Series on Process Performance Measurement, Issue 1: From "Processes Running" to "Processes Running Well" — A Systematic Framework for Process Performance Management

Why is Process Performance Measurement So Important?

Many companies, when advancing process management, often fall into a common trap: processes are mapped out, documents are written, and job responsibilities are clarified, but when asked, "How is this process actually performing?" — no one can provide an accurate answer.

This is a typical case of the "processes exist, but performance is absent" issue.

Process management has three core components: process architecture (whether processes exist), process execution (whether processes are smooth), and process performance (whether processes are effective). Most companies invest a significant amount of effort in the first two components, but the third — process performance measurement — is often neglected.

Without measurement, there is no management. Without process performance metrics, managers cannot determine:

• Whether the process is improving or deteriorating?
• Where the bottlenecks are?
• Which areas should receive more resources?
• Whether process optimization is effective?

Process performance measurement provides a systematic answer to these questions.

1. Three Dimensions of Process Performance Measurement

A comprehensive process performance measurement system unfolds across three dimensions — efficiency, quality, and cost. These three dimensions are essential and interdependent.

1. Efficiency Dimension: How Fast Does the Process Run?

Efficiency is the most intuitive indicator of process performance. The customer's most direct perception is also "how fast" — whether it's an approval process, order processing, or after-sales service.

Key metrics include:

Key Insight: The Velocity Ratio is one of the most underestimated metrics. In most functional organizations, the Velocity Ratio is often below 10% — meaning that more than 90% of the time is spent on waiting and transferring, rather than creating value.

2. Quality Dimension: How Accurate Does the Process Run?

Efficiency addresses the "speed" issue, but being fast doesn't necessarily mean being good. The process must also answer the "accuracy" question.

• First Pass Yield (FPY): The ratio of processes that are completed correctly the first time
• Rework Rate: The proportion of process instances requiring rework
• Defect Rate: The number of defects per unit of output
• Customer Complaint Rate: The proportion of customer complaints due to process output issues
• Compliance Rate: The proportion of process executions that meet regulatory/standard requirements

3. Cost Dimension: Is the Process Worth the Investment?

Efficiency and quality both require resource investment, and the ROI must ultimately be assessed through the cost dimension.

• Total Process Cost: The full cost of completing a process (labor + systems + materials)
• Unit Process Cost: The process cost allocated per unit of output
• Cost of Quality (COQ): Prevention costs + Appraisal costs + Internal failure costs + External failure costs
• Process Cost Efficiency: Process output value ÷ Process operating cost

2. From Metrics to System: Designing Process KPIs and SLAs

With the framework of the three dimensions, the next step is to convert it into actionable KPIs and SLAs.

Process KPIs (Key Performance Indicators)

Good process KPIs follow the SMART principle:

• Specific: Directly linked to key process outputs
• Measurable: Data is obtainable and quantifiable
• Achievable: Target values are reasonable and attainable
• Relevant: Aligned with process goals
• Time-bound: Has a clear evaluation period

Example: KPI Design for the Procure-to-Pay (P2P) Process

SLAs (Service Level Agreements)

SLAs are key tools for converting process KPIs into cross-departmental service commitments. An effective SLA should clearly specify:

1. Scope of Service: Which process and which stage
2. Service Level Objectives: Specific KPIs and thresholds
3. Measurement Method: Data sources and calculation methods
4. Exception Clauses: Situations where the SLA does not apply
5. Penalty Mechanisms: Follow-up mechanisms for non-compliance

Practical Experience: More SLAs are not always better. In the initial stage, select 3-5 core indicators to make process performance "visible" before gradually refining them.

3. Implementation Path for Process Performance: From Data to Improvement

Once the metric system and SLAs are designed, the key is whether they can be truly implemented. Below is a step-by-step implementation path:

Step 1: Identify Critical Processes

Not every process requires in-depth performance measurement. Prioritize:

• Customer touchpoint processes (orders, after-sales, complaints)
• Processes with the highest resource consumption
• Processes with frequent issues

Step 2: Establish Data Collection Mechanisms

The biggest obstacle in process performance measurement is not knowing what to measure, but inability to obtain data.

• System Data: Directly obtained from ERP, OA, MES (recommended)
• Manual Statistics: Use Excel/shared spreadsheets during the transition period
• Process Mining: Automatically discover real process paths from system logs (detailed in subsequent articles)

Step 3: Set Baselines

Before improvement, run the process for 1-3 months to collect data and establish a baseline of the current level. Without a baseline, it's impossible to measure "how much improvement has been made."

Step 4: Visualization and Dashboards

Create visual management dashboards for process KPIs and report them regularly (weekly/monthly). An effective process dashboard should include:

• Connectivity Rate (Green/Red status)
• Trend Charts (weekly/monthly trends)
• Benchmark Comparison (against industry standards or historical data)

Step 5: Introduce the PDCA Improvement Cycle

The ultimate goal of process performance measurement is improvement, not evaluation. Once performance deviates from the target, immediately initiate the problem-solving process:

• Plan: Analyze root causes and develop improvement plans
• Do: Implement improvements within a controlled environment
• Check: Verify the effectiveness of improvements through process performance metrics
• Act: Standardize successful practices or adjust the improvement direction

4. Common Pitfalls and Countermeasures

Pitfall 1: Too Many Metrics, Data Overload

Symptoms: A process has a dozen KPIs, and the dashboard is cluttered, making it difficult for managers to focus on key areas.

Countermeasure: Limit each process to 3-5 core KPIs, and place alternative indicators on secondary dashboards.

Pitfall 2: Measuring Efficiency Only, Not Quality

Symptoms: The P2P process focuses solely on "speed," leading to a surge in purchase order error rates and rework time far exceeding the time saved.

Countermeasure: Efficiency metrics must be paired with quality metrics to form a "Efficiency × Quality" dual-dimensional evaluation.

Pitfall 3: SLAs Become "Wall Documents"

Symptoms: SLAs are signed and published, but no one looks at or uses them during actual operations.

Countermeasure: Embed SLAs into the process execution system — automatically remind and report non-compliance at process nodes.

Pitfall 4: Inaccurate Data, Wasted Effort

Symptoms: Incomplete system data, manual statistics with deviations, and inconsistent criteria.

Countermeasure: Start with data quality governance (refer to subsequent articles in this series) before implementing performance measurement.

5. Action Checklist from the First Article

After reading this issue, you can immediately take one action:

Select a process you are most familiar with (approval, procurement, after-sales, etc.), map out its end-to-end path, and calculate its "Velocity Ratio" — using actual time data, not estimates.

You will find that this simple calculation itself can reveal numerous improvement opportunities.

Knowledge Number: 3.3.1

Version: v20260528

Author: Quality Excellence Think Tank