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Despite the well-documented costs of overload, many leaders still think organizations thrive under pressure. They have a lot to learn from manufacturing, where managers have adopted a "pull" system to manage task flow, improving productivity and performance. This concept can be used to prevent overload in knowledge work, too. And "visual management" techniques make it easier to apply pull thinking to a portfolio of projects by rendering nonphysical tasks tangible. Two recent changes at the Broad Institute, an MIT-affiliated biomedical and genomic research center, illustrate how.

This is an MIT Sloan Management Review article. The goal of this article, according to the authors, is to help managers understand several key work design principles that undergird not only agile practices in software but also Toyota Motor Corp.'s well-known production system. Understanding these underlying work design principles -through a framework the authors call dynamic work design -enables managers to create work processes in their own organizations that are both more flexible and more efficient. Traditionally, an academic theory known as contingency theory has suggested that if work consists of well-defined tasks (for example, assembling components), then it is best to organize it serially, like a factory assembly line. Conversely, if work is highly ambiguous and requires ongoing interaction (for example, designing new products), then it is best organized collaboratively. The authors argue that this approach to work design is not entirely satisfying for two reasons. First, it describes an unpalatable trade-off: Work done using a serial factory design isn't very flexible, making it hard to adapt to changes in external conditions, and work done using the collaborative approach often isn't very efficient. Second, few types of work perfectly fit the archetype of well-defined or ambiguous work. The authors instead advocate a dynamic approach to process and organizational design that transcends the serial versus collaborative work framework by creating mechanisms for moving between the two basic ways of organizing work at appropriate intervals. By identifying mechanisms to cycle back and forth between well-defined factory-style tasks and collaborative modes when appropriate, managers can considerably reduce the trade-off between efficiency and adaptability. For example, work on Toyota assembly lines is the epitome of the serial, mechanistic work design, and tasks are precisely specified. But sometimes things go awry.

This is an MIT Sloan Management Review article. According to the authors, there are few questions in business more powerful than "What problem are you trying to solve?" The authors argue that leaders who can formulate clear problem statements get more done with less effort and move more rapidly than their less-focused counterparts. Clear problem statements can unlock the energy and innovation that lies within those who do the core work of an organization, whether it be manufacturing, product development, or service. As valuable as good problem formulation can be, it is rarely practiced. Psychologists and cognitive scientists have suggested that the brain is prone to leaping straight from a situation to a solution without pausing to define the problem clearly. Such "jumping to conclusions"can be effective, particularly when done by experts facing extreme time pressure, like fighting a fire or performing emergency surgery. But, when making change in an organization, neglecting to formulate a clear problem statement often prevents innovation and leads to wasted time and money. A good problem statement has five basic elements: It references something the organization cares about and connects that element to a clear and specific goal; it contains a clear articulation of the gap between the current state and the goal; the key variables -the target, the current state, and the gap -are generally quantifiable, even if they cannot be measured objectively; it is as neutral as possible concerning possible diagnoses or solutions; and it is sufficiently small in scope that it can be tackled quickly. To tackle complex problems, executives need to complement good problem formulation with a structured approach to problem-solving. The authors recommend an approach using a modified version of the A3 form, which was originally developed by Toyota Motor Corp. to support knowledge sharing in its factories by summarizing a structured problem-solving effort in a single page.

One of the most common syndromes in product development is firefighting, the unplanned allocation of resources to fix problems discovered late in a product's development cycle. Although it has been widely criticized in both the popular and scholarly literature, firefighting is a common occurrence in most product development organizations. Product development systems have a tipping point. In models of infectious diseases, the tipping point represents the threshold of infectivity and susceptibility beyond which a disease becomes an epidemic. Similarly, in product development systems, there exists a threshold for problem-solving activity that, when crossed, causes firefighting to spread rapidly from a few isolated projects to the entire development system. The location of the tipping point, and therefore the susceptibility of the system to the firefighting phenomenon, is determined by resources utilization in steady state. Many of the current methods for aggregate resource planning are insufficient, and managers wishing to avoid the firefighting dynamic must rethink their approach to managing multiproject development environments.

Today's managers face a paradox. On the one hand, the number of tools, techniques, and technologies available to improve operational performance is growing rapidly. On the other hand, despite dramatic success in a few companies, most efforts to use them fail to produce significant results. To understand and resolve this paradox, this article investigates the difficulties organizations face in implementing processes and techniques such as lean production, TQM, computer-aided design and development tools, stage-gate product development processes, and improved customer service systems. The inability of most organizations to reap the full benefit of these innovations has little to do with the specific technique. Instead, the problem has its roots in how the introduction of a new improvement effort interacts with the physical, economic, social, and psychological structures in which implementation takes place. Presents a framework to understand how these failures arise and illustrates strategies for overcoming the pathological behavior through case studies of successful improvement.