Marina Gorbis's Blog, page 1565

Google's CIO on How to Make Your IT Department Great

Running an IT department is hard enough under any circumstances, but imagine doing it at one of the world's preeminent technology companies. Your customers aren't haplessly trying to set up their voicemail; they're experts in technology and expect it to work.

In that sense, you might think Ben Fried, Google's CIO, has one of the toughest jobs in existence. On the other hand, few CIOs can boast a company culture as supportive of technology.

As part of our series on the future of corporate IT, I gave Fried a call and asked him about his job, and where he thinks the industry is going. An edited version of our conversation is below.

Tell me about your role at Google, and what your purview as CIO includes.

I'm responsible for the technology that people who work at Google get as part of doing their job. That also includes the major line of business systems that power the back office and related functions of the company, as well as the front line support and operations elements for all of that.

So what do you do at Google that is different than most IT departments?

One initiative is an area where IT has a harder time understanding its role traditionally: workplace technology. It's all the productivity tools and technology you use to get work done, that aren't part of a line of business; it's a large portfolio, but any company that has a company directory or something it thinks of as "the intranet" can relate. In a lot of workplaces, these technologies don't get thought of in strategic terms, but those are actually most of the touchpoints people have with IT. I see a lot of CIOs spending a lot of time — which is very important to do — on major business initiatives. But I often see an inadequate amount of time spent where the day-to-day, most frequent touchpoints are, which is with all the other ways the people in the company are their users. One of the big changes that has come with the mass consumerization of technology is that IT needs to flip that around a little and spend more time focusing on the overall employee experience.

When the people you deliver technology to are technology experts — and it's not just at Google where that's the case, but any workforce that has people born within the last 30 years — it's really important that you make sure that that daily impression, that first impression they get of IT, is a good impression.

To do this you have to have IT people who are more knowledgeable about the technology and the best ways to use it than the average employee. In the future, that kind of thinking is going to differentiate great IT departments from good IT departments.

If that's the case, why isn't everyone doing it that way already?

If you've got a problem with your laptop, the person you bring it to should be an expert who knows more than you do. I can't tell you how many shops I've been to where the first person you bring your problem to is someone who is being paid, or whose employer is being paid, on a per incident or a per ticket basis. The standard approach is to apply tough cost control. That generally means that front line, in many cases, are the lowest cost of labor, who are generally working off a well-scripted common recipe of how to provide tech support. The sad thing is, a savvy knowledge worker can tell you're dealing with someone who's not really an expert. We take great pride in the fact that the people we hire to be that first touchpoint, they're our employees. And most of the time — over 90% of the time — they'll solve your problem themselves.

The first response when you talk to people who are marinated in the old ways of doing things is 'That's gotta be way too expensive.' It's actually a lower-cost approach, because it's faster for a more tech-savvy person to resolve the problem. Secondly, you can do more with a smaller support workforce as a result. Third, you get better people when you take this approach, because you get people who are attracted to solving hard problems. It turns out that this approach produces what I think is a virtuous cycle that brings costs down and customer satisfaction up.

Tell me a bit about how IT has changed since you came to Google, and how you see it evolving going forward.

One of the reasons why I really wanted the Google CIO job was I'd had these very early indicators when I was an IT leader at an investment bank that the demographics among the users of technology had changed. I was starting to see the effects of having a deeply technology-savvy workforce across the company, and not just in IT. And I saw that that led to big change.

The changing demographics of the workforce are one thing that every CIO has to wrestle with. That is a workforce that is much more opinionated, much more rightly so, comes to work already knowing how to work, already having made a choice about how it wants to work. And that's the thing that CIOs face right now.

The other tidal force that CIOs face is this aspect of economies of scale, and economies created by vertical integration that really, really large cloud companies like Google have. Google has economies of scale that I don't believe any other organization in the world — and I'm including governments when I say that — have. And that's a tidal force that will change the role of the CIO, because the cloud is going to become the better delivery mechanism.

There's only so long enterprises can hold out against that. One of the things I'd learned working for a number of CIOs was that IT is most commonly viewed as the largest cost center in the enterprise. One of the reasons I wanted to come to Google was to have some small role in helping to shape the direction of a product suite for enterprises. I thought, 'Listen, I can be on the outside and have this done to me, or I can be on the inside.'

Reinventing Corporate IT
An HBR Insight Center





IT Has to Deliver Great Tools — and Teach People to Use Them
IT on Steroids: The Benefits (and Risks) of Accelerating Technology
The Building Blocks of Successful IT
Move Beyond Enterprise IT to an API Strategy

New Books from HBR Press for August

Check out these new or forthcoming books from HBR Press:

Conquering the Chaos: Win in India, Win Everywhere

by Ravi Venkatesan

India is on the minds of business leaders everywhere. Within a few decades, India will be the world's most populous nation and one of its largest economies. But it is also a complex market, with a reputation for corruption, uncertainty, and bureaucracy. Ravi Venkatesan, the former Chairman of Microsoft India, offers inside advice on how your firm can overcome the unique challenges of the Indian market. If you can win in India, you can win everywhere.

