Engagement Measures Downward

Let's look at one of the most popular engagement models in the world today. This particular framework categorizes three types of employees:

1. Actively disengaged: unhappy employees who undermine their coworkers
2. Not engaged: employees who are checked out and sleepwalking through their jobs
3. Engaged: employees who work with passion, feel connected to the company, and help move the organization forward

In this model which you can see in figure 3.1, an engaged employee should be the minimum of what an organization should expect from anyone. If we're being honest, then it's fair to say that an engaged employee should be an average employee. In grading terms this would be a C. Hiring for passion and the ability to drive the organization forward is something any business leader looks for and asks about during an interview. If employees don't help move the company forward and they don't feel a connection to the company, then they have no business being there and perhaps we should also ask how they got there to begin with? Organizations bringing in these types of employees must review their hiring practices. I know it's harsh but that doesn't make it any less true.

A not engaged employee is the equivalent of a D, and an actively disengaged employee is a big fat F. So looking at this model, the best that an organization can do is hire an average employee who will perform as expected. Everyone else is either below or very below average. Imagine what kind of an organization this creates, better yet, we know what kinds of organizations this creates as evidenced by the current engagement scores around the world.

What about the employees who do feel a sense of passion and who go above and beyond what is expected of them to help others? Or, what about the super employees who constantly exceed expectations and act as brand cheerleaders even when not at work? These types of employees don't fit into the traditional model of engagement. This is what I mean when I say employee engagement is stuck measuring downward instead of upward. You can be only a C employee or worse when looking at this type of a model.

Engagement Has Become the New Annual Review

Organizations question the value of annual employee reviews yet for some reason are okay with measuring employee engagement every year. This makes no sense. In many cases employee engagement surveys are simply replacing the annual review and are becoming the very thing that organizations are trying to get rid of! There is no right answer for how often you should measure employee engagement. That's something I believe your people should control and be able to do when and where they want as often as they want. Organizations need to understand that this is a dynamic and fluid thing that changes constantly. We are not light switches that are either on or off.

Anything related to people should be measured continuously. Perhaps you have a short single‐question pulse survey weekly, monthly culture snapshots, semiannual engagement reviews, and a larger state of the company survey. Of course, this is just an illustrative example to show that doing one annual survey may not give you an accurate reflection of what's going on inside of your company. Some companies I've spoken with don't even look at people metrics annually. They might do so only once every few years! If annual reviews don't do a good job of measuring employee performance, then annual engagement surveys don't make much sense for measuring the pulse of the organization.

Another approach that some organizations, such as General Electric (GE), take is to run constant surveys to random employees. So you might do a survey for 1,000 employees one month, another thousand the following month, and so on. The idea is to get employee data and feedback constantly from a representative sample size of the organization. For an organization like GE that has over 300,000 employees around the world, this approach makes much more sense than trying to do one annual survey. I'll talk about this a bit later in the book as well.

Engagement Tends to Look at the Effect but Not the Cause

In most models the ideal scenario for organizations is to get as many engaged employees as possible. They do this maniacally as if they are collecting Pokémon characters. It's as if for every engaged employee an organization gets, it will level up and will finally be able to take on that giant monster! Unfortunately, many organizations get so stuck focusing on engagement that they forget to take a step back to understand what causes engagement to begin with let alone understand the impact that engaged employees are having on the organization. This means that engagement just boils down to a number, and a number without context is quite useless. If you recall the famous book and movie The Hitchhiker's Guide to the Galaxy, the answer to “What's the meaning of life?” is 42. It's just a number as are most employee engagement scores that organizations receive. You scored a 68? Wonderful! A 92? Even better! Now what? Does this mean if you get to 100 you can stop? See what I'm getting at here? The cause is employee experience; the effect is an engaged workforce.

Engagement Surveys Are Exhaustingly Long

It's common for employee engagement surveys to be well over 100 questions long that ask pretty much everything and anything. This makes me think of my college days when I had to take multiple choice tests on scantrons (remember those?). Those exams were around 30 to 40 questions, and sometimes we even got a 15‐minute break! Who in his or her right mind would want to sit and take an exam about his or her organization, and more important, who would actually sit through and answer all the questions honestly?! Speaking of honesty, let's not forget that employee engagement surveys can also be manipulated. I once spoke with a chief human resources officer of a global company who told me that if she wanted to increase her employee engagement score quickly, then she would ask employees to take it once on a cloudy, rainy day and then again on a sunny day. Boom! Ten point improvement! Some organizations also have the scary habit of manipulating their engagement scores by either offering incentives to get people to score higher or reprimanding employees who don't score their organizations high enough.

