From Guesswork to Growth: How to Engage with Uncertainty

Bold new initiatives have built-in uncertainty, where the best direction forward is often unclear and unproven. Strangely, most organizations don’t address this uncertainty head-on, but instead prefer to over-focus on a single direction with grit and perseverance, or conversely, get stuck in endless research and debate and never make meaningful progress.

Both of these strategies try to treat uncertain initiatives as if they were traditional, more predictable efforts, where being “wrong” is to be avoided, and making progress can’t happen without long-term commitment to a single direction. These approaches inevitably use up the precious time and resources we have, don’t teach us what we need to know, and don’t reliably get us to successful outcomes.

To effectively navigate the uncertainty associated with bold new initiatives, we need to adopt an approach that embraces uncertainty instead of avoiding it; by moving quickly before feeling confident, pursuing ideas with humility, and prioritizing learning to inform evidence-based decisions. This strategy acknowledges uncertainty and leverages our limited time and resources to resolve key questions and make a team smarter, faster.

Helping your organization manage uncertainty is not done by simply snapping in new processes, frameworks and tools, but by adopting a key set of principles-based behaviors. Your aim should be to understand, evaluate and reinforce these behaviors.

Here are five principles-based behaviors we've come to understand deeply that are required for moving away from a traditional, linear approach that works well in areas of certainty towards a more adaptive, iterative approach for when we’re facing dynamic problems with high degrees of uncertainty.

Principle 1: Learn Through Quick, Early Action

From this:	To this:
Getting stuck in internal debate	Avoid debate by identifying uncertainties and resolving them through evidence-driven discovery and testing activities.
Show our solutions to outsiders once they are “done”, so we’re safe. Sharing things too early might signal incompetence, premature commitment, or arrogance.	Show our work to outsiders as quickly as possible in order to get feedback and drive better solutions. Set expectations and carefully consider the impact of testing, so we’re safe.
Investing in formal research before moving forward	Moving quickly on hunches and testing, discovering and de-risking ideas along the way to help set direction
Ensure we do our homework and get agreement before proceeding.	Have a strong bias towards action. “Rough draft” thinking drives the best learning, permits the organization to move quickly and ensures the most runway possible for evaluating and improving what works.

Principle2 : Use Short, Repeated Iteration

From this:	To this:
Relying on significant up-front planning to build internal confidence	Use repeated, short iterations (days/weeks, not months) to generate evidence and replan based on what we’re learning so we’re confident we’re headed in the right direction
Work until we’re done as defined in our plan.	Timebox our efforts. Work until we run out of time and then evaluate our interim efforts using objective measures, and start another iterative cycle with a new plan, otherwise we’re over-investing in diminishing returns.
If we want to resolve uncertainties, we should invest in a test that is meticulously designed, reflects empirical best practices, and puts our best foot forward with a comprehensive solution.	The best way to resolve uncertainties is to not over-invest in any one test, otherwise we risk creating something so big it can’t fail. Instead, focus on lowering the stakes so we feel comfortable moving quickly, being OK with being wrong, and providing the space and time to run many imperfect tests designed to make us smarter.

Principle 3: Orient Around Learning

From this:	To this:
Seeing building and executing on things as we imagine them as progress, evaluating projects on the volume of outputs and activities and reaching our predetermined outcomes on time and on budget.	Seeing learning and making evidence-based decisions as progress, evaluating projects on their outcomes and not on outputs that may have little or no meaningful impact.
Consider learning as an afterthought, once we’ve completed the project.	Be disciplined in our approach to learning early and repeatedly, through planned and deliberate steps, like identifying questions up-front and instrumenting our efforts for measurement

Principle 4: Stay Objective through Evidence-based Decisions

From this:	To this:
Working on a project means a commitment to pursuing this idea to completion	Working on a project means a commitment to generating evidence in order to pivot, persevere or perish
Reach decisions through consensus or HiPPO	Reach decisions through evidence created by small teams with autonomy

Principle 5: Operate with Humility and Openness (While Staying Committed to our Vision)