Keeping Up with the Quants: Your Guide to Understanding and Using Analytics

by Thomas H. Davenport and Jinho Kim

Welcome to the age of data. No matter your interests (sports, movies, politics), your industry (finance, marketing, technology, manufacturing), or the type of organization you work for (big company, nonprofit, small start-up) — your world is awash with data. As a successful manager today, you must be able to make sense of all this information. You need to be conversant with analytical terminology and methods and able to work with quantitative information. This book promises to become your "quantitative literacy" guide — helping you develop the analytical skills you need right now in order to summarize data, find the meaning in it, and extract its value

The End of Competitive Advantage: How to Keep Your Strategy Moving as Fast as Your Business

by Rita Gunther McGrath and Alex Gourlay

Are you at risk of being trapped in an uncompetitive business? Chances are the strategies that worked well for you even a few years ago no longer deliver the results you need. Dramatic changes in business have unearthed a major gap between traditional approaches to strategy and the way the real world works now. In short, strategy is stuck. Most leaders are using frameworks that were designed for a different era of business and based on a single dominant idea — that the purpose of strategy is to achieve a sustainable competitive advantage. This book serves as a new playbook for strategy, one based on updated assumptions about how the world works, and shows how some of the world's most successful companies use this method to compete and win today.

How CEOs Can Fix Capitalism

Edited by Raymond Gilmartin and Steven E. Prokesch

The financial crisis of 2008 and the Great Recession caused a crisis of public confidence in business and American-style capitalism, with its focus on maximizing shareholder value. Corporate leaders understood that reform was needed and that they needed to commit themselves to the dual goal of producing benefits for society and their firms' bottom lines — to creating "shared value." But the specific actions they could take to bring about this change were less clear. This HBR Single offers some of the freshest thinking today on practical measures that businesses can implement to create shared value.

Work Smarter with LinkedIn

by Alexandra Samuel

If you think LinkedIn is just for job hunting, you're missing out on the many ways you can take advantage of this social network to build the professional relationships you need to advance in your career. LinkedIn can help you initiate, strengthen, and use the very real human connections that make you effective on the job — and help you get ahead. This short, practical book shows you how. In Work Smarter with LinkedIn, social media expert Alexandra Samuel demonstrates the most effective ways to actively build and use your network

True Story: How to Combine Story and Action to Transform Your Business

by Ty Montague

Is your company a storyteller — or a storydoer? The old way to market a business was storytelling. But in today's world, simply communicating your brand's story in the hope that customers will listen is no longer enough. Instead, your authentic brand must be evident in every action the organization undertakes. Today's most successful businesses are storydoers. These companies create products and services that, from the very beginning, are manifestations of an authentic and meaningful story — one told primarily through action, not advertising. In True Story creative executive Ty Montague argues that any business, regardless of size or industry, can embrace the principles of storydoing. The book is filled with examples of how forward-thinking organizations — including Red Bull, Shaklee, Grind, TOMS Shoes, and News Corporation — are effectively using storydoing to transform their organizations.

Worthless, Impossible, and Stupid: How Contrarian Entrepreneurs Create and Capture Extraordinary Value

by Daniel Isenberg

Are you a member of the new class of global entrepreneurs? If not, beware — this book may inspire you to become one. It's a rallying call for those whose ideas were ever called worthless, impossible, or even stupid. In this fascinating read, global entrepreneurship expert Daniel Isenberg illustrates the new rules of starting and growing a business. No longer bound by a western "Silicon Valley" approach to entrepreneurship, a new group of enterprising doers has created a global and diverse mix of organizations that could be tomorrow's leading firms. What can you learn — and what will you be inspired to do? Let Worthless, Impossible & Stupid be your new manual for making change.

Primal Leadership, With a New Preface by the Authors: Unleashing the Power of Emotional Intelligence

by Daniel Goleman, Richard Boyatzis, and Annie McKee

This is the book that established "emotional intelligence" in the business lexicon — and made it a necessary skill for leaders. Managers and professionals across the globe have embraced Primal Leadership. This refreshed edition, with a new preface by the authors, vividly illustrates the power and the necessity of leadership that is self-aware, empathic, motivating, and collaborative in a world that is ever more economically volatile and technologically complex.

A Better Way to Tackle All That Data

The single biggest challenge any organization faces in a world awash in data is the time it takes to make a decision. We can amass all of the data in the world, but if it doesn't help to save a life, allocate resources better, fund the organization, or avoid a crisis, what good is it? Hampered by a shortage of qualified data scientists to perform the work of analysis, big data's rise is outstripping our ability to perform analysis and reach conclusions fast enough.

