While software is eating the world, and whole industries are being created, fundamentally transformed, or swept away to join the makers of buggy-whips, the state of leadership/guidance/management (hereafter ‘LGM’) continues to lag behind. It’s easy to see why, and less easy to see how it gets changed. I have some ideas to share, and look forward to feedback and comments with other views.

One reason leadership lags is history. We have centuries invested in optimizing the practices associated with managing industrial processes, and military processes before those. These fields have little in common with modern knowledge work, but the art or science of modern leadership is still very much in the rapidly evolving stage. Factory design, workflow, task and inventory management, and (recently) Deming, Toyota and others have optimized manufacturing to a fine science. When we apply these methods to knowledge work, we’re rarely successful, yet we persist in trying.

As one starting point, let us consider the difference between tasks that are complicated and those that are complex. Manufacturing methods can handle extremely complicated tasks. They’re characterized by being standardized, completely documented, measurable, repetitive, and intolerant of change or variability. When GE builds jet engines for Boeing airliners, they employ the most advanced version of these methods to handle this extremely complicated task. Every component is machined to as near perfection as can be measured, and assembled in exactly the prescribed order, using the prescribed method, every single time. No experimentation, creativity, or innovation is desired or welcome on the manufacturing floor – or in the air! Changes to this assembly line are made infrequently, and only under the most tightly controlled circumstances, in order to prevent any unexpected variability from intruding. Every pilot wants every engine to have the same ‘maximum thrust’, on every plane of that type, on every flight, and so do the passengers. Use of statistical methods and data-gathering may allow us to accurately estimate the cost and duration of even these awesomely complicated tasks with almost surgical precision.

On the other hand, tasks that are complex have very different characteristics. Their details are often relatively unclear or completely unknown at the outset. Potential solutions to a given problem space may be hypothesized, but cannot be assumed to be correct. These tasks lack documentation, are rarely repeated, and change or variability may turn out to be positive or negative. Accurately estimating these tasks is challenging at best, and maddening (or bankrupting) at worst. Complex tasks include problems that are being solved for the first time, or using new tools and technologies. So called ‘wicked’ problems, whose parameters and challenges may be changed by attempting to solve them (perhaps even by _thinking_ about attempting to solve them!), are also in the complex category.

Just for one example, consider a company that is attempting to provide access to their existing services, using a mobile platform. This project includes efforts that involve every facet of the company’s existing structure and staff, requires adding new elements (mobile engineering, user interface, security, etc), and presupposes a level of communication, interaction, feedback, and healthy conflict that many organizations find daunting. Having a discussion in the company about this project, before it begins, may begin to change the problem by affecting staff behavior, even to the point of departure!

Given the very high risks and rewards of such a task, it behooves us to consider investing in the best leadership/guidance/management practices that are applicable to knowledge work, not simply re-purposing our manufacturing methods.

Being clear about the difference between complicated and complex is key to a discussion of appropriate methods. Like a good crafts-person, we always want to use the right tools for the job at hand. Using manufacturing/complicated tools on a knowledge work/complex task is ineffective, frustrating, and expensive. We owe it to our teams to up our game.