In today‘s complex and fast-changing business landscape, companies often lose visibility into their own processes. Assumed process maps drift from reality as exceptions and workarounds crop up. This lack of truth threatens operational excellence and process improvement efforts.
Enter process discovery – a critical technique to illuminate the actual end-to-end processes being performed within an organization. By reconstructing processes from system event logs, companies can finally "see" their processes as they are executed.
With this holistic intelligence, leaders can make strategic decisions grounded in facts vs. assumptions. Process discovery provides the roadmap for process excellence.
In this comprehensive guide, we’ll unpack everything you need to know about process discovery in 2024:
- What is process discovery and why it matters now
- How process discovery reconstructs processes
- Key benefits for operations, compliance, automation
- Overcoming top challenges
- Review of enabling technologies
- 10 steps to maximize the business impact
Let‘s dive in to unlock the immense power of process discovery.
What Exactly is Process Discovery?
At its core, process discovery uses data to reconstruct and analyze actual business processes versus assumed processes. Also called “process mining”, it connects the dots between digitally recorded events to model end-to-end processes.
The key output is an objective “as-is process map” reflecting real-world processes. This reveals:
- Each process step performed
- The sequence of activities
- Process variations and deviations
- Performance metrics like cycle times
- Roles, systems, rules, and decision logic
For example, process discovery can map the full order-to-cash process from end to end – from order entry to delivery to invoicing and payment. This exposes the real flow of work, bottlenecks, and exceptions.
A discovered "as-is" order-to-cash process
With this accurate picture, companies can optimize processes, improve compliance, identify automation opportunities, and resolve pain points. Assumptions and guesswork are replaced by data-driven truth.
Why Process Discovery Matters Now
In today‘s business environment, process discovery is more relevant than ever for driving operational excellence:
Accelerating Complexity: As competition intensifies, processes grow increasingly complex from new technologies, distribution channels, regulations, and product variations. Undiscovered processes become black boxes.
Digital Transformation: Major IT initiatives like ERP overhauls and RPA scale implementations dramatically reshape processes. Mining new processes becomes mandatory to realize benefits.
Remote Work: With remote and hybrid work, processes end up executed differently than designed. Continual rediscovery is key for visibility.
Regulatory Mandates: Regulations like GDPR require companies to intimately understand personal data flows, making process discovery essential.
Process Automation: Initiatives like RPA and workflow automation rely on accurate process insights to target the right opportunities. Otherwise benefits diminish.
Competitive Mandate: Efficient and agile operations are now competitive mandates. Process discovery provides the roadmap for operational excellence.
As complexity continues accelerating in 2024, few companies can afford "dark" processes without complete visibility. Process discovery is a must-have capability.
How Process Discovery Reconstructs "As-Is" Processes
Performing process discovery involves four key phases:
Step 1: Extract Digital Event Log Data
Process discovery relies on event log data that captures the digital footprint of actual process execution.
Event logs are extracted from key enterprise systems like ERP, CRM, HRIS, SCM, and other transactional applications. This requires connecting to database transaction logs or application APIs.
Example event log data from multiple systems
Key event data fields generally include:
- Case ID: Unique ID for a process instance (e.g. order #)
- Activity: The process step name (e.g. "Generate Invoice")
- Timestamp: Date/time the activity occurred
- Resources: Employees, systems, or agents involved
- Other attributes: Case data, organizations, etc.
This raw material reflects real-life behavior to discover how activities are performed in sequence during process execution.
Step 2: Reconstruct Process Models
Next, the event log data is analyzed case-by-case to reconstruct complete process models. Timestamps associate events into chronological end-to-end sequences per unique case ID.
Data science techniques identify the most frequent process sequences. Variants surface deviations from the happy path caused by exceptions or decisions. Advanced algorithms incorporate contextual data for a multidimensional view of processes.
The result is an objective process model reflecting the observed reality – warts and all.
Step 3: Visualize the Process with Analytics
Process discovery analytics bring models to life with interactive process maps and dashboards. Key analysis dimensions include:
- End-to-end flows showing all process paths
- Frequency of different variants
- Performance with cycle times and bottlenecks
- Roles involved at each step
- Decisions driving process branching
This visual storytelling empowers drilling into case details and analyzing root causes behind process behaviors.
