Marina Gorbis's Blog, page 1584

Would You Wear That Company's T-Shirt in Public?

A client recently told me that he knew it was time to leave his previous job when he was no longer proud to wear the company's T-shirt in public. His comment is telling. The seemingly simple and innocuous act of wearing a company's T-shirt is actually a very personal and public endorsement that carries a degree of social risk.

My client's T-shirt problem reminded me of the time when I was working for Reebok's ad agency in the early 1990s.

During this time Reebok and Nike were blood rivals and neck and neck for the number one position in the market. A few years earlier, Reebok had come out of nowhere to outsell Nike with a soft, glove-leather shoe called the Freestyle. With the Freestyle, Reebok had identified a market that Nike had completely missed — women's aerobics. Sales really took off when Cybill Shepherd wore a pair to the 1985 Emmys. But by the early 90s, Reebok was having a tough time building on top of this success, and they began looking for their next hit.

Back at the No.2 spot, Rebook tried to develop a credible rival to Nike's "air" technology — the Energy Return System, a group of shock-absorbent tubes under the midsole of its shoes, and The Pump, an inflation device that provided personalized fit and cushioning. While each technology bumped sales, something was still missing. Reebok was doing a poor job of articulating a higher-order mission, a story that would help people understand what its brand meant, a story that set itself apart from Nike.

Nike had a rich and authentic connection to high performance athletics, which began when legendary running coach Bill Bowerman made his first experimental soles using the waffle iron in his kitchen and CEO Phil Knight sold shoes at local track meets out of the trunk of his car. Nike was a company of, by, and for athletes. Because of this rich heritage, people knew what Nike meant, in addition to what Nike made.

The average consumer's relationship with Reebok was much shallower. Sure, Reebok had a story (Cybill Shepherd wore them to the Emmys!), but that story didn't amount to anything substantial or meaningful. Despite its strong sales, the Reebok brand lacked meaning.

To get that story point across to Reebok, we devised a simple test that we called "The T-shirt Test." We put two stacks of identical gray T-shirts on a folding table on a Manhattan sidewalk. The only difference between the two stacks was the logo on the shirts: the Nike logo was on one stack, Reebok the other. We put a sign on the table, "Free T-shirts, One Per Customer," and retreated to a safe distance to film the result. One by one, as pedestrians saw the sign, stopped, and examined the T-shirts, they went for the Nike stack. When those were all gone, the Reebok shirts went, too.

People didn't hate Reebok. But when given a choice, they were quick to show their allegiance to Nike because its story was clearer, and therefore more useful for helping people express themselves and their beliefs. A Nike T-shirt signaled membership in the Nike tribe — a tribe that believed in something bigger than shoes or apparel. Nike was fast becoming a religion. Reebok was just a shoe company.

This lesson has never been more relevant. Today, we are awash in customer data of all kinds, but first-hand observations of real people in the real world (outside of a focus group room and outside of social media) are more important than ever; they can be an invaluable reminder of how clear and compelling (or confusing and boring) your story actually is.

The most important data you need to pay attention to is how well your customers understand your story and how they are using your story to advance their own. The story of your business can be as vital to your customers as air or water. It can help them navigate the complexities of their social world (and their social-media world). All the data in the world won't help you if you don't have a clear understanding of the story you are telling.

Know your story.

Who New CEOs Fire First

New research by RHR international shows which executives incoming CEOs are likely to replace, and highlights some differences between first-time CEOs and more seasoned chief executives. I interviewed Dr. David Astorino, Global Practice Leader for Senior Team Effectiveness, about the findings. Below is an edited version of our conversation.

Your survey showed that as much as CEOs had shaken up their senior team, looking back on it they wished they'd moved even faster. Why?

When they look back, and you ask them what you would have done differently, they almost always say, "I knew in my gut that was not going to work with that individual, and I wish I had trusted that gut feeling and made that decision faster." By delaying the transformation of a particular function or business unit, they're now six months behind. That's often were that comment comes from. There are some other factors, but that's the main one.

What are some of those other factors?

A lot of it relates to organizational knowledge. They hesitate because they don't feel like they know enough about what's going on. You'll also see a real difference between first-time CEOs and people who've been a CEO before, especially if that first-time CEOs is coming from outside the company. They don't trust themselves as much, and they tend to not be as suspicious, frankly, as CEOs who have been there, done that before. They tend to wait too long. CEOs who've been around the block a bit more say, "I'd rather risk losing institutional knowledge and get someone in there I trust."

