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Dispelling the Myth That It’s Difficult to Experiment in an Enterprise Environment


It’s not news that fostering a culture of experimentation brings enormous benefits. When teams embrace testing, they’re more innovative, agile and in sync with ever-changing customer needs. Experimentation also reduces risk, because teams know how the product will be received before it’s rolled out. As a result, they see increased profitability and customer satisfaction.

Yet even if they understand the value of experimentation, some enterprises hold back because of some common concerns. I want to assure you that these concerns are mostly myths. Not only do they lack any factual support, if you look beneath the surface, they’re founded on a fundamental fear of change. Below, I’ll provide my perspective on how you can build a culture of experimentation that scales with your company.

Three Common Myths About Experimentation

Conceptually and philosophically, leaders understand that they should embrace experimentation. Yet many are quick to dismiss experimentation as needlessly complex, expensive and risky.

Myth #1: Experimentation Is Expensive (It’s Not)

A common misconception is that product experimentation will require a whole new suite of tools — and possibly a whole new team of highly paid talent — in order to modernize systems and overhaul workflows. The assumption is that this requires substantial investment.

In reality, there’s no reason why teams can’t adopt some simple tools to start experimenting today. As long as you can test new features in a production environment, control how quickly or gradually you release them, and easily roll them back if an A/B test goes sideways, then you’re good to go.

Myth #2: Testing Poses Business Risks (It Doesn’t)

Some leaders may assume that A/B tests and other forms of experimentation are liabilities. They fear losing customers and revenue due to poor experiences, bugs and system outages. But this assumption badly underestimates the robustness of modern experimentation platforms.

A proper experimentation framework lets you mitigate risk by managing every aspect of the code you deploy. Progressive delivery staggers feature releases so you can fix bugs and change what customers don’t like. Having a kill switch lets you instantly disable a feature that goes awry. And performance metrics help you continuously gauge what’s working and what’s not.

At the end of the day, every business is taking risks all the time. When you have a strong methodology for experimentation, it supplies a safety net so that your developers can diagnose issues and test bigger, bolder ideas without worrying about breaking things.

Myth #3: Iteration Slows You Down (It Shouldn’t)

I’ve also heard peers express hesitancy because they worry experimentation will slow them down. If they take time to test features before rollout, they fear it will add an unnecessary step.

But in fact, it is necessary. Experimentation enables you to view everything you do with data — which lets you make better decisions at the outset. By catching mistakes early, you massively reduce both your time to market and your time to value.

The Real Reasons for Business Leaders’ Reservations

These myths make for comforting stories that organizations tell themselves. It’s easier to believe you can’t experiment rather than you won’t experiment. But none of them offer a compelling explanation for why some organizations hold back on testing.

A better explanation is that embracing experimentation forces us to shift our mindsets, break our patterns and be comfortable with ambiguity. And that’s not easy for a lot of leaders.

At the executive level, being open to experimentation means being open to the reality that the data may defy your expectations. For business leaders who want to take decisive action, it’s difficult to know what to make of an experiment that increases margins but lowers customer satisfaction, or that yields no easy conclusions after a lengthy trial. But true leaders need to be learners, ensuring that documentation, categorization and metrics are in place to guide genuine data-driven decision making.

That brings me to the organizational level: being open to experimentation means change management. Leaders can move the needle on culture change, but the actual experiment takes place with employees who need to adopt new processes and best practices. Here’s how to do that.

With The Right Processes in Place, Scale Follows

There are three things leaders should do in order to transition their organization towards a culture of experimentation and scale their efforts:

1. Establish a Center of Excellence

There will be people in your organization who are well-positioned to drive new initiatives and implement improved experimentation processes. Empower them to form a core team that defines best practices and decides what further tools and tactics are needed to carry your culture of experimentation forward.

2. Start With a Single Business Unit

Organizations with a strong approach to testing often begin with a center of excellence that has a keen understanding of a single product line or business unit. It’s okay to start small. Once systems and processes for robust testing are embedded, that center of excellence can either expand to serve multiple business units or be replicated elsewhere in the organization.

3. Make the Most of Strong Metrics

A successful approach demands data-driven decision making and rigorous tools that allow you to amass the most reliable, clean and complete information possible. Without these, your experimentation framework will be built on a faulty foundation. Above all, you need to have the ability to measure impacts. Executives are looking at revenue, conversions and customer satisfaction; engineers are looking at the quality of code and data. Demonstrate success — and celebrate failure — by being able to connect all the dots and show where correlation does indeed imply causation.

With tools that let you run experiments and collect clean data, along with a center of excellence and executive buy-in, the barriers to implementing and scaling an innovative, iterative culture aren’t so large after all. The main obstacles to overcome are the fear of disruption and the fear of being wrong. And while these may be deeply rooted in human nature, it’s also our nature to be curious, inventive and to continuously build on our success.

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