Wednesday, December 21, 2011

Becoming a Lean Thinker - Part 4

The "Becoming a Lean Thinker" Series is an account of your friendly neighbourhood Strategic Planner's transformation from a predictor to an experimenter - and my ongoing attempt to apply Lean Thinking to aspects of business, marketing, and even life!

So far, Part 1 covered the beginning of my journey, Part 2 spoke to the benefits of "Reducing the Feedback Cycle", and Part 3 took an idea "From MVP to Scalability". In the Final Part of this series, I'll share with you the last stage of my transformation - from a Strategic Planner to "The Eternal Experimenter"...


The Eternal Experimenter

Experiments. They are, and have been, a key part of the marketing and strategic planning practices for a very long time. Only that they haven't really been experiments in the true sense of the word. Today, when marketers and planners think about experiments, they think about "testing" - testing finished or near-finished creative ideas in environments that are meant to recreate real-world situations and experiences. Perhaps an ad is shown to someone within the context of a mock web page. Perhaps a focus group is walked through a series of storyboards, the moderator attempting to make them picture themselves watching a real ad, in the comfort of their own homes.

This experiment - or test - is different than the type of experiments that one will conduct when they're a Lean Thinker on two fronts: (1) Their objective; (2) Their context. First their objective: these tests are meant to predict real-world behaviour, not learn from it. The goal is to gauge the reactions of our audience in order to gain a better understanding of how the idea might work in market - these tests help us determine whether our prediction could be right, or whether it needs more work, before seeing the light of day. If Qualitative, the learning helps us reframe our idea or series of ideas and revise them to improve the chances of our prediction. If Quantitative, there's often a score - red light, yellow light, green light - that helps us predict - "with certainty" - how the idea will perform.

This takes us to point two, the context of the experiments. They're not conducted in the real world, with our audience in real-wold situations, making real-world decisions. In many cases, we make many efforts to replicate that real-world experience (ie. facilities that recreate the aisles of a store for test subjects to walk through), but it still isn't the same. This reinforces the fact that we're learning in order to help us make better predictions about the real world, rather than learning in the real world itself.




Lean Thinkers approach experiments in a completely different way. With the help of an MVP, their goal is to enter the real-world as soon as possible with an idea or product and learn from real-world behaviours. Part 3 in this series covered the "Build" part of the experiment process, but once that MVP enters the real world, the "Measure" and "Learn" part of the process begins, and things really start to get interesting. Since you're in the real world, approaching experiments in this way takes a bit of courage. But executing first and then experimenting is one of the major tenets of Lean Thinking.

For one, it helps you learn from real audience reactions. As Ries says in The Lean Startup, it's about "offering customers the chance to try something and then measuring their behaviour." It's not random, however. Experimentation begins with a hypothesis: a prediction about what effect a certain action or change will have. The test then validates or invalidates that hypothesis, based on a measurable and meaningful metric. Only when a experiment - a hypothesis about how an audience will react to an idea, product, or feature - has been conducted and measured successfully in the real world can it be said to be "validated".

Real world validation is another key part of the measurement process - it tells us whether we are on the right track and ready to either continue the experiment or scale, or whether we need to go back and modify the idea based on what we've learned. For example when tweaking their initial MVP, Ries wanted to learn which features would benefit the product and which would have no effect, or worse, detract from the experience. “The proof did not come until we put those theories into practice and built subsequent versions of the product that showed superior results with actual customers.” One of the key methods for testing ideas in the real world that Ries describes is A-B Testing. For example, whenever a hypothesis about a new feature or update was being tested, new users were split between two different versions of the site - one the original, the other revised. Based on the measurement and comparison of metrics that specifically link back to the hypothesis (ie. time spent), they could validate that the new version of the website actually improved the customer experience.



Once the performance of the idea, product, or feature that you've built has been tested and measured in the real world, the next step is to reflect on what you've learned. Have you "validated" your original hypothesis? Even if it worked, did it do so because of the reason you intended, or for some completely different reason altogether? If it wasn't validated, why was that the case? Did you make an incorrect assumption about the idea, the audience, or even the context? Learning about the reasons why an experiment worked or didn't work is essential in helping with the next phase of the experiment, which actually takes you back to the beginning of the process - Build.

Only this time you're no longer in the Build phase, you're in the Adapt phase. Revising something you've built - whether an idea, product, or feature - based on previous learning is just like adaptation. You're changing based on what you're learned, in order to increase your chances of real-world success. Adaptation brings us back to the idea of Kaizen - continuous improvement. As Ries describes in his book, this adaption doesn't have to happen slowly, it can happen extremely fast, so fast that an idea or product can be said to be rapidly evolving: "We change the product constantly--much too fast by traditional standards--shipping new versions of our product dozens of times a day." It sounds like a beast, a Chimera, constantly mutating and evolving based on the changes and reactions from its real-world environments, adjusting itself in order to remain on top of the food chain.

There is one caveat to being an experimenter, and it's a big one: you have to be flexible. If you haven't given yourself the leeway - whether through time, money, or resources - to continue to change and modify the idea, product, or feature, you won't be able to adapt. You'll be stuck. This lack of flexibility is typically the key barrier to becoming a Lean Thinker and practicing it in the real world. Not having enough time to change something, not having the money to change it (or having committed that money to something that can't be changed), or not having the resources to make change happen, reduces the flexibility that you have and forces you to stick with the original idea. Which means that whether it works or not becomes a major issue - if it doesn't work, you're going down with the ship! By making an extra effort to improve your flexibility and reducing the pressure of time, money, and resources, you'll be able to continue the experiment and find the right path to success - in business, marketing, and even life.



Conclusion

As I've written this series, I've realized a few things, both about Lean Thinking and about the best way to apply that thinking to my life.

First, Lean Thinking can be applied anywhere. Whether at work, in the gym, in the kitchen, or even in your inter-personal relationships, there are always opportunities to reduce the feedback cycle, go from MVP to scalability, and to become an eternal experimenter. Rather than approaching situations as a Go - No Go, Pass - Fail, one-time opportunity, or as a path that must be committed to for the long-term (no matter how it plays out), you can approach situations with an open mind, and the willingness to experiment. That part of my lesson was mind-blowing.

Now here's the more sobering part: it doesn't always work. Some situations, some contexts, call for more thought. They call for Strategic Planning in the traditional sense - doing lots of up front thinking in order to mitigate against defeat or failure. And so the lesson that I've learned is that it really isn't about being a Lean Thinker 100% of the time, it's about finding the right balance - between Lean Thinking and Strategic Planning - that gets the job done.

And with that, my journey was complete.

  • Reducing the Feedback Cycle
  • Going from MVP to Scalability
  • The Eternal Experimenter

No comments:

Post a Comment