HBR has published research suggesting that insider CEOs are more effective than outsiders. Could part of the reason be that outsiders replace so much of their staff with other outsiders, lacking that institutional knowledge?

It could be. But why do you hire an outsider? Either you couldn't develop an insider, or the external environment has shifted enough that you need someone who can come in and really drive transformational change. So either way, outsiders are often coming in to a tougher job. They're going to be driving change, and so they're going to need new people with new skillsets to drive the business forward.

So to that point about skills, how much of this is really about bringing in new skills, and how much of it is about what you mentioned earlier — just looking for people they can trust, people they're comfortable with?

It's really both. Every good seasoned executive will do two assessments of people. One is, they'll look at you and evaluate, "Do you have the right values and motivations for what I need on my team and what we need moving forward?" Can they trust you? The other big piece of it is, "Are you going to put the enterprise before your self-interest?" And that one is big. They need their senior team to make big decisions about where resources go, and sometimes that may disadvantage you. You may have to be selfless, give up some of your budget. So after they've looked at those two things, then they might go down that more methodical path of, "Do you have the capabilities to do what I need in your function?"

Speaking of functions, it wasn't terribly surprising to me that the CHRO and the CMO are two that are likely to leave. But why the General Counsel?

That was an odd one, and I don't have a great answer for that. Certainly we know that heads of finance and HR tend to move around a lot more because the skills are very transferrable, and in fact it looks better for an HR executive or CFO to show a breadth of industry. You actually get a bit disadvantaged if you've been in the same company or the same industry your whole career, as an HR person. But general counsel is a little different, because legal issues are often more specific to the industry. So I don't really understand that one.

What about the difference between insider and outsider CEOs — they really seem to replace different functional heads. Insiders are much more likely to replace the COO, for instance, while outsiders are more likely to replace the CFO. Why the discrepancy?

When a new CEO gets that [internal promotion], they want to be closer to the business than not, and boards usually want them to have their thumb on the pulse of the organization, rather than someone else. But CEOs do need to be less in the day to day operations, and become more externally focused. So they need to have the right person in that COO role.

When you're coming from the outside, the CFO role and the head of HR are the right and left wing of a CEO, they're the people CEOs come to trust most for obvious reasons. The CFO in particular is one where outside CEOs really need to get the person they trust.

If a CEO has been around the block before, they seem more likely to bring in the people they know can get the job done and they have a bigger and better network at the c-level they can bring in and rely on.

New CEOs don't have a good a sense of what good looks like. They don't necessarily know what a great CFO really looks like. They rely more on search firms.

What are some of the other differences between first-time CEOs and more experienced CEOs?

There are such differences. The leap is so great, especially if you're going into a very tough situation. You learn so much, so fast that when you get that next CEO job, you are so much faster in making decisions. You almost have a template.

That has pros and cons. The pros are that certain types of people really want to follow that kind of leader with confidence and declarativeness. Boards like that, too. The downside is — well, take your first-time CEO, who doesn't have the templates. The pros are that they often form really strong teams to go on a journey with them; you're going to help define the path. So those CEOs really get people to follow them who want to have impact, who want to shape the future, and who want to create those templates together.

Both can be very successful, but at different times you really want different types of leaders.

Why Brazilians Were So Quick to Protest Bus Fares

Recent protests in Brazil reflect not just opposition to higher bus fares but deep discontent with quality of life, according to Gallup. A December 2012 survey shows declines since 2010 in the proportion of citizens who are satisfied with four types of services: availability of quality health care in their communities, 25% (down 16 percentage points); local schools, 48% (down 9 points); local roads, 44% (down 9 points); and public transportation, 48% (down 8 points). Moreover, 70% believe corruption is widespread (up 9 points), and only 36% feel safe walking alone at night (down 12 points).

New Research: Flexibility Versus Face Time

When Yahoo! ended the company's telecommuting option for employees early in 2013, and Best Buy followed suit a week later by terminating its groundbreaking, decade-old flexible work program, Results Only Work Environment (ROWE), they joined a growing trend among organizations trading flexibility for face time. Prior to Yahoo!'s decision, Bank of America had drastically cut back on their popular My Work program that used flexible scheduling and telecommuting centers to help employees find a work environment and schedule that made them most efficient. And Zappos, Amazon's online retailer, also recently scaled back their flexible work arrangements.