At the root of this problem is our concept of what constitutes data. Existing boundaries of what we can digitize and analyze are moving outward every day. Taking Gartner's prediction that the Internet of Things (essentially, sensors that share data with the Internet) will add 50 billion machine voices to today's 2 billion connected users, we have to believe that the ability for humans to manage the process of amassing the right data and performing the right analysis is headed for trouble.

The measure of how long it takes analytics to reach a conclusion is often called "time to decision." If we accept that big data's holy grail is, as Randy Bean says in Information Week, better, faster decisions, we have to believe that as data continue to grow in volume, velocity, and variety, making management more complex and potentially slowing time to decision, something has to give.

This is a problem crying out for a solution that has long been in development but only recently has begun to become effective and economically feasible enough for widespread adoption — machine learning. As the term suggests, machine learning is a branch of computer science where algorithms learn from and react to data just as humans do. Machine-learning software identifies hidden patterns in data and uses those patterns both to group similar data and to make predictions. Each time new data are added and analyzed, the software gains a clearer view of data patterns and gets closer to making the optimal prediction or reaching a meaningful understanding.

It does this by turning the conventional data-mining practice on its head. Rather than scientists beginning with a (possibly biased) hypothesis that they then seek to confirm or disprove in a body of data, the machine starts with a definition of an ideal outcome which it uses to decide what data matter and how they should factor into solving problems. The idea is that if we know the optimal way for something to operate, we can figure out exactly what to change in a suboptimal situation.

Thus, for example, a complex system like commuter train service has targets for the on time, safe delivery of passengers that present an optimization problem in real time based on a variety of fluctuating variables, ranging from the weather, to load size, to even the availability and cost of energy. Machine-learning software onboard the trains themselves can take all of these factors into account, running hundreds of calculations a second to direct an engineer to operate at the proper speed.

The Nest thermostat is a well-known example of machine learning applied to very local data. As people turn the dial on the Nest thermostat, it learns their temperature preferences and begins to manage the heating and cooling automatically, regardless of time of day and day of week. The system never stops learning, allowing people to continuously define the optimum.

The application of machine learning in health care is essential to achieving the goal of personalized medicine (the concept that every patient is subtly different and should be treated uniquely). Nowhere is this more easily seen than in cancer treatment, where genomic medicine is enabling highly customized therapy based on an individual's type of tumor and myriad other factors. Here machine-learning algorithms help sort the various treatments available to oncologists, classifying them by cost, efficacy, toxicity, and so forth. As patients are treated, these systems grow in intelligence, learning from outcomes and additional evidence-based guidelines. This leaves the oncologists free to focus on optimizing treatment plans and sharing information with their patients.

With the rise of off-the-shelf software, such as LIONsolver, the winner of a recent crowdsourcing contest to find better ways to recognize Parkinson's disease, machine learning is at last entering the mainstream, available to a wider variety of businesses than the likes of Yahoo, Google, and Facebook that first made big data headlines. More and more businesses may now see it as a viable alternative to addressing the rapid proliferation of data with increasing numbers of data scientists spending more and more time analyzing data. Expect to see machine learning used to train supply chain systems, predict weather, spot fraud, and especially in customer experience management, to help decide what variables and context matter for customer response to marketing.

The Missing Half of the Education Debate

As employers, as citizens, and as parents, executives the world over are increasingly becoming concerned about the education systems, especially post-high school, that are supposed to prepare young people for work and life. The crescendo of concern is shaping public discourse, policy debate, and private experimentation through commitments such as the $472 million made to higher education by the Gates Foundation since 2006.

So far, I fear, the discussion is only half a conversation

Take, for example, US President Barack Obama's recent "middle out" speech at Knox College. His promise to "lay out an aggressive strategy to shake up the [tertiary educational] system, tackle rising costs, and improve value for middle-class students and their families" went over well. No surprise there; when a president says "it is critical to make sure that college is affordable for every single American who is willing to work for it," heads will nod. Who would argue about making college more affordable and more accessible?

The problem is that such talk leaves much unsaid. The underlying assumption is that because college pretty much does the right things — and does them well — the real challenge society faces is to make sure that all who desire a college education have fair and affordable access to it. I do not question the importance or the difficulty of the challenge; I question the basic assumption.

Most often, that assumption doesn't even get discussed. When it is, what we hear is the emphatic argument that college works because it does pay, which is supported by data like that gathered by the OECD's most recent compendium of education-related data, Education at a Glance 2013, which covers the period through 2011. The data show a modest rise to 4.8% in the unemployment rate among graduates in the OECD countries, but that's far lower than the 12.6% for individuals of comparable age but without college education. In the US, the corresponding gap is larger: 4.9% vs. 16.2% .

