Imagine you want to design a robot that can get through a maze by itself. How might you go about it? First, you would probably define the robot's objective: Find the exit of the maze. Then, Imagine, you would create a mechanism to reward the robot for moving toward that goal and to punish it for moving farther away, so that over time it finds its way out. But what if the robot comes to a dead end right next to the exit? It's geographically as close as possible to its objective but it can't get there. And it won't want to turn around because that would mean moving away from the goal and getting punished. Your robot would be stuck.
Kenneth Stanley is a professor in artificial intelligence who has studied this problem, the stagnation that can result from dogged pursuit of a prescribed goal. Eventually he and his colleagues arrived at a simple solution. What if instead of rewarding the robot for getting closer to the maze exit, they rewarded it for trying new and interesting directions? They found that this shift in programming significantly improved the robots' ability to solve mazes — a successful result in 39 out of 40 trials, versus 3 out of 40. Testing objective-less challenges in many other AI contexts, Stanley got similar results. When made to seek novelty, his robots developed surprising and creative solutions to problems they could not previously solve.
Most modern managers take this as a given. Of course goals should be clear; how can you prioritize work or run a company without them? We have corporate and group objectives (quarterly and annual), project objectives, and individual objectives, and we're reviewed and rewarded for meeting them. At a large bureaucratic company, a typical objective for a midlevel manager might look something like, "Ensure optimal support for assigned projects in line with agreed timelines and priorities." This might be followed by 20 project-specific objectives such as, "Ensure high quality and timely delivery of cross-functional alignment plan for printer firmware update." In today's data-driven world, organizations seem to be more focused than ever on metrics that track progress toward such goals; we all want to know whether and how quickly we are moving toward desired results.
But Stanley's work indicates that our objective obsession might be doing more harm than good, causing people, teams, and firms to stagnate over time. And this view is bolstered by statistics on and stories surrounding invention. Reports indicate that half are the result of not direct research but serendipity — that is, people being open to interesting and unexpected results.
Instead of focusing only on their initial goals, and most likely failing to achieve them, the people working on these projects allowed themselves to take detours, in the process creating different breakthrough drugs and technology.
Outside the R&D department it's hard to imagine an organization or an individual leader greenlighting a project with no goal other than to discover something new and interesting. But this is a mindset shift we all need to make. The more time we spend defining and pursing specific objectives, the less likely we are to achieve something great.