Quantitative process analysis employs numerical methods to assess and enhance operational procedures by identifying inefficiencies and improving decision-making through data. Key steps involve data collection, defining metrics, modeling processes, analyzing performance, and recommending improvements using various tools such as statistical and simulation software. Its benefits include improved efficiency, resource utilization, and data-driven decisions, though challenges exist in data accuracy and potential resistance to change.

1. QUANTITATIVE
PROCESS ANALYSIS

2. WHAT IS QUANTITATIVE
PROCESS ANALYSIS?
 The use of numerical methods to evaluate
and improve processes.
PURPOSE:
 Identify inefficiencies and bottlenecks.
 Enhance decision-making using data.
2

3. KEY STEPS IN QUANTITATIVE
PROCESS ANALYSIS
1. Data Collection: Gather relevant metrics and
process data.
2. Define Metrics: Choose key performance
indicators (KPIs).
3. Model the Process: Use diagrams, flowcharts,
or software.
4. Analyze Performance: Apply statistical or
mathematical methods.
5. Recommend Improvements: Develop
actionable insights.

4. TOOLS USED IN
QUANTITATIVE PROCESS
ANALYSIS
4
Process modeling tools (e.g., BPMN)
Statistical tools (e.g., regression
analysis, variance analysis)
Simulation tools (e.g., Monte Carlo
simulations)
Spreadsheet software (e.g., Excel).

5. EXAMPLE OF QUANTITATIVE
PROCESS ANALYSIS
Scenario: Evaluating a manufacturing line’s
productivity.
Steps Taken:
 Collected data on cycle time and defect
rates.
 Analyzed delays and inefficiencies.
 Recommended optimized scheduling and
quality checks.
5

6. BENEFITS OF QUANTITATIVE
PROCESS ANALYSIS
Improves process efficiency and
performance.
Identifies bottlenecks and
eliminates waste.
Enhances resource utilization.
Supports data-driven decision-
making.
6

7. CHALLENGES IN
QUANTITATIVE PROCESS
ANALYSIS
7
• Difficulty in collecting accurate data.
• Requires skilled analysts and tools.
• Potential resistance to changes in the
process.

8. THANK
YOU
 RAMBOYONG, ROBERT V.
 NAZ, IAN M.
 PRUDENCIO, CRISIEL G.
 BAYOS, MA. HAZEL B
 LINDAYAG, GENE RUZELE B.
 BAÑARIA, BRYAN S.
 RIVERA, CLARIZE B.