Order

TABLE OF CONTENTS

§ Total Quality Control
§ Organizational Learning
     Operational and Conceptual Learning
     Learning Cycle Time
     TQC as a Vehicle for Organizational Learning
     Systems Thinking and Organizational Learning
§ Beyond TQC: Systemic Quality Management
     Tackling Organizational "Messes"
     The "Laws" of Systems Thinking
     The 10 Tools of Systems Thinking
     The Manager's Dilemma: Reflection vs. Action
§ From Learning Systems Toward Learning Organizations
     Managerial Microworlds as Learning Systems
     Toward Learning Organizations
     Managers' New Roles: Researchers and Theory-Builders

ABOUT THE AUTHOR

Daniel H. Kim is cofounder of the MIT Center for Organizational Learning and Pegasus Communications, Inc., and founding publisher of THE SYSTEMS THINKER™ Newsletter. This volume was formerly published as part of the Special Report Series, and has been reformatted for this edition.

EXCERPTS

Beyond TQC: Systemic Quality Management

We must do more than play "follow the leader" if we hope to regain and sustain a competitive advantage in the global marketplace—we must innovate beyond TQC. Integrating TQC and systems thinking can accelerate organizational learning beyond the current capabilities of traditional TQC methods. The two approaches form a synergistic pair whose individual strengths complement each other and provide a balance of operational and conceptual learning (see "Systemic Quality Management Model"). Each process informs and enhances the other. Together, they advance organizational learning by helping to build a shared understanding of conceptual insights and operational processes, and create a powerful new model I call Systemic Quality Management (SQM).

In the SQM model diagram, the top box represents the traditional system dynamics approach of gathering data, conceptualizing, building a model, running simulation analyses, and proposing policy changes. An implicit assumption of this process is that the insights alone would be compelling enough to produce action. In reality, however, such policy-change recommendations are seldom implemented because building shared understanding traditionally has not been part of the process. Clearly, more could be done on implementation.

The bottom box represents a typical TQC process of quality improvements, the so-called PDCA (Plan-Do-Check-Act) cycle, which should be carried out at every level of an organization. Requests from a higher level are interpreted and translated into a plan of action with the appropriate check points identified for monitoring progress relative to the plan. The plans are incorporated into the budgetary cycle and implemented. The check points identified earlier are tracked, and deviations are observed. The data is then analyzed, and actions are taken to correct any discrepancies. Although the PDCA cycle can help in implementing new requests given from above and in maintaining control over current processes, it is relatively weak on identifying the high-leverage areas that can drive the whole process.

Combining these processes means integrating conceptual and operational learning by blending the two into a seamless process. For example, building shared understanding through the use of management flight simulators and learning labs can enhance the PLANning and DOing steps by providing a common base of conceptual models. Having greater shared understanding can also facilitate buy-in of policy-change recommendations. Conceptual insights such as "eroding goals" and "worse-before-better behavior" can help those involved in the DOing to see how their actions relate to the overall system. The analysis and action produced through the PDCA cycle should generate new data that would feed into the data-gathering process as well as the next cycle of the PLAN.

Through SQM, organizations can identify high-leverage points and act upon them. Because there is an abundance of written materials available on TQC and limited systems thinking literature, I will concentrate on illuminating the ways in which ST can contribute to the SQM model.