In an age when technology enables us to work in a coffee shop just as easily as a cubicle, these dramatic reversals in access to flexible work arrangements in favor of face time—especially at e-commerce companies—drew contentious debate. Arguments addressed all angles of the debate: the rationale for these decisions, the merit of "presenteeism," the impact of telecommuting on productivity, the implications of eliminating flexibility for working parents, and consequences for the future of work. Reactions from all sides have been emotionally charged, and unending, signaling the deeply personal nature of this debate.

But despite all of this discussion, in the absence of hard data, many armchair opinions persist about flexible working arrangements, specifically with respect to who offers them, who uses them, and how important they are to attracting and retaining top talent.

To examine this common wisdom, Catalyst recently surveyed 726 high potential employees—MBA graduates around the world working full-time in both for-profit and non-profit firms across industries—about their experiences with, and perceptions of, flexible working arrangements. Their answers were revealing.

Flexible working arrangements are no longer the exception.

Despite all the attention that Yahoo!, Best Buy, and others have received recently for doing away with their flexible work arrangement policies, our research shows that they are in the minority among organizations today. Among our sample of high potential employees, 81% reported that they were currently working at a firm that offers flexible work arrangements of some kind. In addition to telecommuting, this includes flexible arrival or departure, flex time, compressed work weeks, reduced work/part-time, and job sharing. And this is true for both global and local organizations of all sizes and in both the for-profit and non-profit sectors. Flexible work options are in fact the rule, and not the exception, at organizations today.

Women and men use flexible working arrangements to the same extent — but men usually choose options with more face time.

Contrary to popular belief, our research revealed that women and men report using most flex options to the same extent throughout their careers. But this is only true for flex time and flexible arrival and departure—the flexible work options that do not adversely impact face time. We did find that women were significantly more likely than men to telecommute—working outside of the office where they don't have traditional face-time requirements—over the course of their careers. So while men and women are equally likely to use some flex work options, women are more likely to telecommute, which could unintentionally be creating a talent drain in companies by denying these women access to influential networks, senior-level sponsors, and advancement opportunities. As Joan C. Williams, founding director of the Center for Work-Life Law at the University of California, Hastings College of the Law, said in a recent New York Times article, "informally everyone knows you are penalized for using" flexible work arrangements. "I invented the term 'flexibility stigma' to describe that phenomenon."

Availability of flexible working arrangements is critical for organizations to maximize their talent pool.

Much of the debate around the termination of flexible work options centered on the rationale behind the decision. Both Yahoo! and Best Buy cited the importance of face time to successful collaboration and innovation, two elements deemed critical to turning these struggling organizations around. Yet our research shows that this move has unintended consequences that could stall their progress. We found that access to flex options impacts career aspirations.

High potential employees without access to flex options are less likely to aspire to the top.

And women working at a firm without flex work options were more likely to downsize their aspirations—a finding that remains true when comparing them to men working without flex options as well as women working at firms with flex options.

Clearly, lack of access to flexible working arrangements damages high potential employees' career aspirations, and is especially harmful to women's aspirations, impacting the number of women raising their hands for stretch assignments and promotions.

Offering flexible working arrangements is critical for organizations to maximize their talent pool and become employers of choice for high potential employees throughout the pipeline. Most competitors already offer flexible working arrangements; there are negative consequences for those that don't. Organizations need to decide if increased face time—or increased flexibility—is really in their firm's best interest. Catalyst's flexibility research can help leaders determine the best options for enhancing productivity, employee engagement, and organizational change in their company.

