🧪A scientific approach to growing your business

Unsurprisingly, I was never that good at science at school. What little I remembered has however been a solid basis for my love of science fiction, and I feel this knowledge has prepared me for intergalactic travel, exploration and likely, the occasional battle.

However, where I have had some luck approaching things scientifically (in the real world) is with tackling business decisions. Approaching things scientifically can sometimes seem like the opposite of the stories we tell in startup land, where a plucky young upstart in their garage ends up building an app that makes trillions with nothing but a hunch, the internet and a small loan from mum and dad.

This isn’t to say you shouldn’t ever rely on your gut, or that this way of thinking is so data led you to forget all feeling, heart and humanity. In our opinion, you should take a measured approach to test, measure and iterate you apps, processes and/or services to make smarter decisions — even if you do have access to significant capital. Arguably, it’s better to run a few smaller cost-effective experiments based on your assumptions and gut and see which ones are worthwhile to pursue than to throw money at any and all problems and hope that they’ll solve themselves.

This cost-effective approach is not just about the financial cost, but in the cost of effort, the cost of focus, and the cost of your desire to continue. It can be very disheartening to pursue something and not find success no matter how hard you try. It’s better to find out sooner than later if something isn’t going to work. (Read: Tinder)

Swipe in the name of love…

So how do you run a business experiment, especially if you’re not used to doing one?

Well, to answer the first question. We work with a number of clients who have run a successful business for years and their usual approach to business has worked. They’ve been successful in the past, but they’ve recognised that technology has given them more data about their business than they’ve ever had before. They just don’t know how to use it effectively enough to grow.

By having better access to their own data and industry information, businesses can make better decisions about what to work on, when to start, who to start with, when to continue and most importantly when to stop. Sometimes, the best thing you can do is stop.

And back to the question about which industry this approach works well in?

The answer is any.

The approach is scientific, but the application is agnostic. You could be in the physical product space, app-building world or even a speed knitting business.

Joey was never the fastest Friend, was he?

So, what’s the best way to begin?

Well, we usually start with our assumptions.

What do we assume and why do we assume this information or opinion is true are true (or false)?

How can you validate those assumptions before you continue with your experiment(s)?

Many a great idea was killed because of a small assumption a business made that wasn’t tested, was overlooked by a few and then scaled. A great example of this is Pets.com at the beginning of the first dot com boom. In the early 2000s, they and a number of their investors wrongly assumed people wanted to buy pets online.

This was not a valid assumption then.

One way to validate assumptions and mitigate your risk is to base your assumptions on behaviour people are already exhibiting. Early Uber is a pretty played out example, but high-level executives were already being chauffeured around in high-class cars. People already had designated drivers. It was a pretty valid assumption that they would like to continue to be driven around in that luxurious manner. What was unclear was using mobile at the heart of the experience, especially back in those days.

As with all experiments, it’s not useful to test multiple variables at the same time as you can’t clearly tell what’s working, what you should be tweaking and what you should be keeping the same. Minimising variables makes for a better experiment. I’m certain that’s a quote from my/a science teacher.

Next up, I’ll be talking about how to run a good experiment, and what makes a good hypothesis or bad hypothesis.

If you’d like to learn more about using a scientific approach to understand your business no matter what stage you’re at, just drop me a line.

I’m Dan Parry. I do product strategy at Metier Digital — A consultancy that helps businesses and founders validate and build commercially viable products.