Constraint Theory A Logic - Based Approach to System Improvement

The Theory of Constraints (TOC), developed by Dr. Eliyahu M. Goldratt, offers a methodology for achieving system optimization, rather than process maximization. By synchronizing an organization as an integrated whole, instead of a collection of related parts, higher levels of system performance can be achieved more quickly. TOC provides a series of guiding principles and concepts, supported by a set of logistical tools to manage work flow through the system and a set of logical tools (trees) to identify system constraints and design and implement effective ways to break them. Hundreds of companies, large and small, have realized major successes with TOC and its tools. Noteworthy among these companies are Bethlehem Steel, Ford Electronics, Harris Semiconductor, and General Motors, whose cases are summarized in this paper. Hundreds of other smaller companies in every conceivable business from software engineering to health care have also applied TOC principles and tools. After introducing constraint theory and explaining its relationship to system management and organizational change, this paper concentrates on the five logical tools Goldratt developed to identify, exploit, and even break constraints to better organizational performance. Examples of the logic trees in various familiar situations are provided. It is a simple task to make things complex, but a complex task to make them simple. The complexity of our environment and the systems within it grows almost daily. The business world, government, and social systems were all far less complicated 70 years ago than they are today. As communication makes the world smaller and its elements more interactive, these environments are likely to become even more complex in the future. The dynamic, ever-changing nature of the environment virtually guarantees challenges of the “adapt-or-die” type to all our systems: business, education, social, and political. SYSTEM COMPLEXITY Adaption implies change, and the more complex the system, the more difficult change is to cope with. Besides complexity, however, several other factors conspire against the chances of first-time successful change. One is the aforementioned dynamic, ever-changing nature of the environment. It’s tough to hit a moving target. Another is the uncertainty posed by variation and the dependent nature of system components. A third is the natural tendency to compartmentalize component activities within systems organizationally rather than to integrate them functionally. In other words, we tend to manage by the organization structure than by the natural functional flow of work through the system. This usually leads to a fourth factor: local optimization at the expense of the well-being of the whole system.