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TQM – Total Quality Management

We changed it, to make it more personal. 

PQM – Personal Quality Management

The principles are the same, but the focus is different and hopefully easier to understand.

So again, what’s TQM and why do we love it?

The primary elements of TQM

Total quality management can be summarized as a management system for a customer-focused organization that involves all employees in continual improvement. It uses strategy, data, and effective communications to integrate the quality discipline into the culture and activities of the organization.

Customer-focused

The customer ultimately determines the level of quality. No matter what an organization does to foster quality improvement—training employees, integrating quality into the design process, upgrading computers or software, or buying new measuring tools—the customer determines whether the efforts were worthwhile.

Process-centered

A fundamental part of TQM is a focus on process thinking. A process is a series of steps that take inputs from suppliers and transforms them into outputs that are delivered to customers. The steps required to carry out the process are defined, and performance measures are continuously monitored in order to detect unexpected variation.

Strategic and systematic approach

A critical part of the management of quality is the strategic and systematic approach to achieving an organization’s vision, mission, and goals. This process, called strategic planning or strategic management, includes the formulation of a strategic plan that integrates quality as a core component.

Continual improvement

A major thrust of TQM is continual process improvement. Continual improvement drives an organization to be both analytical and creative in finding ways to become more competitive and more effective at meeting stakeholder expectations.

Fact-based decision making

In order to know how well an organization is performing, data on performance measures are necessary. TQM requires that an organization continually collect and analyze data in order to improve decision making accuracy, achieve consensus, and allow prediction based on past history.