Engagement Acts as an Adrenaline Shot

One of the things that I find quite fascinating is when people start working at an organization, they are already engaged. Rarely have I talked to an employee just starting out at an organization who says, “Man, this job is terrible!” The exact opposite is actually true. When employees start working for an organization, they are typically excited to be there and are very much looking forward to being a part of your team and making an impact. Think back to the jobs you have had in the past. You may have been a bit nervous or scared when starting a new job, but chances are that you rarely started being unhappy or disengaged. So something happens to turn these already engaged and happy employees into unhappy and disengaged people. Right about this time the organization does one of its employee engagement surveys, and when it sees the negative results, managers say, “What? Our engagement scores are that low? Quick, we need to do something!” At that point some new perks might be introduced. Maybe a flexible work approach is implemented, some office layout changes might happen, and perhaps catered meals a few times a week are introduced because clearly free food makes us happier. Then things improve a bit on the engagement score temporarily before dropping off again and the same cycle repeats itself as you can see in figure 3.2. Basically engagement in many organizations acts as an adrenaline shot to temporarily boost employee happiness and satisfaction whereas employee experience is the ongoing design of the organization. Unfortunately engagement efforts simply feel like manipulation and thus doesn't create trust or loyalty and does nothing to unlock human potential which also means no business impact for the organization.

Employee engagement has been a wonderful tool for us to think differently about our organizations, but it's also been used as a bit of a crutch to justify the existence and importance of human resources (HR) as a function. We also have to remember that just because you measure something doesn't mean you improve it. While there's nothing wrong with continuing to measure employee engagement, it's time for us to look at a new approach for a rapidly changing world that is focused on the long‐term designing of employee experiences which then yields an engaged workforce.

In fact, I believe that employee engagement can and should simply be measured by asking employees one question. What that question is can certainly vary from one organization to the next. When doing research for this book, I wanted to say it should be something along the lines of “Do you wake up every morning wanting to go to work?” Although this type of a question is tempting to ask, I don't think it's the right approach. In other words how an employee feels is not a good indicator of engagement, but what he or she actually does is. This is why I think a question such as “Do you show up to work every day with the intention of helping others succeed?” is far better suited to measure engagement. Success in this case is a very subjective metric that can mean anything from helping people feel good to actually helping them deliver on a project, but in this case the subjectivity is a good thing. When I spoke with Pat Wadors, the CHRO at LinkedIn, she told me that if she could pick just one way to measure engagement at her company, it would be “If employees show up to work each day wanting to create a sense of belonging for others.” In Pat's case she has the data to back up the significant positive correlation between this criterion and employee engagement. Focusing on an action is better than focusing on a feeling because it looks at a tangible impact.

Beth Taska is the CHRO of the world's largest gym, 24 Hour Fitness. When I met with her in 2016, she echoed what Pat told me. The whole point of employee engagement is to unlock the discretionary effort within employees. This is the amount of effort that employees could put in if they actually wanted to. But what does that mean? If you think about most of the interactions you have daily with various brands, you will realize that they are very linear and static. There is very little differentiation. Whether you go to a retail store, a supermarket to purchase groceries, a check‐in gate to board a flight, or a restaurant to order food, you pretty much know what will happen and what to expect. It's always the same thing. So how is it that some organizations are able to go above and beyond to deliver customer experiences? The answer is discretionary effort. What organizations like LinkedIn and 24 Hour Fitness have figured out is that when you focus on employee experiences, employees go above and beyond to help not only one another but also your customers. Discretionary effort is measured in terms of an action, which is why I believe that measuring something like “if employees help others become more successful” is more meaningful and telling than simply asking, “Do you feel a connection to the organization?”

At organizations like wireless provider T‐Mobile, this level of discretionary effort all comes down to the impact that employees have on their customers. I spoke with Marty Pisciotti, T‐Mobile's vice president of employee careers, who told me that across T‐Mobile in the United States, every employee knows the first line of the company values, “Frontline first, because customers are first.” T‐Mobile believes that frontline employees always come first because the better they are treated, the better they will treat their customers. T‐Mobile realized that when employees feel like the company cares, they start to act more like owners who are empowered to truly go above and beyond a traditional job description. To further get this point across, the company introduced a program over three years ago that gives all employees—including those in retail and customer care call centers—stock in the company, which is vested over a three‐year period. These are free shares in the company that T‐Mobile gives to all employees to help them feel like they are truly making an impact on the business, are vested in the success of the organization, and are able to unlock their maximum potential.

