December 2022 - Margy With a Hard G

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?

By new ideas I don’t necessarily mean a massive overhaul like changing your core offering. Something like pivoting your primary lead gen strategy, which could be totally necessary in the face of a changing market, could have a disastrous impact if not approached strategically.

At Interview Connections, we’ve learned this the hard way.

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.

So if there are things in your business you want to change or try, here’s how to set up an experiment:

Be realistic about how many things you can change at one time and learn to prioritize

Most entrepreneurs love shiny objects and new things. We want results yesterday, and sometimes this means we try to change too many things at the same time. While initially appealing, running too many experiments at the same time (i.e. changing too many things at the same time) can cause chaos and sabotage the success of all of your initiatives. Get clear with yourself and your team on how many things you feel comfortable changing at once and the priority of each thing. If everything is priority, nothing is, so getting crystal clear on this is huge. Once you have that clarity, start with the most important experiment first.

Base your hypothesis and assumptions on actual data as much as possible

To run an experiment you need a hypothesis. You obviously believe the thing you are trying will improve your business in some way or you wouldn’t be trying it. There is always going to be a decent amount of assumption in these, which is why we are running the experiments in the first place (to see if your assumptions are accurate). That being said, it’s a good idea to identify in the very beginning what data or vital signs you can track that will objectively let you know if you are on the right track or not.

Create a time box for your experiment that balances time for learning with realistic limitations

Creating a time box on your experiment is huge. The boundaries of a time box increase learning, lower risk, and ensure you actually follow up on whether you want to continue the new idea or not. Different experiments will require different size timeboxes, and you’ll have to decide what is right for your company and for your experiment. A few things to consider are:

How high risk is this? How long can we afford to let this run?

There may be certain experiments that have very high stakes. An example would be making a massive change about how you generate and close sales in your business. While a full 6 months of data might be ideal, if your business can’t afford to see lower sales for 6 months while you try something new, then this time box is too long. In a situation like that, I would look at 30-90 days.

How long will it take to truly see results with this? How long before we have meaningful information we can use to move forward?

Get honest with yourself about how long it will take to truly know if something is working. There will likely be a healthy tension between how long it would ideally take to see full results and how long it feels “safe” to try something new. If you know it will take you a full 90 days to truly evaluate something but you only have 30 days of cushion if it doesn’t work, you may want to go back to the drawing board and start with something smaller.

Make sure your whole team is fully enrolled in the experiment

If you have a team or will be working with others to execute this experiment, it’s important to take the time to communicate as a group and get on the same page. If everyone isn’t actively enrolled in the experiment, it can sabotage your results very quickly.

Agree as a group in the beginning what success and failure look like, and under what circumstances you would stop or pivot the experiment

Once you and your team agree on the hypothesis and time box for your experiment, make agreements around how you know if the experiment is failing or succeeding, and agree under what circumstances you would stop or pivot the experiment early (before the conclusion of the timebox). There are absolutely valid reasons to call off an experiment, but those need to be established before you start. Otherwise, there could be disagreement and frustration within your team.

Regularly review how it is going and what you are learning using as much data as possible

As a company we work in sprints (2 weeks or 1 month, depending on the department) and at the end of every sprint we do a retrospective reviewing how the sprint went and what we learned. This is the time where we review any experiments we are running, look at as much data as possible and evaluate what we are learning, whether we want to continue and whether our hypothesis is holding true.

At the end of the time box, decide as a group how to move forward

At the end of your agreed upon time box, discuss as a team how it went, what you learned, and what to do going forward. Some experiments may end, others may require more time to determine success (create a new extended timebox) and successful experiments will be integrated into the day to day and no longer be considered experiments. Change is a beautiful thing, and when we as leaders provide structure and encourage learning, we foster environments of innovation and engagement. So what experiment are you going to run next?

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