Set the Conditions for Anyone on Your Team to Be Creative

One of the most damaging myths about creativity is that there is a specific “creative personality” that some people have and others don’t. Yet in decades of creativity research, no such trait has ever been identified. The truth is that anybody can be creative, given the right opportunities and context.

If you don’t believe me, take the least creative person in your office out for lunch — someone who doesn’t seem to have a creative bone in their body. Chances are, you’ll find some secret passion, pursued outside of office hours, into which they pour their creative energies. They just aren’t applying those energies to their day jobs.

The secret to unlocking creativity is not to look for more creative people, but to unlock more creativity from the people who already work for you. The same body of creativity research that finds no distinct “creative personality” is incredibly consistent about what leads to creative work, and they are all things you can implement within your team. Here’s what you need to do:

Cultivate Expertise

One of the things that creativity researchers have consistently found for decades is that expertise is absolutely essential for producing top-notch creative work — and the expertise needs to be specific to a particular field or domain. So the first step to being creative is to become an expert in a particular area.


The reason expertise is so important is that you need to be an expert in a specific field to understand what the important problems are and what would constitute an important new solution. Einstein, for instance, studied physics intensely for years to understand the basic physical model for time and space before he understood that there was an inherent flaw in that model.

So how do you cultivate expertise? Performance expert Anders Ericsson has studied that problem for decades and found that the crucial element is deliberate practice. You need to identify the components of a skill, offer coaching, and encourage employees to work on weak areas. That goes far beyond the intermittent training that most organizations do.

For example, one skill that Amazon has identified as crucial to performance is writing. Employees need to constantly write six-page memos, even for introducing small product features throughout their careers at the company. They consistently receive coaching and feedback and need to write good memos in order to advance within the company.

Any company can replicate Amazon’s memo-writing policy. What’s not so easily replicated is the intense commitment to cultivating writing expertise that the company has prioritized for years.

Encourage Exploration

While deep expertise in a given field is absolutely essential for real creativity, it is not sufficient. Look at any great body of creative work and you’ll find a crucial insight that came from outside the original domain. It is often a seemingly random piece of insight that transforms ordinary work into something very different. For example, it was a random visit to a museum that inspired Picasso’s African period. Charles Darwin spent years studying fossils and thinking about evolution until he came across a 40 year-old economics essay by Thomas Malthus that led to his theory of natural selection. The philosophy of David Hume helped lead Einstein to special relativity.


More recently, a team of researchers analyzing 17.9 million scientific papers found that the most highly cited work is far more likely to come from a team of experts in one field working with a specialist in something very different. It is that combination of expertise, exploration, and collaboration that leads to truly breakthrough ideas.

That is how Google’s “20% time” policy is able to act as a human-powered search engine for new ideas. By allowing employees to work on projects unrelated to their formal job descriptions 20% of the time, people with varied experiences and expertise can combine their efforts in a way that would be extremely unlikely in a planned company initiative.

Empower Your People with Technology

In Walter Isaacson’s recent biography of Leonardo da Vinci, he recounts how the medieval master would study nature, from anatomy to geological formations, to guide his art. Now Leonardo was clearly a genius of historical proportions, but think about how much more efficient he would have been with a decent search engine.

One of the most overlooked aspects of innovation is how much technology can enhance productivity. Part of the reason is because it makes the two factors noted above, acquiring domain expertise and exploring adjacencies, so much easier. However, another reason is because it frees up time to allow for more experimentation.

You can see this at work at Pixar, which was originally a technology company that began shooting short films to demonstrate the capabilities of its original product, animation software. However, as they were experimenting with the technology, they also found themselves experimenting with storytelling, and those experiments led them to become one of the most highly acclaimed studios in history.

As Pixar founder Ed Catmull put it in his memoir, Creativity Inc., “Every one of our films, when we start off, they suck…Our job is to take it from something that sucks to something that doesn’t suck. That’s the hard part.” It is that kind of continual iteration that technology makes possible, and that makes truly great creative work possible.

