In the middle of the 20th century, dozens of countries and millions of people believed that central planning was the best way to run their economies.  Even today there are many people who can’t quite understand why market economies invariably outperform planned economies; it would seem that at least some of the planned economies should have flourished.  After all, there are advantages to centralizing economic decisions:  virtually full employment is possible; income can be distributed more equally; central coordination should be more efficient; directing resources into investment should spur growth.  So why did planned economies fail? 

A fundamental problems with planned economies is that in a complex and changing economic system, it is impossible to plan for everything, so a lot of things fall between the cracks.  For instance, planned economies usually suffer a shortage of spare parts, because no one plans for machines to break down.  Secondary effects such as environmental impact are often ignored.  Furthermore, planners do not have control of the purchase of goods, so they have to guess what consumers really want.  Inaccurate forecasts are amplified by a long planning cycle, causing chronic shortages and surpluses.  Finally, individuals have little incentive to address these problems, because they are rewarded on meeting planned targets, not on improving the overall system.

The difference between a planned and a market economy is rooted in two different management philosophies:   

1. Management-as-planning/adhering focuses on creating a plan that becomes a blueprint for action, then managing implementation by measuring adherence to the plan. 

2. Management-as-organizing/learning focuses on organizing work so that intelligent agents know what to do by looking at the work itself, and improve upon their implementation through a learning process. 

An example of management as planning/adhering can be found in Material Requirements Planning (MRP) systems, which were widely expected to increase manufacturing efficiency in the 1980’s by providing detailed production planning. In fact, most MRP systems failed at shop floor planning for the same reasons that planned economies failed:  the systems could not readily adapt to slight variations in demand or productivity.  Thus they created unworkable schedules, which had to be ignored, causing the systems to become ever more unrealistic.

As the centralized MRP planning systems were failing, Just-in-Time systems appeared, with their focus on management-as-organizing/learning.  Just-in-Time forsakes central planning in favor of collaborating teams (intelligent agents).  The environment is organized in such a way that the work itself and the neighboring teams signal what needs to be done; rather than a central plan.  When problems occur, the root cause is sought out and eliminated, creating an environment in which intelligent agents continually improve the overall system.  In almost all manufacturing environments, implementing Just-in-Time trumps any attempt to plan detailed production activities using an MRP system.  Just-in-Time systems succeed for the same reason a market economy succeeds:  intelligent agents are better at filling in the gaps and adapting to variation than a centrally planned system.

Management-as-planning/adhering leads to the same problems with software projects that planned economies suffered: in a complex and changing environment, it is virtually impossible for a plan to cover everything.  Work breakdown structures and detailed project schedules are similar to MRP systems; they are invalidated by even modest variation.  Worse, measuring adherence to an invalid plan produces incorrect results and diminishes incentives for catching the things that fall between the cracks.