Superhuman Innovation summary

Most people can still recall the days when mobile phones flipped open to reveal a simple keyboard that could only make calls or send short messages. Nowadays, 82 percent of Americans walk around with powerful, pocket-sized computers at all times.

The capabilities offered by smartphones have significantly changed customer expectations. Take something as simple as ordering a pizza. These days, we expect to be able to order, pay, and track the delivery person right up to the moment they arrive at our door – all from our phone. Long gone are the hassles of having to verbally repeat complex orders, let alone having to pick up everything from the restaurant yourself. 

Recall the last time you ordered a product online from a site like Amazon. On your end, the process probably seemed unbelievably simple – just a few clicks and the purchase appeared at your doorstep the next day, or even the same evening.

Now, think about how much data had to be transferred on Amazon’s end to get that package to you on time. The product itself is attached to a barcode, and all the details about it – like its dimensions and location in the warehouse – are stored in an Amazon database. When you place an order, the product needs to be retrieved from the warehouse, boxed up, and assigned to a delivery service. The box gets its own barcode, shipping records are created, the package is delivered, and you get a text or email confirmation.

Back in the early twentieth century, Henry Ford was on a quest to make cars for the multitudes. At the time, though, it took 12 hours for a group of workers to put together a new car – which was just too slow. A dramatic change happened in 1913 when Ford invented the assembly line. Now, each worker only had to install one part of the car before passing it on to the next. This brought the assembly time down to just 2 hours and 30 minutes.

Why was this development so significant? Because a business can only sell as many units as it can manufacture without accruing massive additional labor costs. If you can only make 10,000 units, then that’s all you’ll be able to sell. 

Picture a marketplace in ancient times, packed full of vendors all vying for people’s attention. How did these vendors ensure that someone bought their freshly baked bread instead of someone else’s? By understanding their customers’ desires and changing their pitch according to the context.

To make sales to prospective buyers, businesses have always needed the second word in the SUPER framework: Understanding. What’s changed are the methods of getting to know your customer. Using AI, you can learn customers’ wants and needs and adapt your strategy based on the feedback you receive. 

If you’ve worked in a large enough company, you’ve probably heard of KPIs, or key performance indicators. For example, perhaps your company wants to increase year-over-year growth by 100 percent. This and other KPIs are ways of measuring how successful an organization has been at achieving its objectives on both the company-wide and departmental level. On the flip side, they can also be a major source of stress, leading employees to fear being perceived as failures.

As a company, it’s important not to judge anyone too harshly for not meeting a KPI, but to instead treat those gaps as areas to improve and optimize. You may have chosen the wrong targets or need other measurements to get a fuller picture of why a product performed a certain way. Or, your data source may be of questionable quality. All of these factors could lead you to mistakenly optimize for the wrong thing.

Historically, humans have excelled at using experimentation and imagination to solve real-world problems. Take the Roman aqueducts. These impressive structures were built long before text messages, trucks, or even explosives were invented. But ancient Rome’s growing population desperately needed a steady supply of water, so they used innovation to dream up the necessary structure to obtain it. 

Just as the Romans used the technology available at the time to help them solve their problems, we can use our own modern-day tools – like AI – to experiment and accomplish difficult goals. We call this chain actionable curiosity, a process that brings us the final two components of the SUPER framework: Experimentation and Results.