From this:	To this:
Assuming we’re right and not getting distracted by outside opinions so we can stay on track	Assuming we’re wrong, and trying to reveal and test our assumptions based on their impact and uncertainty
Falling in love with the solution	Falling in love with the problem instead of the solution
Failure is to be avoided. If failure happens, move on quickly to minimize the damage.	Intelligent failure is accepted and even pursued. Continuous, deliberate and objective recognition of what’s not working is a critical aspect of success in the face of uncertainty.
If we run a test, it’s to validate or pilot our imagined solution.	A validation mindset tries to prove we’re right and reinforces confirmation bias. Instead, tests should be designed to reveal flaws and test assumptions so we can avoid wasting resources and time and more quickly get on a path to successful outcomes. Waiting to test our ideas until a pilot is too late.
Avoid unreasonable ideas, challenges to the current direction and team conflict so we can stay focused and be harmonious.	Invite unreasonable ideas, challenges and healthy team conflict so that we can ensure we’re being objective, getting smarter and increasing our chances of success.

To ensure our organization’s success, it’s necessary to pursue uncertain directions towards unclear outcomes. To do this efficiently and effectively, avoid tools and frameworks that promise a quick fix. Instead, focus on shifting your organization’s behaviors away from traditional practices that work well in areas of certainty, and towards this set of five key principles and their associated behaviors. These principles address the discomfort of uncertainty by helping develop a learning and discovery mindset and achieve real outcomes through quick, evidence-based and open-minded action.

Coaching Others Through Learning Loops

The key to helping others see and experience the benefits of a Learning Loop is to guide them through a small initial loop of their own and use structured questions to encourage effective loop design and meaningful reflection.

Effective Learning Loops consist of four deliberate steps: Planning, Doing, Checking and Adjusting.

Planning: Determining where you’re uncertain - particularly on project next steps or around an idea you’d like to try, or simply an area where you’d like to get smarter.

Sample coaching questions:

• Where are the uncertainties you’re currently facing with the project - for example, thoughts about how to proceed that are untried or untested, or a lack of clarity on how to achieve your desired outcomes.

• “What do you have to do next on this project and what’s holding you back? Is there an area where you’re stuck or where the next step is unclear or unproven? A problem you’re trying to solve?”

Doing: Identifying and executing on a meaningful effort to try.

Sample coaching questions:

• What's one small thing you might try next to help you learn?

• What specifically might you do with your target user/customer to better get at the truth? Is there something you might show them to get feedback on, or ask them to commit to?

• What are you hoping to learn by running your loop?

Checking: Pausing and objectively reflecting on what was learned.

Sample coaching questions:

• Where has your understanding changed? What do you know or believe now that’s different from when you started your loop?

• What surprised you?

Adjusting: Ask yourself how you should respond differently now that you have new knowledge.

Sample coaching questions:

• What does this mean for you moving forward? What will you do differently moving forward?

• How might you make the next loop smaller, faster, easier or more creatively reveal the truth behind your uncertainty?

The Illusion of Explanatory Depth

When trying to figure out if an innovative idea is going to work, it's common to see the situation as pretty straightforward and not question our current understanding. Turns out, there’s a weird human quirk that explains this called the “illusion of explanatory depth.”

Simply put, the illusion can be described as: thinking we understand something when we actually don’t, and it’s particularly strong when we’re faced with something conceptual or nuanced, like a thorny business problem or a novel solution approach.

Researcher Rebecca Lawson designed an experiment to highlight this phenomenon. She asked subjects to draw a picture of a bicycle, showing how it works - connecting all the bits in the way they should be connected. Turns out very few people could do it correctly, yet virtually everyone claimed to understand the way a bicycle works before they were asked to actually explain how it works.

When first imagining an innovative solution to a tough problem, we typically don’t invest in trying to learn more, because - like the bicycle - we simply don’t recognize that our understanding is limited.

In the case of a novel innovation, the problem and solution appear to be straightforward because we’ve never encountered it before in a way that exposes the critical elements, the key subtleties and the characteristics that matter. We haven’t had our illusion questioned. And when our illusion isn’t questioned, we run the risk of thinking we have all the answers and blazing forward with a mistaken approach.

The secret to overcoming the illusion of explanatory depth is to confront ourselves early with assumptions that might lie behind the problem and solution - how do we know the problem is important enough to solve? Are we targeting the right customer? Will users embrace our solution approach?

Even better, run a small test that reveals new information we didn’t know earlier. This new information can challenge our early explanation and show us that our understanding is limited.

Like being confronted with a sketch of a bicycle that doesn’t make sense, new information can shatter our illusion of deep understanding.