"Educating the Next Steve Jobs"

Most of our high schools and colleges are not preparing students to become innovators. To succeed in the 21st-century economy, students must learn to analyze and solve problems, collaborate, persevere, take calculated risks and learn from failure. To find out how to encourage these skills, I interviewed scores of innovators and their parents, teachers and employers. What I learned is that young Americans learn how to innovate most often despite their schooling—not because of it.

Enlarge Image

Zuma Press

New Tech high school junior Kai Morgan in Napa, Calif., works on his trebuchet, a type of catapult. The school promotes 'independent learning.'

Though few young people will become brilliant innovators like Steve Jobs, most can be taught the skills needed to become more innovative in whatever they do. A handful of high schools, colleges and graduate schools are teaching young people these skills—places like High Tech High in San Diego, the New Tech high schools (a network of 86 schools in 16 states), Olin College in Massachusetts, the Institute of Design (d.school) at Stanford and the MIT Media Lab. The culture of learning in these programs is radically at odds with the culture of schooling in most classrooms.

Related Video

Apple CEO Tim Cook will be the opening night speaking at AllThingsD's D10 conference, Kara Swisher reports on digits. Photo: AP.

In most high-school and college classes, failure is penalized. But without trial and error, there is no innovation. Amanda Alonzo, a 32-year-old teacher at Lynbrook High School in San Jose, Calif., who has mentored two Intel Science Prize finalists and 10 semifinalists in the last two years—more than any other public school science teacher in the U.S.—told me, "One of the most important things I have to teach my students is that when you fail, you are learning." Students gain lasting self-confidence not by being protected from failure but by learning that they can survive it.

The university system today demands and rewards specialization. Professors earn tenure based on research in narrow academic fields, and students are required to declare a major in a subject area. Though expertise is important, Google's director of talent, Judy Gilbert, told me that the most important thing educators can do to prepare students for work in companies like hers is to teach them that problems can never be understood or solved in the context of a single academic discipline. At Stanford's d.school and MIT's Media Lab, all courses are interdisciplinary and based on the exploration of a problem or new opportunity. At Olin College, half the students create interdisciplinary majors like "Design for Sustainable Development" or "Mathematical Biology."

Learning in most conventional education settings is a passive experience: The students listen. But at the most innovative schools, classes are "hands-on," and students are creators, not mere consumers. They acquire skills and knowledge while solving a problem, creating a product or generating a new understanding. At High Tech High, ninth graders must develop a new business concept—imagining a new product or service, writing a business and marketing plan, and developing a budget. The teams present their plans to a panel of business leaders who assess their work. At Olin College, seniors take part in a yearlong project in which students work in teams on a real engineering problem supplied by one of the college's corporate partners.

In conventional schools, students learn so that they can get good grades. My most important research finding is that young innovators are intrinsically motivated. The culture of learning in programs that excel at educating for innovation emphasize what I call the three P's—play, passion and purpose. The play is discovery-based learning that leads young people to find and pursue a passion, which evolves, over time, into a deeper sense of purpose.

Mandating that schools teach innovation as if it were just another course or funding more charter schools won't solve the problem. The solution requires a new way of evaluating student performance and investing in education. Students should have digital portfolios that demonstrate progressive mastery of the skills needed to innovate. Teachers need professional development to learn how to create hands-on, project-based, interdisciplinary courses. Larger school districts and states should establish new charter-like laboratory schools of choice that pioneer these new approaches.

Creating new lab schools around the country and training more teachers to innovate will take time. Meanwhile, what the parents of future innovators do matters enormously. My interviews with parents of today's innovators revealed some fascinating patterns. They valued having their children pursue a genuine passion above their getting straight As, and they talked about the importance of "giving back." As their children matured, they also encouraged them to take risks and learn from mistakes. There is much that all of us stand to learn from them.

"Retail Success is About Who's Working When"

Along with the growth in scale of leading retailers in the 20th century came a growing attitude toward the people working in the stores: they were a cost to be minimized. Sam Walton, the founder of the biggest retailer in the world, summed it up in his book Made in America: "No matter how you slice it in the retail business, payroll is one of the most important parts of overhead, and overhead is one of the most crucial things you have to fight to maintain your profit margins. That was true then, and it is still true today." But recent research by my colleagues and I suggests that retailers are thinking far too simplistically about the cost and potential value of their workforces.