Reward Persistence

Far too often, we think of creativity as an initial, brilliant spark followed by a straightforward period of execution, but as Catmull’s comment above shows, that’s not true in the least. In his book, he calls early ideas “ugly babies” and stresses the need to protect them from being judged too quickly. Yet most organizations do just the opposite. Any idea that doesn’t show immediate promise is typically killed quickly and without remorse.

One firm that has been able to buck this trend is IBM. Its research division routinely pursues seemingly outlandish ideas long before they are commercially viable. For example, a team at IBM successfully performed the first quantum teleportation in 1993, when the company was in dire financial straits, with absolutely no financial benefit.

However, the research wasn’t particularly expensive, and the company has continued to support the work for the last 25 years. Today, it is a leader in quantum computing — a market potentially worth billions — because it stuck with it. That’s why IBM, despite its ups and downs, remains a highly profitable company while so many of its former rivals are long gone.

Kevin Ashton, who first came up with the idea for RFID chips, wrote in his book, How to Fly a Horse, “Creation is a long journey, where most turns are wrong and most ends are dead. The most important thing creators do is work. The most important thing they don’t do is quit.”

Yet all too often, organizations do quit. They expect their “babies” to be beautiful from the start. They see creation as an event rather than a process, don’t invest in expertise or exploration, and refuse to tolerate wrong turns and dead ends. Is it any wonder that so few are able to produce anything truly new and different?

Greg Satell is an author, speaker, and advisor. His first book, Mapping Innovation: A Playbook for Navigating a Disruptive Age, was chosen as one of the best business books of 2017 by 800-CEO-READ. His new book, Cascades: How to Create a Movement that Drives Transformational Change, will be published by McGraw-Hill in April, 2019. You can learn more about Greg on his website, and follow him on Twitter @DigitalTonto.


Reinventing the To-Do List: A Multi-billion Dollar Opportunity


By: Michael Schrage
October 10, 2013

Gotta love Dan Markovitz’s post decrying to-do lists. Contrarian, yes.  But it unfortunately ignored the digitally-enhanced tomorrow made possible by the very device you’re reading this on.

To-do lists, in fact, will likely be the internet’s next multibillion dollar global innovation. The only serious question is whether the to-do breakthroughs come from Google, Amazon, Microsoft, Apple, LinkedIn or a Zuckerberg yet to emerge from the venture capital chrysalis. To-do lists are too big, too rich and too transcendent a business and technical opportunity to ignore. All the digital ingredients exist; what’s missing is the right intrapreneurial—or entrepreneurial—master kitchen to mix them.

Multibillion dollar markets in gray market to-do lists already exist; they’re called recommendation engines.  Amazon and Netflix have effectively branded themselves as superior recommenders. Those Web 2.0 innovators succeed through blending algorithmic alchemy and data-driven decisions into user experiences inviting exploration, sampling and outright purchase. You’re under no obligation to do any of those things, of course. But the odds are you— rightly—take many of those recommendations seriously. The better their recommendations, the more you trust their judgment. They’ve little incentive to squander your time or their credibility.

Google, of course, is the ultimate recommendation engine. Gmail increasingly nudges and autosuggests other folks who you might want to copy on that email you’re sending. Microsoft’s “” of email similarly sets the digital stage for a powerful new genre of recommendation integration. Do you sync your iPhone and/or Android with your tablet and/or laptop, too?

Consider: A Google and/or Microsoft and/or Apple likely has access to your calendar, your address book, your email, your apps and most of your searches. Because you’re probably using your devices to help manage every single aspect of your life, those companies have excellent insight into both your personal and professional life. If you provided Facebook, LinkedIn and Amazon with calendar/schedule access, they’d have similarly rich visibility into what you’re doing and how you plan to spend/invest your time.

Now make the obvious leap: How difficult do you think it would, could or should be for a Google, Microsoft, Amazon, Apple or LinkedIn to engineer recommendation engines that generate custom to-do lists based on that ever-growing embarrassment  of real-world  data riches.  Not very. They have all the algorithms and infrastructures they need to provide as targeted —or as comprehensive—a weekly/daily/hourly/real-time to-do list you think you might want or need.

Wake up in the morning, for example, tap your Google/Microsoft/Amazon “TDL” icon — or whisper “to do” to your Google Glass—then skim the day’s Top Ten List of what you should do based on an algorithmic scan and review of your calendar, phone calls, Fitbit/Jawbone, Facebook status reports, twitterstreams, etc. Your RTDs—recommended to-dos—could be as simple and straightforward as a list of people to call or email or as sophisticated as minute-by-minute day plan decision tree suggesting a variety of different options depending on how much you want to accomplish.

What kind of recommended to–dos would influence or inspire you most?

To-do lists could be tunable; you could ask for to-do lists with recommended reminders for you to do a better job of keeping in touch with friends and family or being more productive at work. Make personal, professional or some happy medium between.  Your to-do list could only appear at the beginning and end of each day or be programmed to pop-up intrusively when you perform unscheduled or time-wasting tasks. To-do lists could be further operationalized with Thaler-ian “nudges” and/or Schelling-esque “precommitments.” Your to-do recommendations could be as instantly perishable as a text or persist as the daily interface for auditable achievement.

Of course, just like a Netflix or Amazon recommender, your to-do list will learn from the to-dos you actually do and the ones you consistently defer or ignore outright. Do you want to train your to-do list to suggest the activities and obligations you most enjoy and effectively achieve? Or do you want your RTD reminding you to take the essential next steps to finish the tasks you most loathe?  Just as people appreciate the occasional oddball movie or television recommendation from a Netflix, you’d likely want the usefully surprising to-do recommendation suggesting luck with a LinkedIn contact or buying a friend a gift.  Are you the kind of person who wants a master recommended to-do list? Or would you be better off managing a portfolio of recommended to-dos for review—like a stock portfolio?

The power and virtue of recommendations is that they are just that: recommendations, not obligations. But just as someone would learn a lot about you seeing the movies and shows recommended by Netflix or the books and products Amazon recommends or the searches you’re performing on Google and/or Bing, people would gain enormous insight into who you are and what you want to become if they could monitor your recommended to dos and track which ones you acted upon.

To-do lists offer a fantastic organizing principle for integrating the physical and digital elements of people’s lives. As surely as recommendations changed the way people shop on Amazon, binged on Netflix and listened to music on Spotify and Pandora, they’re going to transform how people prioritize their time.

About Michael Schrage:

Michael Schrage, a research fellow at MIT Sloan School’s Center for Digital Business, is the author of Serious Play and the new HBR Single Who Do You Want Your Customers to Become?




S+B The Thought Leader Interview: Loran Nordgren

Loran Nordgren

In this interview with Ken Favaro and Amy D’Onofrio for S+B, Loran Nordgren, the cofounder of unconscious thought theory, explains how taking a break and distracting the mind can lead to higher-quality decision making.

Could you boost the quality of decision making and innovation at your company by encouraging a more structured form of intuition? Loran Nordgren thinks you could. Indeed, the associate professor of management and organizations at Northwestern University’s Kellogg School of Management argues that adopting new approaches to how we process thought is the remedy that will free organizations from the shackles of traditional strategic planning.

Nordgren, who grew up in Chicago, cofounded a body of work called unconscious thought theory with Ap Dijksterhuis, a professor at Radboud University in Nijmegen, Netherlands, while getting his Ph.D. in social psychology at the University of Amsterdam. Based on in-depth studies of the impact of different ways of merging analytical thinking and strategic intuition, this theory proposes, in effect, that some forms of thought processing consistently lead to more beneficial choices and more effective problem solving...

Download the attached PDF to read the complete interview.