Consider his process.

First, he picks small venues where he can do rapid, low-risk experiments with new material. In gearing up for his latest global tour, he made between 40 and 50 appearances at a small venue called the Stress Factory in New Brunswick, New Jersey, not far from where he lives. Rock says the Orange Country Register, “It’s like boxing training camp. I always pick a comedy club to work out in.”

In front of audiences of say 30 to 40 people, Rock will bring a yellow legal note pad with lots of joke ideas scribbled on it, according to fellow comedian Matt Ruby. In sets that run say 45 minutes, many of the jokes will fall flat, but according to Ruby, “There were 5-10 lines during the night that were just ridiculously good. Like lightning bolts. My sense is that he starts with these bolts and then writes around them.”

It’s all part of the process. When the material falls flat, Rock will even pause to say things like, “This needs to be fleshed out more if it’s gonna make it.”

Believe it or not, Chris Rock innovates like Amazon does. Amazon led by founder and CEO Jeff Bezos has continuously used experiments to identify unique growth opportunities beyond the company’s core book business – such as the Kindle, Amazon Marketplace, and elastic cloud computing.

Rock doesn’t over-analyze or put all of his hopes into developing a routine in front of his bathroom mirror – he quickly and inexpensively uses experiments to learn, gather insights, and identify unique opportunities – then rapidly iterates, relearns, and refines to create a new show that brings people to tears around the world.

Chris Rock has become the king of comedy, but getting there doesn’t happen in a vacuum – we can all learn from his process.

What can we take from this? Design has always been a part of Apple’s DNA and two key underlying principles from the world design thinking, which is being advanced in remarkable ways by my colleagues at the Stanford Institute of Design (the d.school), can be seen with the iPhone.

First, it’s critical to understand the underlying needs of your customers or partners, which can be very different than what they say they want. Not only is the phone enjoyable to use, the iPhone value chain (or value network) has incentives for its partners and monetization opportunities for Apple throughout. The prime example is the iPhone Application Store where outside software developers keep 70% of each sale for the products they develop, since Apple understands that outside software developers need the right incentives to work weekends and late nights. But, Steve Jobs seems more than happy to take 30%, especially as he predicts gross sales of iPhone applications will soon reach $1 billion.

When it comes to iPhone service and distribution, AT&T needs ARPUs and users, so Apple gives AT&T those in spades on an exclusive basis, and in exchange AT&T pays Apple an estimated $320-$420 for each new subscriber (according to Oppenheimer). Meantime, Best Buy needs to improve its brand and customer pull for mobile phone products and services. Adding iPhone sales to its stores will do just that, while Apple’s distribution reach will grow dramatically.

A second key design principle to highlight here is the use of rapid, low-cost prototypes to gather market insights in order to innovate and improve the offering. Each time a new application is launched, no one knows if it will become a big winner. Perhaps people will flock to games like “Texas hold ‘em”; or, maybe the entire financial community will rush to download the HP-12c calculator iPhone application. The original HP-12c does, after all, cost $80 compared to the $19.99 iPhone application. Apple cannot predict all of the needs it can serve with the iPhone and, as Chris Anderson brilliantly observed, there’s a Long Tail of needs. Through the iPhone Application Store, the market can surely align needs with solutions and Apple has designed its business model to facilitate the operation of that ecosystem, while taking nice profits along the way.

As more people and companies are incented to contribute to the iPhone ecosystem, the phone’s utility grows and the customer experience improves. That drives overall demand. All of this helps to explain why people are still willing to wait two hours in line to buy one or why one of the biggest challenges CIOs face these day is managing requests for iPhones (just ask any CIO).

Indeed, Apple is benefiting from the virtuous cycle of the iPhone ecosystem:

1) Design a product that people love to use;
2) Develop ways to fill the needs of partners who will then increase the value of the ecosystem;
3) Monetize each element of the value network; and,
4) Allow everyone in the ecosystem, most notably Apple, to reap the benefits of scale through increased revenues, profits, and defensibility of the model.

Case in point: Nokia recently announced plans to launch a phone with 300 songs pre-sold, but good luck competing against an iPhone ecosystem that becomes more valuable every day.

Let’s just hope Google’s Android platform doesn’t disrupt the iPhone phenomenon. It’s still too soon to tell.

Even still, we can all learn from Apple’s DNA - their innovation mindset - that by constantly observing and understanding the needs of those we are serving and challenging our assumptions against market desires through rapid, low-cost experiments, we can first create great value for our customers and partners, then capture and monetize that value throughout an ecosystem.

Essentially, Best Buy faces a massive challenge — how to accurately forecast its annual sales of over $40 billion, throughout over 1,000 stores worldwide, across thousands of SKUs, as well as sales online. This is retail, so customer demand is fickle and market insight is highly dispersed, and small percentage point differences between forecast and actual sales can have a big impact on the bottom line.

In 2004, Jeff Severts, then head of Best Buy’s advertizing division, found that eight merchant teams generated the consolidated forecast, i.e. those merchants who ordered the TVs, computers, video games, etc. As Severts told Gary Hamel, it was not uncommon for those forecasts to be off by 10% fewer than 30 days out. Serverts then heard James Surowiecki speak about his book The Wisdom of the Crowds, and wondered if employees from throughout Best Buy could collectively provide the market insight and information to more accurately predict sales than the merchant teams.

Severts was allowed to start with a low-risk, focused experiment. For a $50 prize, he challenged employees throughout Best Buy’s $1 billion gift card division to estimate monthly gift card sales. He received 192 estimates that, when aggregated, was off actual sales by less than one-half of one percent, compared a 5% miss for the gift-card forecasting team. That successful outcome led to a much larger experiment: estimating Best Buy’s 2005 holiday sales. The results spoke for themselves — the crowd’s estimate was 99.9% accurate four months out, compared to 93% for the merchants.

As yesterday’s WSJ article describes, Best Buy continues to test and refine its prediction systems, but the lessons are simple: leaders that give employees permission run low-risk experiments are much more likely to innovate their products, services, processes, and even their company culture than those who believe that insights come only from small, select groups of people.

Great innovative leaders, such as Proctor & Gamble CEO A.G. Lafley, Brad Anderson, CEO at Best Buy, or the folks at Google surround themselves with diverse points of view and constantly use focused experiments to test new ideas. If you think you have the best insight about a complex problem, you probably don’t, but worse, you’re probably not a good leader.