Let's start with stockouts, a problem most big retailers are highly attuned to; they know that when a customer arrives intending to make a purchase and finds the shelf picked clean of the desired item, the store not only loses a sale but also damages the likelihood of that customer's returning. Fixated on that challenge, retail chains have invested heavily in sophisticated inventory management systems. Yet at one large retail chain we studied (pdf), those systems didn't seem to be doing the trick. When we analyzed results of a customer survey, we found that nearly 20% of the products they wanted to buy were out of stock. This was despite the fact that, according to the inventory management system, only 2-3% of items ever ran out before being replenished. It wasn't that the system's numbers were wrong. The problem was that customers couldn't find what they were looking for—and without a store associate to help, they left empty-handed.

Saving sales by pointing to merchandise locations is just one of the ways that store employees facilitate the sales process and perform a very important role. But in large retail enterprises, it's easy for managers to ignore the details of sales floor interactions and opt for large-scale, broad-brush solutions to the challenge of staffing. Most simply set targets for store staffing levels they must maintain over time (mandating, for example, that the cost of labor cannot exceed 10% of sales), and then apply that level across the board. At best, they vary staffing levels based on sales forecasts. Almost invariably, such overall targets lead to a situation where some stores are overstaffed while others are understaffed.

Given today's technology available for data acquisition as well as new developments in analytics, it is possible to do much better than this. Rather than simply predicting what volume of merchandise will sell in a certain period and scheduling more or fewer labor hours accordingly, it is possible to observe the actual flow of customers through stores and make adjustments—even in real time by moving additional employees to the sales floor or redeploying them to higher-traffic areas. Our studies have shown the wisdom of this: stores that manage labor levels in light of store traffic rather than sales forecasts achieve substantial sales increases without extra costs.

Even better results come when retailers recognize that their workforces are not just homogeneous pools of labor to draw on. The most innovative employee managers we know use business analytics to understand the differences in how individual store associates perform. When these retailers make dynamic adjustments, therefore, they are not only deciding how many but who in particular to move to a sales floor. Ann Taylor, the women's clothing retailer, has been a pioneer in tying staff scheduling to the past performance of sales associates: its best salespeople get first choice of times to work and more schedule flexibility. It's a capability that is also finding its way to other business sectors. Call center companies are increasingly capitalizing on their ability to track individual sales to match the most effective people with the right opportunities. A Boston-based startup, Objective Logistics, has just received a round of funding from Google Ventures, Atlas Ventures, and a few other investors to bring performance-based scheduling software to restaurants. (Full disclosure: I am an advisor to the company.) The system would offer up the best times to work, like Friday and Saturday dinner times when bigger orders generate higher tips, to the most productive waiters.

Scheduling, of course, is not the only aspect of labor management that retailers must get right. Once they're at the counters and in the aisles, employees also need the knowledge of how to interact effectively with customers. This is a hard thing to understand—let alone teach—and an area where managers find simplistic solutions just as tempting. Take, for example, the edict some retailers have issued that each customer must be greeted with a smile at the entrance of the store. (Our research has found essentially no relationship between greeting the customers and store sales.) To better understand the nature and the outcomes of customer-employee interactions, a handful of companies are currently experimenting with analysis of in-store video streams. (Note that privacy concerns hamper such video analysis in the US. My experience of it has been in South America, Asia, and Europe, in collaboration with Bravo Lucy, a Norwegian and Indian business analytics firm.)

Scheduling, however, is an area where the tools exist to manage better today—and where the evidence is clear that managing simplistically can send a retailer into a dangerous downward spiral. In a recent study, colleagues and I used data from major retail chains and found a common trend of low forecasted sales for a weekend resulting in stores staffed too thinly to provide adequate service for the customers who actually showed up. The lost potential was evident in the long lines observed at checkouts and the poorly stocked shelves; undoubtedly many customers left the store without buying. But for any manager looking only at receipts and staffing, the end of the day brought vindication: sales, indeed, were low. Isn't it remarkable how prophecies can fulfill themselves?