3 Steps to Identify Your Happy Paths with Process Mining in ‘23
Optimize Workflows, Reduce Waste, and Improve Experiences
Smoothly flowing, efficient processes are the hallmark of a world-class organization. But over time, processes become bloated, inconsistent, and error-prone. Identifying and optimizing your "happy paths" – the streamlined workflows for key processes – unlocks transformational performance gains.
In 2024, process mining provides a powerful way to shine a light on your processes and hone in on the optimal happy paths. Done right, it leads to reduced costs, faster throughput, and delighted customers.
In this comprehensive guide, we‘ll explore how you can leverage process mining to identify and optimize happy paths in 3 key steps:
- Discover Your Processes and Happy Paths
- Understand Root Causes of Deviations
- Continuously Monitor Processes for Compliance
Implemented together, these steps create a closed-loop process excellence cycle that drives continual optimization. Let‘s dive in.
Why Do Happy Paths Matter?
First, what exactly is a "happy path" and why does it matter?
A happy path, also known as a golden path, refers to the optimal workflow through a business process that results in the perfect outcome. It is the sequence of tasks and activities that leads to the desired result in the fastest, most efficient, and error-free way possible.
Mapping and optimizing the happy path is essential for several reasons:
- Increased efficiency – Smoother workflows with less waste reduce cycle times and free up capacity. According to McKinsey, process excellence programs have increased productivity 15-50%.
- Lower costs – Eliminating redundant steps and manual work reduces operational costs. One IDC study found 30% cost reduction from process improvements.
- Enhanced customer experience – Speedy, flawless processes delight customers and prevent frustrating delays or mistakes. 89% of companies see customer satisfaction gains from process excellence initiatives.
- Compliance – Standardized happy paths ensure consistency and compliance for regulated processes. Conformance to required steps and controls is assured.
Simply put, aligning your processes with optimized happy paths translates to game-changing performance improvements. But identifying these ideal workflows can be extremely difficult without the right visibility.
This is where process mining comes in.
Step 1: Discover Your Processes and Happy Paths
Traditionally, business processes were modeled through interviews and workshops. But assumed processes often differ wildly from actual executed processes.
Process mining uses data to map your as-is processes with full transparency. Powerful algorithms auto-discover end-to-end processes by connecting events in your IT systems.
Process discovery visualizes your processes as flowcharts. You see every step, decision point, and connection between activities. Metrics like frequency, durations, and paths are automatically captured.
This complete visibility reveals areas of waste and inefficiency and their underlying root causes – something that interviews alone could never uncover.
For example, with an accurate process map, you can instantly identify:
- Redundant steps – Activities repeated in multiple paths
- Bottlenecks – Steps with consistently high durations
- Quality issues – High rework and error rates
- Variants – Multiple ways the process flows
By comparing the different variants, you can determine the optimal workflow – the true happy path.
Let‘s see this in action with an example:
A retail bank uses process mining on 50,000 loan applications. The tool discovers and maps the four primary process variants:
- Path A – 35% of cases – Average of 9 days
- Path B – 30% of cases – Average of 11 days
- Path C – 25% of cases – Average of 6 days
- Path D – 10% of cases – Average of 15 days
Path C has the fastest end-to-end duration, low rework rates, and highest straight-through processing. It represents the optimal happy path for this loan process.
Data-driven process discovery provides a 360-degree view of your operations. This insight makes identifying waste, delays, and the ideal path simple and objective.
Step 2: Understand Root Causes of Deviations
Of course, most processes deviate from the happy path all the time. Exceptions, errors, and variants abound.
Understanding exactly why these deviations happen is critical for targeted process improvement. Process mining enables this through automated root cause analysis.
Root cause analysis compares conforming versus deviating cases to pinpoint the factors leading to variants. This helps you enrich processes by addressing the root factors leading to waste and delays.
Let‘s see some examples:
- Errors – Data entry mistakes cause validation failures that route cases to rework
- Decision logic – Incorrect rule configuration sends high-scoring applications to manual review
- Resource bottlenecks – Understaffing generates queues and delays at verification steps
- External events – New regulations spur additional approval requirements
Each deviation you resolve moves more cases closer to the optimized happy path. For example:
- Correcting Errors – Adding data validation controls or automating data entry where possible
- Streamlining – Simplifying overly complex decision logic and removal of redundant steps
- Smoothing Workflows – Automating manual steps and balancing workloads to eliminate bottlenecks
You can also quantify the business impact – such as costs or delays – of deviations. This builds an ironclad case for process improvements.
"We identified over 2 million hours of annual rework and $22 million in costs from deviations. Fixing these would allow 80% of cases to follow the happy path."
Fact-based process enrichment sets you up for transformation success.
Step 3: Continuously Monitor for Compliance
Once you‘ve mapped and optimized your happy paths, the work doesn‘t stop. You need to continuously ensure processes adhere to the new golden standard.
This is achieved through conformance checking – comparing the ideal path to actual executions to detect deviations.
Conformance checking highlights any process variations, errors, or failures to comply with required steps in real-time. This enables you to quickly detect and address process issues before they spiral out of control.
You can also set up automated alerts and actions based on policy. For example:
- Alert process managers when error rates exceed 5%
- Trigger remedial workflows when critical steps are skipped
This prevents degradation and sustains the performance gains from your process excellence initiatives. It provides proof that processes are compliant for regulated industries.
Most importantly, it fosters a culture of continuous improvement. Process optimizations become business as usual rather than one-off initiatives.
Drive Continual Excellence with Process Mining
Following these 3 steps creates a closed-loop cycle of process optimization powered by objective data:
1. Discover actual processes and identify opportunities
2. Improve processes by addressing root causes
3. Monitor improved processes to sustain gains
This data-driven methodology is key to embedding process excellence into the DNA of your organization. The outcomes speak for themselves:
- 50% faster process cycle times
- 80% reduction in errors and rework
- 15-25% efficiency gains in personnel utilization
- Above 90% of cases following the optimized happy path
These performance gains compound over time to profoundly transform customer and employee experiences, costs, and competitive differentiation.
Process mining provides the quantitative insight to turn your operations into a well-oiled machine. Still have questions? Reach out to our experts for a custom demo tailored to your needs:
