Evolving into a data-driven organization has gone mainstream over the past 10 years. Roughly half of companies say they’re using data to drive strategy, and most admit to stockpiling data and reporting on it. In fact, it’s almost become difficult to get away from data.
Nearly every application comes with an analytics tab. Implementing tracking on products, campaigns, processes and digital experiences has become easy as copy-paste. Our iPhones even report back to us how much time we spend on them.
But success doesn’t come from looking at data; it comes from failure — and using data to experiment until you get it right.
When something doesn’t pan out, data won’t tell you what the pitfall is — or how to get over it.
Yet, it will call your attention to a specific area, pointing to it like a blinking neon sign that says, “look here!” And that’s when you take the reigns and try something new. Data can also tell you whether your solutions are working (the blinking neon sign then reads, “getting warmer!”) and when you’ve taken a turn toward getting it right. This is called experimentation.
As Google’s global head of customer analytics Neil Hoyne points out, time and again, companies make “crushingly common mistakes with data, and refuse to give themselves the room to experiment and to fail.”
For data-driven organizations, it’s a required skill set to turn the data you see into lessons you learn. It’s a fast-moving discipline that requires hands-on attention and a full-court press.
While different practices, from UX to product development, ops to growth marketing, have their nuanced approaches to experimentation, we’ve outlined a straightforward framework to help your organization harness the power of data with true experimentation.
Keep in mind, when we say “solution,” it doesn’t simply apply to technology solutions. It can. But it can also be testing new email campaigns or website designs, better open enrollment processes or troubleshooting inefficiencies in accounts receivable.
Consider this example: Testing a Solution for Better New Employee Onboarding
Experiments don’t need to be big to be successful — or a well-earned failure. They just have to happen. So, stop stockpiling and pushing around data that isn’t getting you anywhere. Decide first what you need to revolutionize, how you’re going to measure it, and how quickly you can fail.
When you need guidance on how to take that turn toward getting it right with data or setting up the first experiment, we can help you stand apart from the crowd.