Daft Punk Didn't "Get Lucky" When It Created This Summer's Biggest Hit

Get Nostalgic


When the new Daft Punk record came out recently, I was tickled by its seventies-inspired beats and catchy hooks. My delight was tempered, however, when a segment of a popular morning show declared one of the tunes, "Get Lucky," to be the official song of the summer. Wait a second: How did this French duo, which hasn't had anything close to a hit since 2000, end up with a No. 1 on the digital charts of 55 countries (and being touted between segments about celebrity style and tips for grilling chicken)? According to Eric Spitznagel, there are a few key factors. The first is the construction of the song itself, which was meticulously crafted with the help of veteran musicians over a span of five years. Another was a small-scale marketing campaign that focused on what Daft Punk's 38-year-old Thomas Bangalter calls "a seduction." "You cannot make people excited by giving them everything," he says. "It's a process of tempting, of teasing, of creating desire." This slow rollout involved billboards showing nothing but an image of the band members in their iconic helmets and TV commercials that contained instrumentals with no mention of the song or release date. The song also played to nostalgia – the music was made with real instruments (not computers), and the marketing strategy embraced old-school methods (billboards and TV) that eventually became fodder for online conversation. There's much more nuance in the Businessweek article, but suffice it to say that Daft Punk did pretty much everything right. And, yeah, I'm still listening. (For more summer hits from as far back as 1962, enjoy this list from NPR.)

Twitter Isn't a Cash Register

Email Is Crushing Twitter, Facebook for Selling Stuff Online Wired

Almost every company is on Facebook and Twitter. But that doesn't mean every company should try to sell products directly from those social platforms. New research from Custora finds that email — yes, creaky old email — beats both for making sales. The marketing-data firm discovered that online retailers’ rate of acquiring customers via email has quadrupled over the past four years to 7%. Facebook's percentage didn't even come close, and Twitter essentially flatlined. Of course, none of these ways to attract customers approaches the effectiveness of search: Custora found that Google and the like create 50% more valuable customers than average (i.e., people likely to buy stuff). Email customers clock in at 11% more valuable, Facebook customers are of average value, and Twitter customers are 23% less valuable than the mean. The problem may be that no one has come up with a good social-sales strategy yet; or maybe Twitter's role isn't product promotions at all.

Like the 1916 Giants

Big Business Continues Its Winning Streak in Health Reform Wongblog

Perhaps the Obama administration didn't think it was asking too much: Under its health care overhaul, each business employing more than 50 people would have to provide workers with health insurance. The fine for not doing so would land in the $2,000 to $3,000 range — pennies compared with the $16,000 it costs, on average, to insure one person on an employer-sponsored plan. And yet on Tuesday, the administration pushed this part of the reform package back for at least a year, with a continued fight from businesses and trade groups expected. Wonkblog's Ezra Klein, for one, hopes they succeed. He argues that the type of mandate in the plan isn't a very good one, as it doesn't incentivize companies to hire full-time workers. In fact, he doesn't think employers should be in the health-insurance game to begin with. But because, in the near term at least, we're stuck with companies being at the center of how Americans get care, Klein calls on Congress to really figure out how to do the employer mandate right. In the meantime, we wait.

Can Seaweed Rescue Us All?

A Green Alternative that Might Just Save the Planet The Guardian

It grows far more quickly, and turns sunlight into energy five times faster, than land plants. Farming it on a large scale for energy use won’t raise food prices. Its cultivation doesn’t require fresh water. And farmed at scale, it could provide hatcheries for fish and trap climate-warming carbon on the seabed. It’s kelp, and, reports The Guardian, it’s an industry on the threshold of taking off, since a Californian firm last year produced genetically modified bacteria that can produce about 1 kilogram of ethanol from 3 kilograms of dried seaweed. In Vietnam, shrimp farmers are raising their incomes by switching to seaweed cultivation. Europe is spending tens of millions of euros on nine pilot projects. Governments and companies in China, Chile, the U.S., and India are investing in projects of their own. Biofuel development can be bootstrapped by high-margin alternate uses, since seaweed is also used to produce cosmetics, plastics, and vitamin supplements—the huge Chinese industry was founded on providing iodine to the country’s growing population. The biggest barrier, says The Guardian, is that seaweed cultivation is labor intensive. Why is that a problem, exactly? —Andrea Ovans

Party Car

China's Luxury Car Could Make Foreign Automakers See Red China Economic Review

To make real money in China, you don’t want to sell to just the country’s emerging middle class. You want to sell to the Communist Party elite, whose members have a penchant for spending money. Back in the day, Chinese state-owned automaker FAW Group excelled in this market. Its sedans were often seen carrying leaders such as Mao Zedong and Deng Xiaoping. It was later eclipsed by foreign luxury brands, but it’s making a comeback: As part of his anti-corruption campaign, China’s new president, Xi Jinping, says government officials shouldn’t be seen driving high-end foreign vehicles. This at just the moment when FAW is launching a new version of its Hongqi, or Red Flag, luxury car. The biggest loser may be Audi, which had become a favorite of party officials. Trivia fact: If the 80-million-member Communist Party were a country, it would be the world’s 17th largest. —Andy O'Connell

BONUS BITS:

Who Wants to Celebrate July 4th Anyway?