Moreover, over a working lifetime, four-year college graduates in the US will earn 84% more than those who just complete high school. This represents a great benefit to people individually as well as to society, which stands to gain from the taxes they will pay and the unemployment and other forms of support they will not need.

What's missing from this happy conversation is an equal level of attention to how few students make it through college, how little they actually learn, and how poorly many of them do in finding the well-paying work for which their education prepares them. In the US, for example, although more than two-thirds of those in the appropriate age cohort begin programs at four-year colleges, a third do not finish. Add in the experience of two-year colleges — and the graduation rate falls to a little over 50%. Equally disturbing, graduation rates among economically advantaged groups are much higher than among those lower down on the economic pyramid, and the gap between them is growing

Every bit as troubling is the performance of colleges in developing the critical thinking skills and capabilities so important to life and work. In Academically Adrift, Richard Arum and Josipa Roska use the Collegiate Learning Assessment tool — a statistical instrument being used by the OECD for its 17-country Assessment of Higher Education Learning Outcomes (AHELO) Project, which is assessing student knowledge and abilities in higher education — to draw a clear line in the sand. After surveying 2,300 college students, Arum and Roska found that at least 45% of them showed absolutely no statistically significant improvement in their critical thinking skills after their first two years in college.

Reports from other countries show a consistent, and growing, disconnect between the fast-rising number of students graduated and the shrinking percentage that find work. A survey of recent graduates from China's famed Tsinghua University revealed that some two-thirds were working for entry-level wages lower than those paid to migrant workers. Across China, these individuals and their peers from other schools huddle together in crowded urban apartments, and are spoken of dismissively as the "ant tribe."

The point is simple: Conversations about college must address more than just cost and access. They must also question assumptions of quality, performance, and relevance. This is uncomfortable and unwelcome ground. But for many students in many places, college is no longer doing well what it was designed to do — and what it was designed to do may no longer be what students most need or what societies most need of them. We need to talk about that too.

Executives need to do more about these issues than just talk or exert influence as alumni or school trustees. They know well that only what gets effectively measured gets properly managed. They should, therefore, follow the imaginative lead of companies such as Boeing, which provides data to colleges on how education has helped its new hires develop the skills and capabilities their jobs require.

After all, colleges need access to tangible, ground-level information showing the correlation between the curriculum and learning experiences they provide and real-world outcomes in terms of usable skills and capabilities. Colleges can't fix things if they, too, have access only to half a conversation. Business can, and must, supply the other half.

Moviegoers May Be Losing Interest in 3-D

The proportion of movie gross receipts from higher-priced 3-D showings is trending below 40% for the first time since the technology became widespread in 2009, says Entertainment Weekly. The 3-D percentages for recent releases Monsters University, World War Z, The Great Gatsby, and R.I.P.D. have been in the 30s, with Despicable Me 2 and Turbo in the 20s. Compare those with Avatar, whose 3-D share during its opening weekend in 2009 was 71%. Consumers may be tiring of the format, and of the hefty surcharges. Fox, Paramount, Disney, and Universal collectively spent $700 million on equipping theaters with 3-D projectors.

Bill Ackman Is Just Doing God's Work

Everybody has been piling on to hedge fund manager Bill Ackman lately. I'm not joining in. The man may have bitten off more than he can chew, dug himself in too deep, played with fire and gotten burned, or whatever other folksy metaphor you favor. But he's doing God's work. Or at least the market's.

Ackman's short-selling campaign against vitamin distributor Herbalife has blown up in his face, with the company's stock up more than 75% since he unveiled his position last December and some of his most prominent hedge fund competitors profiting from his misery.

Then there's JC Penney, where Ackman's push to remake the retailer under the leadership of former Apple Stores chief Ron Johnson has ended in red ink and recriminations. After 17 bold but financially disastrous months, JC Penney's board fired Johnson in April and reinstated his predecessor, Mike Ullman, as interim CEO. Last week Ackman wrote (and leaked) pair of letters in which he pushed for quicker action in finding a permanent replacement for Ullman and demanded the resignation of board chairman Tom Engibous. That led iconic Starbucks CEO Howard Schultz (who knows Ullman from Starbucks' board) to weigh in, telling The Financial Times that Ackman "has blood on his hands for being the one who brought Ron Johnson in" and arguing on CNBC that Ackman and Johnson had "ruined the lives of thousands of JC Penney employees and fractured shareholder value."

Schultz is may be right about that. But the choice of Johnson was a bold bet that didn't pay off — or at least didn't pay off in time. Sometimes that happens. And the whole reason Ackman jumped in at JC Penney in the first place is that the company's fortunes had been in decline. That's what activist hedge fund managers like Ackman do. They identify companies that they think could be worth a lot more than their share price indicates, and push for changes. Often these changes involve straightforward moves like spinning off subsidiaries, which Carl Icahn pushed Time Warner to do seven years ago and the company is finally getting around to now. Occasionally they get much more involved, as with Eddie Lampert's seemingly permanent (and not exactly successful) takeover of Sears and Kmart. And sometimes, when they think a company's stock is overvalued, they sell it short and try to convince the rest of the world that they're right.

