Have a second for a thought experiment?
I want to look at affordable loss today, but first, let's start with a thought experiment.
Let's say you have two jobs you're deciding about. The first is your existing job. Let's say you make $65,000. The second job is at a local startup. The starting pay is $50,000. But there's a chance you could go public and make a lot of money. Friends estimate you might even make a million dollars.
I know, nothing to do with experiments. And maybe you've never even heard the phrase affordable loss. But go with me on this thought experiment….
How do you decide?
Well, honestly, if you're in the Silicon Valley, or another entrepreneurial environment, you might not even call this a decision. After all, all your friends have already made their decisions. They all left their existing jobs to join startups.
The reason they all made the choice they did was because of potential gain.
Potential gain is how a lot of folks doing product development make their decisions. Every feature and every effort is evaluated on the criteria of how much this will potentially net us in the future.
But that's not the only way to make decisions.
[tweet “Calculating the upside of a feature isn't the only way to evaluate the value of the investment.”]
There's another approach.
Let's go back to that $65,000 job you were thinking of leaving. It's one thing if you're young, have no kids, live with three other roommates so that your rent is cheap, and can easily take the pay cut to $50,000.
But what if you're a bit older instead? What if you have a spouse and two kids? What if you're far away from a tech hub and you're not sure this local startup will have all the resources it needs – such that it could fold up and die?
At that point, you're not thinking about your potential gain. You're thinking about your affordable loss.
Affordable loss is how much you can afford to lose and still be ok. In this case, you have to ask yourself if you're willing to lose $15,000 (from a big pay cut)?
If you're single and have no children, you might say yes. If you're not, you might say no. How you decide is up to you.
But most folks look at potential gain. And they see the whole affordable loss camp as folks who don't take risks.
But they couldn't be more wrong.
How does this relate to building new products & successive experimentation?
I'll tell you. But first let me direct your attention to how the pharmaceutical companies build new products.
Unlike most startups that build products, they don't get emotionally attached to their ideas. Clinical trials protect them from that.
You can't get emotionally connected, excited, committed to a product that kills people, doesn't work, or doesn't work better than what's in the market today. So clinical trials test that out – to ensure that it's worth investing and taking a new product to market.
It's what I call successive experimentation. Not one big experiment. But rather, a series of smaller ones. One after another. Testing for different, and scoped, things.
And now you can see why affordable loss is so important.
Scoped risks are intelligent risks.
A lot of folks talk about product-market fit. What I don't hear a lot about is the cost of finding product-market fit.
- What did you spend to figure out what kind of traction your idea was getting?
- Did you evaluate that cost?
- Did you determine what you were willing to lose if you didn't get the information you wanted?
- Or did you just go into the exercise without much thinking and with a lot of energy and hope?
When you can define the experiment clearly, you can determine that the risk is worthwhile. But to do that, you need to:
- Know what you want to ask
- Know how you plan to test
- Understand the cost of data collection
- Define the criteria for evaluation
- Determine what will let you move forward
- Accept that if you don't move forward, you've still paid costs
That last part is the affordable loss talking.
You know, going into it that if you don't get the feedback you want back, you may have done this to help save you from spending so much more, but it still has a cost. And you're willing to pay it.
Are you embracing affordable loss?
So here's my question—as you build your new products, are you looking at upside or what you're willing to lose?
What's your default?
Most importantly, are you crafting your efforts in the form of small successive experiments? Because that will help you limit the downside while still chasing an upside.