While employee experience needs to look at many aspects of the organization and requires several questions to determine and measure, employee engagement needs just one. So what's the one question you could ask your employees to determine whether they are indeed engaged? Go ask it.

Skills Gap and Talent Shortage

A McKinsey Quarterly article by Richard Dobbs, Susan Lund, and Anu Madgavkar titled “Talent Tensions Ahead: A CEO Briefing” stated that “new research from the McKinsey Global Institute (MGI) suggests that by 2020, the world could have 40 million too few college‐educated workers and that developing economies may face a shortfall of 45 million workers with secondary‐school educations and vocational training. In advanced economies, up to 95 million workers could lack the skills needed for employment.”⁴ The most recent ManpowerGroup Talent Shortage Survey of “more than 41,000 hiring managers in 42 countries and territories found that 38% of employers are having difficulty filling jobs.”⁵ There is little agreement on what is causing this skills gap, what the potential solutions are, and whether the skills gap is even a real thing! Most of the executives I speak with acknowledge that the skills gap is real. Perhaps what makes this even more challenging is that we aren't sure what the jobs of the future will be or when they will be here. Consider that by the time most people graduate from college, the skills and the things they have learned are mostly rendered obsolete. This means organizations are looking to hire employees for jobs that don't yet exist. Not only do we have a skills gap, but we also have a skills uncertainty. The number one thing that potential and current employees can do to succeed in this type of environment is to learn how to learn. In other words, have the ability to learn new things regularly and apply the things that you learn to new and current situations and scenarios. This is further evidenced by the dozens of publicly available conversations I have had with CHROs at the world's largest companies. You can listen to and read about all of these discussions by visiting https://thefutureorganization.com/future‐work‐podcast/.

What's fascinating is that organizations that focus on creating employee experiences aren't feeling this skills gap as much as those who aren't. It appears that in the coming years, organizations are going to want to hire people, and there just won't be enough high‐skilled labor to go around.

Changing Demographics

According to a report by Robert I. Lerman and Stefanie R. Schmidt called An Overview of Economic, Social, and Demographic Trends Affecting the US Labor Market:

BLS [Bureau of Labor Statistics] projections imply that over the next decade, 40 million people will enter the workforce, about 25 million will leave the workforce, and 109 million will remain. Although only a modest reduction will take place in the overall growth in the workforce (from 1.3 percent per year to 1.1 percent per year), the composition of growth will generate rising shares of young (under 25) and older (45 and over) workers and a decline in the share of middle‐age workers.⁶

We are already starting to see this trend. Today, millennials are already the largest demographic, surpassing baby boomers in 2016. By 2020 they are expected to comprise 50 percent of the workforce, and by 2025 this is expected to be 75 percent of the workforce. We also see Gen Z (the generation after the millennials) creeping into the workplace as well, and they currently comprise over 25 million people in the United States alone. Not only that but also the labor participation rate in the United States appears to be gradually yet consistently shrinking. This changing mix of demographics brings new values, attitudes, expectations, and ways of working. Still, this isn't new. Our organizations have always had to adapt to new generations entering the workforce, but the overall sense is that previous adaptations were very slow and gradual and have now become more aggressive.

Changing Face of Talent Competition

In the past organizations used to compete on a few levels, which were typically skills and seniority, location, and direct rivals. This meant that if you lived in San Francisco, you would compete against other people in the area, or that if you were Coca‐Cola, you'd compete against Pepsi, Ford versus Toyota, Boeing versus Airbus, or McDonald's versus Burger King. Today, with the exception of certain specialized skills and roles, everyone is competing with everyone. Coca‐Cola is competing against Toyota and McDonald's is competing against Airbus. Not only that but organizations are also competing on a global scale (read globalization) in a world where many perceive a skills shortage in an environment that is seeing traditional employment and business models change. This competition also extends to the gig economy, where smart and talented individuals might decide to drive for Uber or join an online freelance marketplace instead of working for you.