Here's the thing. On balance, this stuff seems to work. That's the finding of a big new study by Harvard's Lucian Bebchuk, Duke's Alon Brav, and Columbia's Wei Jiang, which shows that companies targeted by activist hedge funds as undervalued markedly improve their operating performance in the subsequent five years. What's more, the authors write:

These improvements in long-term performance, we find, are present also when focusing on the two subsets of activist interventions that are most resisted and criticized — first, interventions that lower or constrain long-term investments by enhancing leverage, beefing up shareholder payouts, or reducing investments and, second, adversarial interventions employing hostile tactics.

It is of course a bit disturbing to see that five years is now considered the "long term." It also doesn't follow from Bebchuk, Brav, and Jiang's evidence that more hedge fund activism would necessarily be a good thing. The very rarity of such interventions helps make them successful. If there were thousands of Bill Ackmans out there, the results of their activism would presumably be far less impressive. But Ackman's current struggles illustrate why his extremely hands-on brand of investing will never become common. It involves going way out on a limb — and limbs (tree limbs, at least) are liable to break or get chopped off.

Now it is true that Ackman's behavior over the past couple of weeks has been petulant in the extreme, and Bill Cohan's epic Ackman profile in April's Vanity Fair makes clear that the guy is not always fun to hang out (or go biking) with. But a normal, well-balanced person would never go into this line of work. And it does appear to be useful work. Which is more than be said of a lot of other financial-market endeavors.

Hedge funds are often criticized as short-term speculators. Some are, some aren't. The particular brand of investing that Ackman and a small number of other hedge-fund managers practice is best described as medium-term. Ackman is no Warren Buffett, who holds on to companies for decades, but he's not obsessing over day-to-day market moves or quarterly earnings reports, either. He started developing his famous case against bond insurer MBIA in 2002, and had to wait till 2009 for it to pay off. At JC Penney, you could argue that it was the rest of the company's board that was too short-term-oriented to give Johnson's big plans a chance to play out (I'm not going to argue that, because things really were going terribly, but Ackman was on the long side of that particular disagreement). If you're concerned that a lot of mischief is wrought by Wall Street's obsession with short-term shareholder returns (and I am), Bill Ackman and his fellow activists really aren't the problem.

Become More Data-Driven by Breaking These Bad Habits

Becoming data-driven is a big, profitable deal, as recent academic work shows. I am delighted to see that more and more companies are looking to become more "data driven," and that the term is penetrating the lexicon ever more deeply. But not every manager is jumping on board with data. Many are threatened by data and work, perhaps subconsciously, to subvert its penetration into the culture. I call them "anti-datas."

But this post is not directed at the anti-datas. They're lost causes, beyond redemption and, frankly, on their way out. Instead, it's directed at those who are trying hard to become increasingly data-driven and in so doing build stronger futures for their companies, but who may have picked up some bad habits along the way. Over the years I've had the good fortune to work with plenty of individual decision-makers and groups, some terrific and some simply awful. From that work, I've distilled six bad habits that stymie managers and companies from taking full advantage of their data.

You prefer intuition over the data. We've all met managers who say things like, "I've been working in this industry twenty-five years and I've seen it all. I know I can trust my gut." They are proud of their experience and are skeptical of anything new. Interestingly, I find many managers who behave this way to be solid in most respects—they care about their companies and people. They desperately want to do the right things, and they are smart. But they go to great lengths to ignore, downplay, or subvert any evidence that suggests a better way. Some even re-interpret the data to reinforce their long-held mental models. The near-certain results are processes, operations, and teams that are increasingly out-of-date.

You rig the system. For some, the decision-making process involves developing the case supporting a decision after you've made it, while ignoring other evidence along the way. It is an especially perverse form of trusting one's intuition, which some might call "CYA." The Internet has made it easier—no matter what the opinion, there is always some data to support it. People figure out what you're up to and develop a healthy mistrust pretty quickly. So even when you are right, it becomes much more difficult to gain the support needed to execute your decision.

You second-guess others. The true spirit of second-guessing involves withholding potentially useful information, then pouncing the minute a decision goes wrong. We've all made mistakes and practically all of us have been second-guessed. Just because the trait is common, does not mean it is not destructive. Withholding information breeds mistrust and pouncing leads many to make more conservative and easily-defended, but sub-optimal, decisions. One observes this trait all the time in overly-political individuals and companies.

