potential changes before implementing them
B) Only show static past data
C) Ensure no improvements are made
D) Replace BPMN entirely
A) Predict outcomes of potential changes before implementing them.
Explanation: Simulation models allow organisations to test scenarios and foresee impacts before deploying changes.
Data-driven decisions, supported by Process Intelligence, result in:
A) Random improvements
B) Targeted, evidence-based process enhancements
C) Less stakeholder trust
D) Ignoring root causes
B) Targeted, evidence-based process enhancements.
Explanation: Decisions informed by data help organisations address specific inefficiencies effectively.
Process Intelligence tools in Signavio can integrate with:
A) No external systems
B) Multiple ERP and CRM systems, extracting event logs for analysis
C) Only spreadsheets manually uploaded
D) Only email logs
B) Multiple ERP and CRM systems, extracting event logs for analysis.
Explanation: Integration ensures that process insights are based on comprehensive data from various sources.
Using historical data, Process Intelligence can help:
A) Identify trends, seasonal patterns, and recurring issues
B) Ignore patterns
C) Focus solely on one-off anomalies
D) Just show daily snapshots
A) Identify trends, seasonal patterns, and recurring issues.
Explanation: Historical analysis provides insights into long-term process behaviours and opportunities for improvement.
Compliance checking in Process Intelligence ensures:
A) Actual processes adhere to required policies and regulations
B) Reducing compliance visibility
C) That all processes are non-standard
D) Limiting data-based insights
A) Actual processes adhere to required policies and regulations.
Explanation: Automated compliance checks reduce risk by identifying deviations from legal or internal standards.
Continuous monitoring via Process Intelligence:
A) Is not possible
B) Allows ongoing oversight, ensuring sustained improvements and early detection of issues
C) Is a one-time check only
D) Does not support alerts
B) Allows ongoing oversight, ensuring sustained improvements and early detection of issues.
Explanation: Monitoring ensures that improvements are maintained and new risks are flagged early.
The ultimate goal of using Process Intelligence in Signavio is to:
A) Only create nice visuals with no action
B) Continuously optimise processes, ensure alignment with desired outcomes, and maintain compliance
C) Confuse stakeholders with data
D) Replace BPMN diagrams completely
B) Continuously optimise processes, ensure alignment with desired outcomes, and maintain compliance.
Explanation: Process Intelligence helps align execution with strategic goals and compliance requirements.