Psychology (and Sociology)

Employee experience is very much a psychological and sociological pursuit as many of the concepts around team building, motivation, performance, and success are influenced by studies that psychologists and sociologists have been conducting for decades (there are several referenced in this book). Any business book that you pick up today is bound to have several mentions of this. Organizations are now taking these pursuits more seriously as they try to truly create environments where people want to show up to work. This is no longer just a challenge that an organization can overcome with perks, higher pay, or gimmicks. Instead the business world is turning to the social scientists to really help them understand why and how people tick. It should come as no surprise that according to the U.S. Bureau of Labor Statistics, industrial organizational psychology is one of the fastest growing professions. These scientists are influencing how we hire and recruit people, design our office spaces, lead and manage, and even build and run our HR departments. Organizations such as Johnson & Johnson work with teams of psychologists for these exact purposes. This too speaks to the trend toward focusing on longer‐term organizational design instead of shorter‐term engagement programs.

Business Turbulence

According to Mark J. Perry of the American Enterprise Institute, a public policy think tank, almost 90 percent of the Fortune 500 have disappeared since the original list was created in 1955.⁷ In the past to really disrupt a large global company, you had to be a large global company. Not only that but also these organizations usually had a sense of where their threats were coming from. Today competition can come from a door‐to‐door fax salesperson (Spanx), a college dropout (Facebook), a former customer (Netflix), or someone who just raises a ton of money (Uber and Airbnb). The point is that in a world that appears to be getting smaller, at a time when change is getting faster, your competition can come from anywhere, and you'll never see it until it's in your face. In this environment organizations are struggling to hire the best talent that will help them see potential threats and uncover new opportunities. By focusing on employee experience many companies are hoping to be able to reverse that trend.

Growing Fast but Not Dominating

The first thing we need to understand is that although the online gig economy is growing, it is by no means going to dominate the workforce, not even close. The vast majority of us will continue to be full‐time employees the way we are today. It's true our workforce will be more dynamic and fluid, but employment as we know it won't be going anywhere.

Ted Egan is the chief economist for the Office of the Controller in the City and County of San Francisco. Recently he released a report called The Gig Economy in San Francisco: Prevalence, Growth, and Implications. In it he cited the JPMorgan Chase Institute, which found that as of September 2015 in the United States, the “percentage of adults who earned income from online platforms” (such as Uber, Upwork, Airbnb, and the like) in the past year was just over 3 percent, and this isn't even people who make a full‐time living from freelancing (that number is undoubtedly much smaller). Even in San Francisco, the supposed home for innovation and technology, wage employment has still been growing faster than self‐employment.⁹

In a 2016 article by Emily Green for SFGate called “Gig Work Isn't Changing Job Landscape, SF Economist Finds,” Robert Habans, a research associate at the University of California, Los Angeles, Institute for Research on Labor and Employment, summed up this fascination with the gig economy (again specifically looking at online intermediaries) wonderfully. He said, “It's kind of hard to reconcile that [findings from Egan's report] with how intensely everybody is talking about the gig economy, especially in a place like San Francisco. Most recent studies have failed to demonstrate a wholesale shift toward the gig economy, including this one.” In that same article Lawrence Mishel, from the Economic Policy Institute (and someone whom I had the privilege of discussing this at length with), said, “Digital platform work is just a small part of a broader set of employment practices.”¹⁰

Another fascinating paper by Seth D. Harris, the former U.S. secretary of labor and now professor at Cornell University, and Alan B. Krueger, an economist at Princeton University and former chairman on the White House Council of Economic Advisers, called A Proposal for Modernizing Labor Laws for Twenty‐First‐Century Work: The “Independent Worker found that “about 600,000 workers, or 0.4 percent of total U.S. employment, work with an online intermediary in the gig economy,” such as Uber or TaskRabbit.¹¹

Lawrence F. Katz, a professor of economics at Harvard, and Alan B. Krueger, published a fantastic presentation called “The Rise of Alternative Work Arrangements & the ‘Gig’ Economy.” The term they used to refer to online intermediaries is the online gig economy, which is what I have used here.

Although they have found the online gig economy to be quite tiny, they also found that it is growing remarkably quickly. In fact they cited Diana Farrell and Fiona Greig's 2016 finding that there was a 10× increase in the percentage of adults participating in the online gig economy each month and a 47× increase in the cumulative percentage of adults who have ever participated in the online gig economy. These are truly remarkable numbers. Another interesting but perhaps not surprising finding from the presentation is that Uber could represent half to two‐thirds of all online gig economy work. If you were to remove Uber from the equation, the online gig economy would be almost nonexistent.

