There are countless examples of well known companies making massive pivots. Amazon started out as an online bookstore. Netflix was once a company that mailed physical DVDs to peoples’ homes. In retrospect, these pivots seem like obvious moves (hindsight and all that). But at the time, these reinventions were massive risks.
For every example of a successful business pivot though, there are hundreds more failures.
Businesses who are too risk averse and fail to pivot can be left behind (RIP Blockbuster), while those who bet all their chips on an idea that doesn’t pan out, go under.
When you own a small business that supports your family, these stakes can feel very high.
So how do we balance risk and opportunity when it comes to new ideas?
We have taken bold risks and made massive moves, and some of them didn’t work. Trying something that doesn’t work is part of life (and definitely part of business) but where we really learned our lesson was the times when we didn’t realize fast enough that something wasn’t working, and we ended up paying for it (in both money and sleepless nights).
Luckily, none of these things put us under; they served as learning experiences and we were able to bounce back stronger. But they DID hurt enough to really drill this lesson home.
Today when we implement a new idea, we do it in a specific way so we can maximize learning and opportunity, and mitigate risk. Instead of spending lots of time on hypotheticals, creating a big plan that’s built on assumptions (the flimsiest of building materials), we now approach change the agile way; by running small tests and experiments.
By running small, structured experiments, we are able to shorten our learning cycles and stay on top of the data around changes so we aren’t caught by surprise. It also allows us to start trying new things sooner. Instead of having to wait until next quarter for a big roll out, we can start moving in a new direction right away with small increments that give us immediate feedback in real time.
- Be realistic about how many things you can change at one time and learn to prioritize
- Base your hypothesis and assumptions on actual data as much as possible
- Create a time box for your experiment that balances time for learning with realistic limitations
- How high risk is this? How long can we afford to let this run?
- How long will it take to truly see results with this? How long before we have meaningful information we can use to move forward?
- Make sure your whole team is fully enrolled in the experiment
- Agree as a group in the beginning what success and failure look like, and under what circumstances you would stop or pivot the experiment
- Regularly review how it is going and what you are learning using as much data as possible
- At the end of the time box, decide as a group how to move forward