You have analysis-paralysis. Analysis-paralysis plagues people and companies that don't deal well with uncertainty. They can fall into the trap of seeking "just one more bit of confirmation" before deciding. They delay, delay, delay, seeking to make the perfect decision. It is easy for the paralyzed to argue that they are data-driven—after all, they are seeking more data! They don't realize that not making a decision is a decision in itself and can have consequences. Delay too long and the competitor may introduce that new product line first; a great candidate may go elsewhere; and an investor may withdraw its offer.

You employ group think. Group think involves packing a decision-making group with people who think in the same way and ignoring those with divergent views or data that points in a different direction. To illustrate the impact, imagine a situation in which there are one hundred options, several of which are "good" and one that is "best. Group think is akin to limiting yourself to only ten options. You greatly reduce your chances of arriving at a good one.

You have misconceptions of or arrogance about data quality. The antis are not opposed to data quality per se. More generally, they truly believe the little data they do use is of high-quality, even though they have no facts to back it up. But in some respects, these points don't matter, as they have great faith in their own abilities to detect and discount bad data, saying things like "I can spot an error a mile away." Finally, in some cases, they don't worry about data quality because they have such high opinions of their own intuition that they don't use the data anyway. Misconceptions about data make it easier to fall into all other bad habits.

Now take that hard look in the mirror. Look at the full list above and ask yourself, "Do I ever do that?" And if so, stop. It is of course, difficult to break multiple bad habits all at once. So if you're going to pick one to start, stop second-guessing others. More specifically, stop withholding and start sharing potentially useful information every chance you get. Doing so pays great dividends in the form of increased trust, better teamwork, and others sharing with you (though don't expect everyone else to be so forthcoming!).



Second, break the group think habit. This may be difficult, especially if you've hand-picked your management team and their careers depend on you. It helps to have a colleague who will provide direct, independent perspective. Give him or her a fair chance to "tell you you're full of it" before finalizing any important decision. And seek far more diverging opinions when they tell you this!

Finally, engage your management team in doing exactly the same thing for your organization. Make a pact with yourselves to call each other out any time you observe the trait. You need to provide true leadership here, as others will follow your example. Snap back at someone who tells you you're second-guessing and you've ended the exercise for good!

Instead, give and take feedback in an open, supportive manner. It's the only way to advance, and reap the benefits of, a data-driven culture.

The Eight-Minute Test That Can Reveal Your Effectiveness as a Leader

How can I determine if I am a good leader, or perhaps even a great one? What are my strengths, and do any rise to the very highest levels? I know I have some weaknesses (as everyone does), but are any of them so appalling as to derail my career?

Many people have asked us those questions over the years. For a truly comprehensive answer, we always recommend a well-constructed 360 evaluation, in which your own views of your strengths and weaknesses are enriched by those of your boss, your direct reports, your colleagues, and other associates.

But as a first step that you can do on your own, we've developed an abbreviated self-assessment which you can take here. That will give you some sense of what your leadership skills may be and how they compare to others, right now.

It will take you about eight minutes, and you will promptly receive a feedback report, which will compare the way you've rated yourself with similar self-scores of 45,000 leaders in our global database. The survey will also measure your current level of engagement and satisfaction in your leadership role.

Obviously, a brief self-assessment is not as valid as a more-extensive assessment that includes feedback from 10 or more of your colleagues, but it will help you understand which of the 16 leadership competencies we measure — such fundamentals as thinking strategically, displaying integrity, focusing on results, taking initiative, developing others, championing change, exhibiting expertise — are your likely strengths.



A score in the 90th percentile means you have an outstanding strength. A score in the 10th percentile (meaning you're worse than 90% of the people taking the test) may indicate a flaw so profound it could derail your career. We expect most of your scores will be somewhere in the middle.

But the answers may surprise you. You may think, for example, that your strong points are your technical skills only to find your own responses score you far higher on inspiring others than you might have believed.

With such an understanding you might embark on a personal development plan in which you move toward the goal of becoming an outstanding leader by developing a few of your middling strengths to the very highest levels. Sadly, we've found that fewer than 10% of leaders take the initiative to create a personal development plan with the explicit goal of becoming a better leader. Yet without a plan you are relying on luck and circumstance to make yourself more effective.

More's the pity since, as is often the case, we find a straightforward approach to be most effective: Once you identify your strengths, we've found, the surest path to improving your overall leadership effectiveness is to pick one and focus on improving that.

Which one should you start with? Think about which of the leadership competencies you have the passion and energy to pursue. Working to improve a competence that you're passionate about makes the possibility of change much more likely. At the same time, though, consider what your current organization both expects and needs from you. The intersection of your strengths, your passion, and your organization's needs defines the ideal place for you to target your development.

Once you identify a competence that meets those criteria, what's the next step? Can you turn a moderately scoring competency into a profound strength? The answer is yes, though perhaps not in the way you'd expect.

To improve a weakness, people typically use a linear approach. If you were a novice, for instance, who wanted to gain some technical expertise, you might take a class at the local university, read up on the subject, or ask an expert in your firm to be your mentor. But if you're already strong technically you won't get very much better with further classes or reading more than you already do.

