It’s no secret that we are living and working in complex, unpredictable times. Accepting that is one thing, but what we all want to know is how to deal with it. By definition there are no longer any “best practices” that can guarantee success for an organization; there are only good practices that we can stumble upon through experimentation. Add to that the fact that success in itself is a continuously evolving state, and you have to wonder, “How do I lead in an environment like this?”
Experts like Frederick Laloux, author of Reinventing Organizations, Brian Robertson, founder of Holacracy, and Stan McChrystal, author of Team of Teams, are pointing to radical transparency and information sharing, more fluid organizational structures and roles, and decentralization of authority as key components to success in this new world. But if prediction is impossible, best practices are fleeting, and authority is distributed, it can start to feel like decisions are being made at random. And that’s not an idea that we are naturally comfortable with.
Before panic sets in, let’s try to look at this in a positive light. To quote John Mayfield in The Engine of Complexity: Evolution as Computation, “Randomness is the [only] source of anything truly new.” From this point of view, randomness should be a great thing for your organization! In a world that is constantly changing, new ideas are a critical component of success.
So the real question isn’t “How do I remove unpredictability and randomness from my business?” It’s “How do I deliberately make and structure decisions to increase the chance that novel ideas or outcomes lead to improvement?”
There are a number of approaches from different disciplines that can point us in the right direction for answering that question. Below are three that we have found to be especially helpful.
Evolution as Computation: Tweak what’s working through minor random mutation
Not knowing what to do next doesn’t mean taking a huge leap is the move to make. When faced with having no idea where improvement will come from, start with small experiments on what you currently have. To quote Mayfield again, “Small improvements are usually not at all improbable.” Put another way, your best bet for an improvement is to make slight tweaks to what’s already working. Reducing the scope of experimental decisions gives you two benefits. First, you can more easily identify what contributed to either success or failure. A “no that didn’t work” provides you and your team just as much information as a “yes.” Second, it increases the probability that the output will be positive. Reducing the number of possibilities for outcomes— a “yes” or “no”, “either/or” etc. — makes your chances of a positive output closer to 50/50. Accumulate the positive and learn from the negative.
To clarify, this doesn’t mean reducing the scope of responsibility of your team or slowing down progress. It means structuring the many decisions that should be happening within a certain area of authority so that you can quickly glean specific insights from them — use A/B testing, work in sprints and get feedback, set short-term milestones and evaluate success or failure. Practices of continuous steering and iteration, like Agile and Lean Startup Methodology, have sprung up in popularity in the past few years because they take advantage of this principle. They allow you to systematically achieve larger improvements than would otherwise be possible in a shorter timespan. Look for ways to apply the same “test and learn” approach to your own business.
The Multi-Armed Bandit: Explore and exploit
Once you have identified decisions and practices with positive outcomes, the challenge becomes deciding when to continue using a practice you know works and when to see if there is better option that is fundamentally different in its approach. This is where the concept of explore and exploit comes in. The dilemma of how to prioritize exploiting what is currently perceived as providing the best return vs. exploring unknown possibilities is not a new one, even if it is exacerbated greatly by the speed of today’s environment. This dilemma has been discussed at length in the realm of probability theory, and is the core issue in a traditional probability problem called the multi-armed bandit.
Boiled down, the problem is this: You are faced with a row of slot machines. You don’t know which machine has the overall highest payoff, so you have to just start playing, learning, and continually identify which machine has the highest expected payoff based on the information you’ve gathered. Before each subsequent pull, you must decide whether to exploit the machine that currently has the highest expected payoff, or explore to get more information about the expected payoffs of the other machines. Either choice is a trade-off. Playing the machine with the current highest expected payoff sacrifices gathering information about what could be a potentially higher return, but exploring, while it provides valuable information, could give you a lower return than the current optimal choice. Sound familiar?
The key is to exploit the option with highest expected payoff while continuing to explore for better options.
The answer is to allocate your team’s resources to exploit what currently gives high returns without making the mistake of halting exploration. In a world full of uncertainty and randomness, complacency with current practices guarantees certain failure. Remember that even decisions with low returns today provide you valuable information in determining what could lead to higher returns in the future. Make uncertainty your competitive advantage by exploring and learning from it rather than letting it be the reason for your failure.
Agile Mind: Switch between the big picture and the small to integrate outcomes
As mentioned in the previous two sections, iterative and exploratory decisions are key to larger, systematic improvements. Equally important, though, is the integration of those lessons learned into a coherent direction for your team. Many improvements in wildly different directions isn’t very helpful for driving organizational success, and success isn’t static. It should be continually reassessed with new information in mind. Doing this requires adeptly transitioning between thinking on a small, tactical scale to thinking on a larger and more abstract one. Agile Mind by Wilma Koutstaal, argues that we are optimally creative when we skillfully move across all levels of cognitive control and detail.
You will best be able to take advantage of randomness and exploration if you and your team look at outcomes on a small scale and then integrate them with your larger strategy.
Lessons from day-to-day decisions should continually filter up to inform and shape new, creative strategy just as strategy should continually inform the direction of lower-level decisions. Create this connectivity through pushing down high-level context about things like strategy, market conditions, and efforts across the organization (see some tips for doing this in a post by Sam Spurlin here) and creating channels for teams to push up information from day-to-day operations.
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