Process analytics uncovering performance insights
Step 4: Act on Intelligence
The core end goal of process discovery is action. Use cases include:
- Identifying automation opportunities
- Resolving bottlenecks
- Improving decisions with process context
- Eliminating broken processes
- Ensuring compliance
- Managing transformations
Process intelligence guides both incremental and transformational process changes. This closes the loop between insights and impact.
Key Benefits of Process Discovery
The scope of benefits from process discovery is far-reaching:
Supports Process Standardization
By mapping truth, companies can define and implement improved future-state processes consistently across regions, departments, and product lines.
Enables Process Compliance
Deviations from prescribed processes become visible for enforcement of standardized processes for quality and compliance.
Optimizes Process Automation
The most impactful automation opportunities are revealed based on frequency, cost-savings, and other factors – rather than automating broken processes.
Reduces Operational Costs
By spotlighting redundant activities and waste, process discovery pinpoints areas for cost reduction through automation and streamlining.
Improves Customer Experiences
Customer-impacting processes can be optimized to remove friction points and bottlenecks that undermine customer satisfaction.
Manages Digital Transformations
Both major IT projects and incremental changes can be measured before and after to ensure process improvements are realized and sustained.
Empowers a Culture of Excellence
With accurate process baselines, a data-driven culture of continuous process improvement becomes possible.
The benefits ultimately translate into competitive advantages as operations become more efficient, compliant, cost-effective, and responsive to customers and stakeholders.
Overcoming Top Process Discovery Challenges
While highly impactful, companies must be aware of a few key process discovery challenges:
Capturing Quality Event Data: Careful instrumentation of source systems is required to capture complete and accurate event logs. Incomplete or erroneous data creates blindspots.
Skill Gaps: Specialized data science, data visualization, and process expertise are required to configure connectors, interpret data, and drive action.
Achieving Stakeholder Buy-In: Overcoming defensiveness and skepticism is key to aligning teams around discovered improvement opportunities.
Translating Insights Into Action: The toughest step is turning process intelligence into measurable operational impact beyond just reports. Dedicated resources are required.
Sustaining Value: One-off process discovery efforts decay without ongoing governance. Companies must embed discovery into operational routines to keep insights fresh.
With the right strategy and expertise, these hurdles can be cleared to drive maximum benefit.
Process Discovery Technology Landscape
Several leading technology approaches enable process discovery, each with pros and cons:
Purpose-Built Process Mining Software: Products like Celonis, UiPath Process Mining, Minit, and QPR ProcessAnalyzer provide robust discovery capabilities out-of-the-box. However, they involve significant software costs.
BPM Suites: BPM platforms like Appian, Newgen, IBM, and Nintex integrate process discovery alongside process modeling, automation, and monitoring. Tighter integration between discovery and improvement but can lack depth of pure-play mining tools.
Open Source Tools: Apromore, PM4Py, ProM, and others provide free process mining capabilities, but require hands-on coding and statistical knowledge for configuration and use.
General Analytics Software: BI tools like Power BI and Tableau enable data loading, analysis, and visualization of event logs but lack built-in discovery algorithms. Significant IT effort is required for process reconstructions.
10 Steps to Maximize Process Discovery Impact
While technology provides the foundation for process discovery, success requires much more:
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Build Executive Sponsorship: Align process discovery initiatives with strategic priorities to secure leadership support and resourcing.
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Start Small, Demonstrate Value: Prove value with targeted pilot use cases before expanding scope. Quick wins build momentum and trust.
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Invest in Skills: A new blend of data engineering, data science, process excellence, and visualization skills is required to extract value. Build or buy these capabilities.
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Instrument Source Systems: Carefully plan collection of high quality event log data with minimal business disruption. Proactively address data privacy.
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Democratize Analytics: Enable business teams to harness insights via self-service visualization rather than just static reporting.
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Nurture Process Ownership: Build process literacy across functions. Ensure process owners embrace discovered processes and improvement roadmaps.
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Drive Action Orientation: Move beyond insights to realize concrete operational improvements. Appoint change agents to bridge discovery and impact.
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Sustain Governance: Operationalize process discovery as a continual capability vs. a one-off exercise. Refresh models on an ongoing cadence.
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Extend Scope: Once proven, expand process discovery across end-to-end value chains and core business processes for pervasive intelligence.
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Enable Continual Improvement: Institutionalize processes as a strategic asset with embedded KPI measurement and monitoring.
Following these steps, companies can harness process discovery for transformational business impact today and into the future. The time for process truth is now.