However, if we look at the broader category of alternative work arrangements, we appear to see a very different story, one of much larger growth and impact. According to same presentation by Katz and Krueger, “All net U.S. employment growth since 2005 appears to be in alternative work arrangements.” This category has grown from 10.1 percent of all employment in February 2005 to an estimate of 15.8 percent at the end of 2015, or around 24 million people, based on Katz and Krueger's analysis of their 2015 survey Bureau of Labor Statistics data.¹²

Another piece of evidence I'll mention here is a great article published by Josh Zumbrun and Anna Louie Sussman in the Wall Street Journal called “Proof of a ‘Gig Economy’ Revolution Is Hard to Find.” According to the article, “Official government data shows around 95% of those who report having jobs are accounted for on the formal payroll of U.S. employers, little changed from a decade ago.” The article continues, “But the share of people who hold multiple jobs is also in decline—only 4.8% of workers do, down from 5.5% in 2005 and 6.3% in 1995.”¹³

These are a few of the many studies that have been done that show that the gig economy as we know it (looking at online intermediaries) is tiny (but growing). The studies I mention here have been conducted with academic rigor and are among the best efforts I have seen undertaken to quantify the true size of the gig economy. I want to stress the importance here of the academic rigor because there are plenty of other studies that have the size of the gig economy exponentially larger. These studies are oftentimes done by organizations that have a vested interest in inflating numbers and they do so by asking questions guaranteed to do so. For example they might ask if in the past 12 months you have done some form of work for money, which falls outside the realm of a traditional job, if you answer “yes” then oftentimes you are labeled as a freelancer. There are all sorts of things that I might do once a year like go sky diving, scuba diving, try a new food, and the like. But I don't tell people I'm a sky or scuba diver!

The Effect on Employee Tenure

Another popular theory that has been circulating is that employee tenure is in rapid decline and that in the near future we will all be portfolio employees where instead of working for a single employer, we will work for many employers at the same time. As someone who has made a living based on portfolio model [I work with over 40 companies a year], I'd be happy to see this become reality, but again, the data doesn't seem to support this direction.

According to the U.S. Census Bureau data Craig Copeland cited, “Data show that the overall median tenure of workers—the midpoint of wage and salary workers' length of employment in their current jobs—was slightly higher in 2014, at 5.5 years, compared with 5.0 years in 1983.”¹⁴ Granted the report is three years old, but it's the most current one as of this writing. I find this quite interesting because from all the executives whom I speak with, there is a consensus that employee tenure is not what it used to be and is in fact shrinking. It's hard to look at national averages and then apply those averages to specific companies. As you can imagine if you are in a hot labor market, such as San Francisco or New York, the tenure might be different than if you're in a part of the country like Wyoming or Minnesota. The industry also has a dramatic impact. Those in the technology industry won't have the same tenure as those in the construction industry. Although the data shows that tenure seems to be growing, many of the executives I speak with would disagree and dispute these numbers as they relate to their respective organizations.

This isn't just an American thing either. According to the Chartered Institute of Personnel and Development in the United Kingdom, which published a report called “Megatrends: The Trends Shaping Work and Working Lives”:

While self‐employment has increased in the last 30 years, some four‐fifths of people working in the UK are still permanent employees. In addition, the average period of time people spend with an employer did not shift greatly between the mid‐1970s and the mid‐2000s, albeit with some changes within the overall average. Furthermore, our evidence suggests that job turnover in the UK has been falling over the past decade—meaning that fewer people change employers each year.¹⁵

Are all of these reports perfect and all the numbers 100 percent accurate? Absolutely not. It's hard for anyone to provide accurate numbers around how large the alternate work category is, especially the online gig economy portion of that. That's because the U.S. government stopped collecting any data on the contingent workforce many years ago. However, early in 2016 Tom Perez, the U.S. secretary of labor, announced that the government will once again start tracking this data as a part of the 2017 population survey. This is very exciting because we will finally get some accurate numbers around how big this space really is.

Does this mean we don't need to pay attention to the gig economy or alternative work arrangements? Of course not. Instead of just looking at total numbers today, it's also helpful for us to look at where things might be going. The numbers can sometimes appear to be conflicting, but based on all the research and data that exist, it's safe to say that today the gig economy as it pertains to online platforms is a very tiny fraction of the workforce. Alternative work arrangements in general (including the gig economy) are growing and adoption rates are staggeringly high. However, today many people are using these platforms as ways to augment existing work arrangements and income. This forces us to ask a broader economical question, “Why is it that so many people feel the need to augment their existing incomes, and if we paid them more, would they continue to do so?”

