What is Experimental Discovery?
Seeking better results in an ever-evolving world by continually experimenting, learning and improving. This stands in contrast with rigid grand plans or plunging into something new on a large scale.
Experimental Discovery encourages us to:
Be thoughtful about which hunches we follow and how to explore them.
Be disciplined in our experimentation while staying curious and creative.
Use what we learn, whether expected or unexpected, to take appropriate action.
[Experimental Discovery] leads to new knowledge that brings about change, even if our assumptions or hypotheses are disproven.
Principle in Brief
As commentator George Will reminded us: “The future has a way of arriving unannounced.” In our rapidly changing world, competitors are constantly improving, and what customers value is constantly changing. No matter how superior a company’s knowledge, products, and services, it cannot stay in business unless it makes improvements and innovations at least as fast as its most effective competitors. Doing this successfully requires that a business apply Experimental Discovery and Creative Destruction to its vision, strategies, products, services, and methods. All businesses must continually innovate, which usually involves numerous changes in direction, leading to the discovery of new paths.
Progress — whether in business, an economy, or science — comes through experimentation and failure. Those who favor a “grand plan” over experimentation don’t understand the role that failed experiments play in creating progress in society. As Einstein supposedly said, “Someone who has never made a mistake has never tried anything new.”
Such failures can effectively signal what doesn’t work. When dealt with quickly and efficiently, they minimize waste and redirect scarce resources to what does work. A market economy is an experimental discovery process in which business failures are inevitable. Attempts to eliminate any risk of failure only ensure greater failure.
For Experimental Discovery to work, we have to design experiments properly and recognize when we are experimenting, so we can learn and limit the bet accordingly. Koch companies have suffered whenever we didn’t recognize we were experimenting and made bets as if the risks were small when they were not.
Since the future is unknown, we can never predict with certainty which investments will be profitable. To drive Creative Destruction, we encourage numerous well-designed experiments to determine which new businesses, products, services, processes, methods, or type of organization will be successful. We also limit the size of experiments by considering the risk and magnitude of gain or loss.
A well-designed experiment starts with a hypothesis and the goal of learning whether it is valid. If done properly, it leads to new knowledge that brings about change, even if our assumptions or hypotheses are disproven. We learn even more when we explore a range of possibilities that includes the areas of greatest uncertainty and potential.
Confusing as it might seem, failure and getting results are not mutually exclusive. As Einstein is believed to have observed, “Failure is success in progress.” A failed but well-designed experiment is valuable if it generates lessons that lead to positive results. A true failure is a failure to learn because of poorly planned or impulsive action.
To encourage Experimental Discovery, we don’t penalize well-planned experiments that fail since they fuel the necessary flow of small and frequent bets that generate discovery and learning. This is vital to innovation, growth, and long-term profitability. It is also motivating, as experimenting to discover new ways to create value makes work more interesting and exciting.
Understand It Better
Videos to Explore
Examples
We use experimental discovery to explore the unknown and figure out what to do with what we learn along the way. These four types of questions can help you on your journey of discovery.
Example 1:
In a production meeting, Jada shares that inventory numbers on their daily report are consistently different from their actual inventory. The team has a hunch that their systems aren’t syncing because of some older technology that might need replaced.
Questions that describe potential ways to test ideas or uncover insights we want to learn.
Cheryl asks, “What if it’s not a system issue? Is there a way to rule out that systems are at fault?”
Questions that prompt us to establish what we will explore and measure before start.
Cheryl suggests, “Let’s set up an experiment where we create a few fake orders and follow them. That might tell us where the break is.” She works with people from each department to track the fake orders through the system to see how they show up in inventory numbers.
After our experiment or exploration, what do the results tell us? Did it work? Not work? Reveal something unexpected?
The experiment reveals that two departments are using different part numbers for the same product, causing the numbers not to match. It wasn’t a technology issue after all.
After an experiment or exploration period is over, we use the knowledge gained to determine what to do: continue, adjust before continuing, or stop.
Now that they know what causes the issue in their reporting, Cheryl can account for it with a simple spreadsheet formula. No system upgrade is needed at this time.
Example 2:
It is difficult for new employees to get the practice they need to learn the press machine because it is always in use.
Questions that describe potential ways to test ideas or uncover insights we want to learn.
Adama, the person responsible for training new employees, asks, “Do new employees need the whole machine to start learning how to use it? What if we just start off by training them on the main control panel?”
Questions that prompt us to establish what we will explore and measure before start.
Adama proposes building a mockup control panel from spare parts to train new operators on the layout and order of operations before they work on the real panel.
After our experiment or exploration, what do the results tell us? Did it work? Not work? Reveal something unexpected?
The prototype allows Adama more flexibility than expected. He can add additional labels and instructions to the control panel and be more hands-on with new employees than he could if they were training on the real panel.
After an experiment or exploration period is over, we use the knowledge gained to determine what to do: continue, adjust before continuing, or stop.
Because it was so easy to build a practice version of the equipment's control panel, Adama recommends fabricating a few more. Now he can train multiple people at a time, and even present specific scenarios for them to practice working through.
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Connection to the Five Dimensions
Here’s how Experimental Discovery shows up in the five dimensions:
- Vision Dimension — experimental discovery guides how we innovate and transform to maximize our long-term success.
- Knowledge Dimension — continual learning is at the heart of the Knowledge Dimension, and we learn quickly through well-designed experiments.
Give It a Try
The power of these principles happens through application. There’s no substitute for learning as you apply.
- Think about some ideas and questions you’ve had recently. Work with others to think through running an experiment to explore one of the ideas.
- Organize a “discovery session” where team members can share unexpected results or lessons learned from recent work.
- What is a fast-changing aspect of your industry or profession? Identify ways you/your team can take an experimental approach to handling these changes.
- What are some “What ifs...?” that you could easily explore with your team? What do you need to get started?
- Consider an experiment where the hypothesis is disproven. Does this mean the experiment is automatically a failure? Why or why not?
- What examples can we share where an experiment or test stopped us from over-investing in something?
- How do we ensure we’re open to unexpected results and willing to adjust our thinking based on what we discover?
- Where are we overconfident in our predictions about the future? How might experimental discovery help?
- Consider a recent decision or action. How might the results have been different if we had taken an experimental approach?
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