Instead, you might use your already-strong technical skills to improve your leadership effectiveness if you learned, say, to communicate your expertise more effectively or teach those skills to your team. That is, you could strengthen your strength by developing skills that complement it, just as elite athletes do when they improve their already formidable talents through cross-training.

We have discovered in our research that between eight and 12 of these companion behaviors are associated with each competency. (You can see the entire set for all 16 differentiated competencies, and a fuller explanation of how to apply them, in the October 2011 HBR article "Making Yourself Indispensable.") By focused attention to applying these companion behaviors, leaders can and do make striking improvements.

What are your own greatest competencies? We look forward to hearing your thoughts about the results you discover.

How Apple Stores Can Keep From Turning Sour

What follows is a customer experience cautionary tale, illustrating the kind of lapse that can happen even at a company with a global reputation for being customer-centric. I suppose if it can happen at Apple Stores — meant to be a beacon of customer service — it can happen anywhere. But take note: beyond the caution is a tremendous opportunity, for Apple and other retailers.

I recently set up a Genius Bar appointment at my local Apple Store, for 9am sharp (when the store opens). I was the second person to take a seat at the Bar. While waiting — and waiting — for my Genius to show up (about 15 minutes) two or three groups of Geniuses came to the bar, looked intently at some device together, discussed, looked some more — but never said a word to me. When the Genius helping the first customer got done, he began tapping on his iPad. I was just a few feet away from him. After a few moments, I announced, "My man, I'm feeling invisible." The Genius, with a wry smile and hardly looking up from his iPad, assured me someone would be with me shortly. At that early hour, the store had many more blue shirts hanging around than customers. Yet at no time did anyone say, "Are you being helped?"

Since then I've mentioned the episode to two friends who themselves are avid Apple users. Instead of responding with, "Wow, that's never happened to me," they immediately related their own "Bad Apple" story.

Coincidentally, a recent article in the Wall Street Journal reports, among other things, that the last head of Apple Stores (post Ron Johnson) had changed the emphasis from customer service to sales and cost cutting. That's an old story in the business world, that typically doesn't end well — and one you don't expect a firm like Apple to illustrate. Sure enough, it's resulted in declining customer satisfaction, and Apple Stores' famous per square foot sales (the highest in retail) has declined this year.

Apple is now looking for someone to head up its retail operations, but some candidates have expressed wariness, saying that the company's top brass lack clear plans for the stores. Here are some suggestions to help Apple Stores fulfill their original promise, and get beyond it to a new kind of relationship with customers:

Build Real Community

I'm not talking about a social media effort of some sort. I'm talking about the real thing, live and in person. Apple now has more than 400 stores worldwide, an unmatched level of penetration into local communities. Those local communities, of course, contain legions of passionate Apple customers who are doing amazing things with Apple products. The stores, together with these customers, are potentially a customer community-building resource that could dwarf anything that Starbucks is doing.

Find Your Local Rock Star Customers

Instead of pushing the blue shirts to sell, push the stores to attract local "Rock Star" customers, who will in turn, introduce new life, and new motivated buyers into the Stores. In particular, find the customers who are doing amazing things with movies, gaming, workflow productivity, design, blogging, presentations — whatever your customers are most interested in. Find ones who are articulate, who like helping others, are appealing in appearance and demeanor. No doubt many of these folks already like to affiliate — perhaps they're blogging and drawing strong audiences. Get ready to deploy these customers using your Stores as a base. And don't worry about the cost of finding and engaging such folks. First, they won't be hard to find — these natural advocates have a way of making themselves known. They're always interested to build their "social capital." Second, when you invite them into your community building events, you'll find that they'll do amazing things to draw audiences and customers, and they won't cost you a thing.

Organize Live Presentations by Your Rock Stars

The Apple Store in my neighborhood is open from 9am to 9pm Monday through Saturday. That leaves wasted time and space. Why not try a morning commute presentation at 7am on "Seven Ways to Dramatically Increase Your Productivity." A Genius might be able to make such a presentation, but much more effective would be a local Rock Star entrepreneur — an impressive "peer" of other creative and successful customers — presenting cool things he's doing to improve his productivity using his iPad and iPhone. Then many more local entrepreneurs and business people would likely show up. Or try a "Late Show" (9 pm) by a local Rock Star developer showing how he's created amazing Apple-worthy Apps. You get the idea. And by the way, you can be sure that as soon as a high-profile customer knows he's been invited to present at an Apple Store, he's going to let all his friends know.

About Those Video Screens

During my extended wait time, I couldn't help but be struck by all the screens behind the bar containing staid looking Apple content that I had no interest in. Another wasted opportunity. Perhaps the most attention-grabbing business communications today are videos by customers showing how they're using new products they've purchased: Teenage girls on a shopping spree. Skateboarders showing their moves. Researchers showing how they conducted the experiment. And of course, Apple users showing the cool things they're doing with their iPhones, iPads or Macbooks.

