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Process Reliability Modeling (PRM) examines organizations transactional, reliability engineering training or manufacturing processes to determine the likelihood of passing work through each process with errors resulting in costly rework and customer disaffection.

Reliability training courses of every process is accomplished by interviewing all employees by process throughout the organization. Qualitative information gained from interviews is analyzed using Cause and Effect Diagrams.

From Cause and Effect Diagrams significant issues are identified and surveys created to collect quantitative data to determine probability of passing work through each process without rework.

PRM is a very sensitive measurement tool to analyze the entire organization to reduce cost of doing business and increase customer’s satisfaction.

Why Should You Attend:

In organizations where employees experience fear, uncertainty or doubt (FUD) production and quality of work will suffer resulting in loss of customers and revenue. FUD symptoms include:

Negative attitudes regarding the organization or it’s customers
Strained relationships between employees and management
Us versus them attitude
Poor morale
Political behavior
Overactive rumor mill
These and many more are all symptoms of dysfunctional organizations and must be addressed.

Process reliability trainingsare an organizations competitive advantage; processes must be effective, efficient and exhibit very high reliabilitymodeling and prediction:

Effectiveness – no rework in any process
Efficiency – work is completed within or on schedule
High reliability –no “weak-link” in the chain of processes
Fear is very contagious; it moves from person to person throughout the organization. Employees will do whatever it takes to survive; however, these actions may not result in the quality of work expected by management.

Process Reliability Modeling starts with employees who analyze their organization to determine issues, bottlenecks that inhibitwork progress. From the analysis Process Owners are selected and work begins on improvement to ensure effective, efficient and reliable processes.

The Cost of FUD: ineffective, inefficient and unrealizable processes are costly to the organization. The average performance of a company is 3-sigma, 25 percent to 40 percent of its revenue is wasted. A 4-sigma company will loose 15 percent to 25 percent of revenue.

Process Reliability Modeling (PRM) can easily move an organization to 5-sigma if the issues found during PRM are addressed and a process owner monitors processes; the final result will be a very low FUD factor.

Areas Covered in this Webinar:

The Organization as a System
The Affects of One Bad Process on the System
How an Ineffective Process is Identified Before It Affects Organization’s Bottom Line
Process Improvements that Lasts
The Role of Process Owners
Management Support
Improving Bottom Line Without Layoffs

Learning Objectives:

Address Problems with Countermeasures
Collect Process Information from Employees
Prioritize the Information for Analysis
Turn Qualitative Information into Quantitative Data
Compute Reliability of Each Process from Quantitative Data
Determine Cost of Unreliable Processes
Determine the Correct Course of Corrective Action
Engage Corrective Action

Who Will Benefit:

Senior Management Team
Process Owners

Speaker Profile:

Dr. Michael Abitz is an Adjunct Professor at New Mexico Jr. College, Hobbs, NM. He received his Doctorate in Management from Colorado Technical University and Master of Science in Quality Assurance from California State University.

His areas of interest include teaching online, mentoring organizations in problem solving and process improvement; to date cost savings include $15.6M in addition to $14M in sales.

His webinar topics to Increase Customer Satisfaction and Profit include subjects like Process Reliability Modeling: Management and Cost Savings Process, Root Cause Failure Analysis: Problem Identification and Correction and Aligning Corporate Strategy, Structure and Systems: Achieve Corporate Objectives.

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