What's a Royal Baby Worth? To the British Economy, $376 Million (Christian Science Monitor)
Weird Wimbledon Threatens to Upset Ratings and Ads (Marketplace)
Jane Austen Could be Face of £10 Note (The Telegraph)

Successfully Integrate Your Work, Home, Community, and Self

You can be a committed A-player executive, a good parent, an attentive spouse, and a healthy person with time for community engagement and hobbies. How on earth do you do all that? Stop juggling and start integrating. Begin with a clear view of what you want from — and can contribute to — each domain of your life (work, home, community, and self). Carefully consider the people who matter most to you and the expectations you have of one another. Then experiment with some minor changes and see how they affect all four domains over a short period.

If an experiment doesn't work out in one or more areas, you can make adjustments or put an end to it, and little is lost. But if it does work out, it's a small win. Rack up enough small wins, and you're well on your way to a life that's less stressful and more productive.

Skeptical? Many people are when they first hear about this approach. But time and again, I've seen business professionals use it to find the greater harmony they're seeking. Working with Harvard Business Review, I've created a free interactive assessment test to help you identify misalignments between the amount of time you spend on one area and how important it is to you. The test also incorporates how satisfied you are, generally, in each of the four areas. Your results will highlight gaps between your values and your actions and ways to get started addressing those gaps. Click here to get started on the assessment.

One of the best ways to address the incongruities that may surface via the assessment is to structure an experiment focused on improving your well-being and performance in all four domains of your life. The assessment results will provide more detail on how to get started, but to show what an experiment can look like in practice, here's a story of a Target executive I worked with who experimented his way toward improving his well-being and performance.

David is a VP accountable for a multibillion-dollar P&L. (His name and title are disguised.) For years, he felt a relentless tension between the domains of work and home, as many of us do: "I spent most of my waking hours at work," he explains, "and I always shut down from work at home." But keeping things separate like this hurt his relationship with his wife. They talked about the kids, nothing more, because that was all they had in common. And at work, David never had enough time to prepare for all his meetings.

So he devised an experiment. Before leaving the office each day, he'd look at the next day's schedule and pick one big meeting to get ready for. On his drive home — at a decent hour — he'd think about what he could do and say at that meeting. When he got home, he'd run some ideas by his wife.

It worked beautifully: "This gave us something new to talk about each day, it gave her a much better understanding of what I do, it engaged her, and it enhanced our relationship because we were having richer conversations. My wife made good suggestions — and I've had better meetings as a result."

The experiment has also had a positive effect on David's team. After telling his direct reports he was changing his hours in the office, one of them approached him with a request to adjust her schedule, because it was aggravating a medical problem. Another employee said he felt empowered to take care of an aging parent during the day when he needed to. He didn't feel guilty about it — David's own actions made it clear that it was OK.

"The example I was setting before was work first, work first, work first," David reflects. "Now I might be in the office for fewer hours, but I'm making faster and better decisions. And my wife has more understanding when work does have to come first. In the long-term, this means that I'm a more engaged leader for Target without an unmanageable tension between my wife and my work."

Interested in identifying your own misalignments and structuring experiments to improve them? Let's get started.

Adapted from "Be a Better Leader, Have a Richer Life" (HBR April 2008) and content posted on hbr.org on February 21, 2013. Stew Friedman's thoughts on how to structure experiments to better your four-domain integration can be found in the HBR Press book, Guide to Managing Stress.

Successfully Integrate Your Work, Life, Self, and Community

You can be a committed A-player executive, a good parent, an attentive spouse, and a healthy person with time for community engagement and hobbies. How on earth do you do all that? Stop juggling and start integrating. Begin with a clear view of what you want from — and can contribute to — each domain of your life (work, home, community, and self). Carefully consider the people who matter most to you and the expectations you have of one another. Then experiment with some minor changes and see how they affect all four domains over a short period.