Why didn't I see any of this during my recent visit? Also, if Apple were to start having interesting events in its stores, it could get fabulous video of those, too. Show customers who come into your store that it's not just a store, it's a community gathering place with all kinds of interesting things going on. Such activities will get local customers to sign up for your email lists so as not to miss out.

Orient the Customer Experience Around What Customers Can Accomplish

When the first Apple Stores were opened, they were organized around the firm's product lines as well as the things customers would want to do with the products — such as importing and editing movies. I don't see this in today's Apple stores. They look more like product displays you'd see in an ordinary retail store — iPads here, Macbooks there, iPhones to the left. I should see something that shows me how to Photoshop pics on my iPad; or how to configure Apple products for my kids; or the top 10 things I can do with my Mac/ iPad / iPhone to organize my life. There could be a couple of community tables in the store, with daytime presentations on these topics.

Such measures would, of course, require experimentation. But the results could be well worth it. There are three areas of huge, latent wealth that the Stores could play a central role in tapping: First, all of the capabilities and expertise that we Apple customers are carrying around. Second, going beyond the use of the physical Stores as mere ABS (always be selling) machines to build them into hubs for customer communities. And third, activating and leveraging the hundreds if not thousands of local Rock Star Apple customers who would jump at the chance to get involved, and to help build such communities. When this potential is unlocked, the devices would almost sell themselves.

IT Has To Deliver Great Tools — and Teach People to Use Them

In a workplace that is increasingly collaborative and knowledge-intensive, many CIOs plan to create value by delivering these capabilities effectively. No wonder collaboration and analysis tools make up the single largest category of IT project spend. But much of this value is being lost because employees lack the skills to use these resources effectively. In response, CIOs must rethink how IT provides employee support and training.

A recent CEB survey of 25,000 employees globally found that about half of an employee's contribution to business performance comes from their "network performance" — the ability to collaborate, to help others and, in turn, be helped by others, through activities such as teamwork, knowledge sharing, and peer coaching. Interestingly, network performance accounted for only about 20% of an employee's contribution to business performance a decade ago. Despite the growing importance of these skills, our survey found that only one in five employees is an effective network performer, the rest struggle to assist colleagues or make an impact when working in teams.

A similar story emerges around the ability to use data to make decisions. Another CEB survey found that more than 80% of employees collect data or use data for decision making. Even in traditionally transactional and process-centric fields such as manufacturing or customer service, more than half the employees undertake at least some knowledge work. Although almost everyone now does knowledge work, not everyone is effective at it. In fact, only 38% of employees have the skills and judgment to use data for decision making. The rest either blindly trust data regardless of its quality, or they are overly skeptical and ignore sound analysis altogether and go with their guts.

Here's the challenge for CIOs: IT is asked to deliver ever more capable tools for collaboration and analytics, but no one is responsible for ensuring employees have the skills to use them. The result is wasted investment, and an IT team that once again faces questions about value.

The whole C-suite has a stake in fixing this problem, and we believe that IT must play a part. We have seen progressive CIOs switch the focus of IT support and training from teaching employees about the functionality of a tool, to teaching them the skills they need to use the tool effectively in their jobs. Consider the following examples:

Assess Team Readiness for Collaboration. Before setting up a collaboration tool, the IT group at a leading industrial company provides the team requesting the tool with a simple checklist to assess their readiness to collaborate. The checklist measures the clarity of the team's objectives and workplans, and the strength of the relationship and communications between team members. It is used to flag potential problems within the team that can be remedied before the tool is deployed.

Hire Quants Who Can Coach. Many IT teams include a group of analysts who conduct analysis and produce reports. These individuals are highly skilled in analytic techniques and know the data inside out, but very few have the coaching skills to help others benefit from their expertise. However, a handful of organizations are redefining these analyst roles and changing the hiring criteria so that coaching and communication skills become as important as technical skills.

Teach the Decision, Not the Tool. The business intelligence team at a leading retailer revamped the training it offers the company's employees. In the past, employees were taught how to use the latest BI tools, now they can access a portfolio of resources to help them use the company's data to make smart decisions. For example, IT runs roadshows where employees learn how to capture new customer insights from a particular data asset, and provides e-learning with tips and tricks on spotting when data may be misleading.

While many IT leaders are reluctant to involve IT more deeply in training, these examples are all ways in which CIOs are taking capabilities IT already has — teams dedicated to collaboration and BI, expert data analysts, spending on employee training and support — and adapting them to ensure that money spent on collaboration and analytics pays back through greater employee productivity and insight.

Reinventing Corporate IT
An HBR Insight Center





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Avoiding the Schizophrenic IT Organization