Optimizing workload has always been a key concern for businesses and managers. A too heavy workload regarding to the capacity leads to explosion, a too low workload means resources are wasted. I don’t even mention last minute assignments to face imponderables. In brief, bad adjustments have an heavy price.

In a manufacturing economy things are more or less easy to manage. The capacity of a machine or the impact of bottlenecks on an assembly line are known facts. As for people accomplishing standardized tasks in such a context, the time needed to execute a precise task at a given level of quality is known too. When imponderables come, it’s easy to identify if an added production capacity is available since the maximal and actual workload are known facts too for machines. As for people, a glance at their work-in-progress is sometimes enough to evaluate the sitation. In short, in a tangible production system, it’s easy to know the sitation at a given moment and what’s the safety margin (if any). More, the situation can even sometimes be assessed by having a look around.

The move toward an intangible economy makes things more complicated. First because things are less and less linear and setting an optimized production planning that matches reality is a very difficult task, if not impossible. Tasks become problems to solve, solutions to find and if average durations can be calculated afterwards, making it a priori as a forecast looks like accomplishing a miracle. More, talking about knowledge work, notions like quantity and quality are closer than ever. That’s for what’s foreseeable (or looks like) and it’s even worse for unforseeable things.

This is a problem that’s both about production performance and management. In this problematic, our modern tools, even if they are a part of the solution are also the cause of new issues that are far from being trivial. [Read more...]