If an experiment doesn't work out in one or more areas, you can make adjustments or put an end to it, and little is lost. But if it does work out, it's a small win. Rack up enough small wins, and you're well on your way to a life that's less stressful and more productive.

Skeptical? Many people are when they first hear about this approach. But time and again, I've seen business professionals use it to find the greater harmony they're seeking. Working with Harvard Business Review, I've created a free interactive assessment test to help you identify misalignments between the amount of time you spend on one area and how important it is to you. The test also incorporates how satisfied you are, generally, in each of the four areas. Your results will highlight gaps between your values and your actions and ways to get started addressing those gaps. Click here to get started on the assessment.

One of the best ways to address the incongruities that may surface via the assessment is to structure an experiment focused on improving your well-being and performance in all four domains of your life. The assessment results will provide more detail on how to get started, but to show what an experiment can look like in practice, here's a story of a Target executive I worked with who experimented his way toward improving his well-being and performance.

David is a VP accountable for a multibillion-dollar P&L. (His name and title are disguised.) For years, he felt a relentless tension between the domains of work and home, as many of us do: "I spent most of my waking hours at work," he explains, "and I always shut down from work at home." But keeping things separate like this hurt his relationship with his wife. They talked about the kids, nothing more, because that was all they had in common. And at work, David never had enough time to prepare for all his meetings.

So he devised an experiment. Before leaving the office each day, he'd look at the next day's schedule and pick one big meeting to get ready for. On his drive home — at a decent hour — he'd think about what he could do and say at that meeting. When he got home, he'd run some ideas by his wife.

It worked beautifully: "This gave us something new to talk about each day, it gave her a much better understanding of what I do, it engaged her, and it enhanced our relationship because we were having richer conversations. My wife made good suggestions — and I've had better meetings as a result."

The experiment has also had a positive effect on David's team. After telling his direct reports he was changing his hours in the office, one of them approached him with a request to adjust her schedule, because it was aggravating a medical problem. Another employee said he felt empowered to take care of an aging parent during the day when he needed to. He didn't feel guilty about it — David's own actions made it clear that it was OK.

"The example I was setting before was work first, work first, work first," David reflects. "Now I might be in the office for fewer hours, but I'm making faster and better decisions. And my wife has more understanding when work does have to come first. In the long-term, this means that I'm a more engaged leader for Target without an unmanageable tension between my wife and my work."

Interested in identifying your own misalignments and structuring experiments to improve them? Let's get started.

Adapted from "Be a Better Leader, Have a Richer Life" (HBR April 2008) and content posted on hbr.org on February 21, 2013. Stew Friedman's thoughts on how to structure experiments to better your four-domain integration can be found in the HBR Press book, Guide to Managing Stress.

How Google Flu Trends Is Getting to the Bottom of Messy Data

Churning through, tabulating, and modeling millions of search queries every day, Google Flu Trends can measure, a full two weeks before the CDC, the incidence of influenza-like illnesses (ILI) across the U.S. Any official response to a flu pandemic, such as vaccine distribution and timing, could be greatly enhanced with such an early warning. And while not billed as an ersatz measure, Google Flu has had an uncannily high correlation with the CDC's own slower, yet more assiduously produced estimate of ILIs.

Until this past flu season, that is. The algorithm drastically overestimated the actual flu rate, in some cases by a factor of almost two, according to a report in Nature News. It's still not 100% certain why it failed, especially since Google isn't speaking publicly about it just yet.

Big data systems like Google Flu are complex and unwieldy beasts. They can (and sometimes do) fail to give us the insights we think they should. They're temperamental, messy, and can break down when the data or model changes unpredictably. So as your business adapts to making more and more data-driven decisions, from managing supply chains to hiring the best employees, how can you be confident in your big data decision making process?

I spoke to Rajan Patel, co-inventor of Google Flu, and he explained the two strategies in their assurance process: algorithms that detect and mitigate aberrations in search frequency that might throw their estimate off, and people to get to the root cause of system failures so that biases get rooted out of statistical models. The algorithms manage most of the day-to-day sanity checks before releasing estimates to the public, and the deeper systemic investigations by people are sparked by abnormalities like the H1N1 outbreak in 2009 and this past winter's flu season.

