Is your organization Task-Driven, Data-Driven, Experiment-Driven, or Learning-Driven?

I’ve worked in over 10 companies in the past 10 years. Interestingly, each company was “driven” in different ways.

But first, what do I mean by “driven?” To get insight into what is driving your company, ask “How will we achieve our goal?” If it’s through data, then you are most likely data-driven, if, through a lot of hard work, you are most likely task-driven, if by learning quickly you are most likely learning-driven.

Over the years, I found that there are good ways and not so good ways to drive a company. I also found that each “driving” method is built on top of each other and yet overlapping. I’ll explain this more in detail as I lay out each method.

So at the bottom of the pyramid is Task Driven. This is when employees pride themselves on completing a bunch of tasks. Never mind how each of these tasks will impact the numbers. Never mind where each task lies in relation to the overall big picture. Hustle and get a lot of work done. But there is a positive side to this and that’s the hustling mentality. If you are Task Driven to such an extent that you are hustling like crazy, then you can move on to the next “driving mode.”

Next is Revenue Driven. The majority of big companies are Revenue driven. Before completing each task, you ask yourself, “How will this impact our revenue?” While task-driven companies ask themselves how many tasks they completed, revenue-driven companies prioritize tasks that have the greatest impact on revenue. You are now looking at the big picture and measuring the impact of tasks. Now, your organization can grow much better. Why? Because now employees are focusing on work that will give us more revenue. But there is a big downside. You become nearsighted. You can never look too deep into the far future and think “How can I really grow the company?” You always need to perform now. So you end up sacrificing a lot of things and sometimes even the brand and the users. But if you learn to prioritize tasks in relation to the big picture, you can move on to the next phase.

Data-Driven. Not only are you now looking to drive revenue, but you are also looking at the underlying reasons behind the growth. You realize that Revenue is the result and data is the reason. If you can master the reason, you can master revenue. You start making decisions based on data and start working in order to get data. Before you were working only to get more revenue. Now data seems to be more important for growth. This is, however different from being Experiment Driven. You can be data-driven, but not be Experiment Driven. You can look at data and base a lot of your decisions on data but not run a single experiment.

You become experiment-driven when you realize the limitations of data. How can you know that A was really better than B? You need to prove it and make sure it’s statistically significant. You realize that the speed of testing is important so you start doing as many experiments as possible. You are thinking “how can I improve this by x percent?” You are searching for answers, much like a blind man throwing a bunch of darts (experiments) hoping it will hit the bullseye. You don’t know what will hit, so you just need to throw as many as possible. The downside? You’re improving the numbers but not learning. What’s the difference? Your primary mode of thinking is

“I improved it by X percent.”

It should be

“I learned that Hot Pink has X percent better conversion.”

Why? Because the latter is Learning-Driven. If you learn that Hot Pink is better for ads, then you can form a follow-up hypothesis and make Hot Pink your CTA in your app or website. Before you were throwing a bunch of darts hoping it will hit, but now with each dart throw you are getting closer to the bull’s eye. You learn from one experiment. If it’s a success, other departments pick up the lessons and can implement it. Growth now starts stacking on top of each other as learnings start to stick. Your organization knows what it learned in the past quarter, month, week and is excited.

Learning driven has extreme benefits for motivation. When a room full of children were told “figure this puzzle out and we’ll give you x dollars” they quit pretty quickly. However, when they are given the learning frame of mind and told “let’s try to figure this out. How can we get this to work?” their intrinsic motivation was much higher and they kept on the task twice as long.

In a learning-driven organization, failure is welcomed. You learned something and that’s more important. However, in an experiment-driven organization, unless you grow the metric by x percent, you feel like a failure. If you fail enough times, you become demotivated. Ideally, a learning-driven organization is much like a playground. You are free to experiment and learn and as a result, grow the company.

Lastly, there is the User Learning-Driven Organization at the top of the pyramid. Instead of thinking

“Hot Pink works”

You are thinking

“Our users like Hot Pink.”

Seems like a small difference? Think again. Before, while you’ve learned that Hot Pink works, you didn’t really connect it to the user. Your main question wasn’t “who is our user, what’s her needs and preferences” but you were learning on how to drive the metric up. And in doing so, you’ve most of the time, alienated the user all together as a bunch of metrics. But in a User Learning Driving Organization, it’s different. You are asking about the user. You are experimenting to discover the user. You are learning about the user.

This is an enormous leap. If the marketing team finds that your users love the outdoors, the product team can implement this learning to the product. Now, Learnings are stacked on top of different teams. As obvious as this sounds, usually, in a learning-driven organization marketing team will never say “our users love the outdoors.” They will say “hiking images lifted conversion by x percent.” The product team will most likely see no way to put in hiking images in the current product, and the learning becomes a dead end. But, if you connect to this user, it’s a drastically different story. The product team will be like “If our users like hiking, maybe they are active people with a lot of energy? Maybe we should have stronger and faster animations?” Do you see how far the product team went from just “hiking images.” Of course, they will test this out with a/b testing, but this hypothesis will have a higher likelihood of success than just throwing random experiment after experiment. The difference in anchoring an experiment on the user and solely on metrics is an enormous difference, to say the least.

When startup leaders like Paul Graham say “focus on your users” I used to think, duh? After 10 years in the startup industry, I think the advice is worth a million dollars. It’s like a restaurant owner who says “focus on cleanliness” or a teacher who says “love your students.” The insight is unfathomable until you actually get it.

You are building a product for users. Not metrics, not revenue, not experiments. These will all follow when you learn about your users. Learn who they are. Learn what they like. And then implement that learning to every department. Use the hustling mentality, data, experiments, and learnings for your users, not for revenue alone. This will give you at least a startup that is generating $10 million a year.