The Google approach suggests a certain data vigilantism comprised of smart people wielding smart algorithms to act as sentinels against faulty inference. Big data vigilantism can help your company cope with two of big data's main issues: messiness and sampling bias, and ultimately help contribute to growing your confidence in wielding big data in your decision process.

Messiness

At the core of the issue with flu measurement (and most projects involving large amounts of data) is ambiguity; both in the intent of a search query, and in the sense that the reference rate from the CDC measures influenza-like illnesses, which might include non-flu ailments that cause fever, cough, or sore throat. Search terms directly relating to a flu symptom or complication are conflated between people who actually have the flu and those that are expressing concerned awareness about it — and CDC measurements mingle people who actually have the flu and those that are just expressing some flu-like symptoms. Trying to determine the actual flu incidence requires some careful disambiguation. This is one place where smarter algorithms may come into data vigilantism: pulling out the information that you actually want to measure from your big, messy pile of data.

Researchers at Johns Hopkins are tackling an even more chaotic source of data for measuring flu: tweets. But by implementing some careful linguistic reverse engineering, their algorithm is able to take into account the context of the tweet and disambiguate the meaning. For instance, they noticed that when the word "flu" was used as the subject in a sentence it suggested that the message was more likely to be about awareness than infection. This pattern, or "template", then gets encoded into the algorithm as something predictive of awareness tweets, along with many other linguistic templates. Using the smarter algorithm their system was able to filter out the awareness messages and focus on the infection tweets, scoring a correlation much closer to that of the CDC.

Sampling Bias

Microsoft researcher Kate Crawford points out another pitfall of working with big data: sampling bias. But this again is something that smarter algorithms can also help correct for, if you make the effort to understand the bias in your data and adjust for it in the algorithm. For instance, we know from Pew surveys that Twitter usage skews towards younger age demographics. Any flu measurement based on Twitter messages would necessarily entail that demographic bias. To correct for this, we need to know the age of each person sending a flu-related Tweet, but thankfully we can estimate that from data too! In fact, researchers at UMass Lowell are already working out the details of integrating age-estimates into flu prediction from social media. So with a little bit of investigation to understand the bias of a sample, we can often correct for it downstream with better algorithms.

The Importance of "Why?"

Messy, ambiguous data and hidden biases underscore a growing need to hire and train data vigilantes to watch over and ask "why?" about our every interpretation from big data. Big data kitsch promotes a world of blissful ignorance in its focus on correlation without explanation. But the data vigilantes do need to understand "why", sometimes to debug a spurious correlation or systemic failure (like we saw with Google Flu Trends), and other times to be able to develop a smarter method to measure the thing that we really want to measure.

It can be tempting to use data as a crutch in decision-making: "The data says so!" But sometimes the data lets us down and that exciting correlation you found is just a by-product of a messy, biased sample. More advanced algorithms can sometimes help cut through the mess and correct the sample, and smart skeptics can help step back, reflect, and ask if what the data is "saying" actually fits with what you know and expect about the world. Hiring and training these data vigilanties as well as inculcating a healthy dose of data skepticism throughout your culture and team can only help bolster the quality of decisions you ultimately make.

A Performance-Appraisal Conundrum: What Would You Do?

After 30 years of consulting, I thought I had run across every question regarding performance management. But a client recently came up with an intriguing query that I hadn't encountered before.

Bob wrote:

Sometimes it happens in our business that a management employee may be involved in a significant incident immediately after the close of the annual performance appraisal cycle that impacts their performance rather negatively. This particular incident happened early in the month of April, right at the time that his manager was writing his performance appraisal. Since the incident was significant, the manager decided to include it in the performance review even though our standard performance review period is from April 1 to March 31.

The reason I ask about this is that the employee in question recently made a formal complaint protesting the fact that since our review period is from April 1 to March 31, and the incident happened in the second week of April, 2013, it never should have been discussed or even considered in the 2013 performance appraisal. The manager, he argued, should have waited until she wrote his 2014 performance appraisal a year from now to raise the issue on the performance review.

Do you know if this is a standard or common practice with other companies? How should this be handled? Who's right? Who's wrong?

I wrote back telling Bob that I don't know of any company that has a formal "rule" or even a clearly understood guideline on how to handle this kind of unusual situation. But, I told him, I know exactly what I'd do.

If the individual's manager came to me for advice, I'd advise her to handle it exactly as was done in the incident he described. Include it in the performance appraisal for the April, 2012 - March, 2013 period, even though the incident happened a week or two or three after the end of the appraisal period. Appraisal periods are always arbitrary, and in this case it happened close enough to the 4/1 - 3/31 period to make it justifiable to include it, particularly since it was a "significant incident."

The purpose of the performance review is to provide the employee with the manager's opinion of the employee's performance, based on that performance over the past year. This incident is certainly on the manager's mind, and it would be a mistake of serious obfuscation to force the manager to wait 12 months to include it in a review. In that 12 month period the impact of the incident will have either totally been forgotten, or the seriousness of it will have been lost in the fog of faulty memory (which is precisely what the employee is hoping for). Why let that happen?

I'm also concerned, I told Bob, about the character of an individual who raises the smokescreen of, "This didn't happen until immediately after the close of the appraisal period so you can't use it against me." What kind of employee—particularly a management employee—does a response like that suggest that we're dealing with? Certainly not one I'd want on my team.

So I say, go ahead and include it. There's no question about the fact that it happened and it needs to be part of the record.

Incidentally, I pointed out to Bob, the reverse is also true. If an employee does something in early April that represents a singularly remarkable achievement, I sure wouldn't wait 12 months to include it in the performance review. And I doubt that any individual would complain that her boss included a reference to medal-of-honor-worthy performance in her performance appraisal, even though this particular triumph happened a week after the appraisal period closed.

Make Good Decisions Faster

In her recent HBR article "Transient Advantage," Rita Gunther McGrath describes how "fast and roughly right decision making will replace deliberations that are precise and slow." While most leaders couldn't agree more, the challenge is how? How do you know the difference between "roughly right" and "not at all right"? And just how much time can elapse before "fast and roughly right" becomes "precise and slow?" Hours? Days? Months?

A simple, flexible Know-Think-Do framework can enable leaders and their teams to immediately start making these fast and roughly right decisions. To paraphrase Einstein, this framework is "as simple as possible, but not simpler."

1. Know the ultimate strategic objective. The biggest hurdle to fast and roughly right decisions is criteria overload. Trying to weigh every possible objective and consideration from every possible stakeholder shoots the decision process in the foot before you even get off the starting line. Of the seven or eight possible objectives you would love to meet with this single decision, which one or two will make the biggest positive impact? Of all the possible stakeholders which one do you least want to disappoint, and what is the objective they care most about?

2. Think rationally about how your options align the ultimate objective. The vast majority of judgment errors can be eliminated simply by broadening our frame of reference. The quickest, easiest, most effective way to do this is by "consulting an Anti-You" before you make every decision. As one banking executive explained, "It's amazing how many poor decisions can be avoided simply by asking one other person for their opinion." An impressive amount of empirical research backs up his observation. (The article "How Decisions Can Be Improved," spearheaded by Katherine Milkman of Wharton, provides an excellent summary. [PDF])

Consulting an anti-you works in two ways. The act of explaining your situation to another person often gives you new insights about the decision before the other person even responds. And the fresh perspective they offer in response is the second bonus.

3. Do something with that knowledge and those thoughts. After you've clearly defined the primary strategic objectives and laid out your research and thinking with one or two key Anti-You's, it's time to call it quits on all of the planning, strategizing, number-crunching, and critical thinking. You simply must select one option while letting go of all the other "good" options. It is helpful to remember here that in the real world, "perfect" options are a myth. Decision-making will always be an exercise in coping with an unknowable future. No amount of deliberation can ever guarantee that you have identified the "right" option. The purpose of a decision is not to find the perfect option. The purpose of a decision is to get you to the next decision.

What makes the Know-Think-Do framework particularly powerful for organizations ranging from tiny startups to behemoth banks and software makers is it's scalability across every level of an organizational hierarchy. For example, a "fast and roughly right decision" might mean two weeks for the division heads at a Fortune 500 bank to decide how to remain competitive while also being compliant with a new government regulation. Or "fast and roughly right" might mean no more than 20-30 minutes for sales managers at the same bank's commercial lending team in Chicago trying to make a customer account decision.

Regardless of where you are or how big you are, this framework enables all corners of an org chart can share a common language and approach for making sound, timely decisions. So get started.