Data also shows that employee tenure isn't shrinking as rapidly as previously thought. It may actually be increasing but slightly. It's important to keep in mind that this is simply an average. Although I have personally heard of many accounts of decreasing employee tenure from various executives at global organizations, they don't represent the average. This is yet another reason why people analytics has to be leveraged so that each organization can understand its own truths. As Wayne Gretzky famously said, “I skate to where the puck is going to be, not where it has been.” While we are still in the relatively early stages of alternative work and the gig economy, organizations should absolutely stay aware of the changes that are happening in this space.

This should be enough information to get you to think again when you hear someone talking about the end of employment as we know it. This should also help you understand why employee experience is so crucial, because full‐time employment isn't going away in the near future. So the long answer to “Does focusing on employee experience even make sense in a world that is supposedly going to be dominated by freelancers and short‐term employees?” is a resounding yes.

People Analytics in Action

Anshul Sheopuri is the director of the people analytics team at IBM, which now comprises over 70 employees and started around 2010, so these guys have been doing this for seven years already and are considered veterans in the people analytics game. Thanks to this team, IBM has been able to reduce employee churn by 2 percent by using data analytics to enable managers to deliver personalized coaching and guidance to employees. They also launched something called Blue Matching, which was designed to improve internal mobility inside of the company, as opposed to employees looking for opportunities outside of the company. Using analytics, employees get personalized job alerts based on their skills, performance, location, and area of expertise. To date over 40,000 employees have participated, and almost 500 job placements have been made. These are 500 potential employees who would have left IBM to go elsewhere.

Microsoft also saw an issue with internal mobility and because of people analytics was able to make policy changes that made it easier for employees to move around inside of the company instead of going elsewhere. Using various data points, such as compensation, tenure, and job performance, LinkedIn is able to create a type of heat map that helps managers better determine when an employee might be a potential flight risk, that is, he or she is getting ready or wants to leave the organization to look for other opportunities. This allows LinkedIn to intervene before that happens.

PwC wanted to test out the value of people analytics internally, so it asked Ranjan and his team (composed of 25 people analytics practitioners who focus internally at PwC) for a kind of test project. Like LinkedIn, PwC wanted to see if they could predict which employees would leave the company at around the 12‐month mark. Sure enough right around that time, the company started to notice that the people Ranjan and his team identified as going to leave actually started leaving. PwC also had a big assumption around recruiting from Ivy League schools. It believed that employees who were recruited from the top‐tier universities would perform better than everyone else. Thanks to people analytics, this was proved false. In fact employees who were recruited from non–Ivy League schools performed better than those who were. This allowed PwC to redistribute its recruiting funds and focus on different universities.

Ashley Goodall is the senior vice president of leadership and team intelligence at Cisco, and when I spoke with him he made a great point that too many organizations get stuck using people analytics to compute averages instead of focusing on what he believes to be far more important, excellence. In other words it's far more useful to understand something such as what the best leaders do and how the best teams work instead of how leaders and teams work on average. This concept of averages is what many organizations around the world then use to assign people an annual performance ranking, which Cisco has since gotten rid of. Cisco actually also got rid of its annual employee engagement survey as well. By the time it would launch the survey and then analyze it, slice and dice it by function, share it, develop a plan around it, and actually implement it, at least five months would go by. At that point the managers would respond to the information and say something like “Great, thanks for the plan but unfortunately four people are no longer on the team, we have shifted gears to focus on a new project, and half the team now works from home.” The problem with most people analytics efforts is that they provide data that is too broad, to people who can't do anything with it, at a period when no action can be taken. To solve this problem Cisco has shifted its approach to focus on experience and engagement at the team level. I should also point out that at Cisco many employees are a part of more than one team, working across functions and regions. In fact, when Ashley and his team were doing their research, they found that over 25 percent of the teams at Cisco were unaccounted for, meaning they didn't know these teams even existed because they weren't on the organizational chart!

Today, any team leader at Cisco can run an eight‐question pulse survey anytime he or she wants to get an idea of what's going on in the team. These responses are then analyzed and reported back in a matter of two to six days instead of six months. Then, the analysis is customized based on what the leader's strengths are and provides strategies around how to improve. From these eight questions Cisco can look at team information and organizational information (by aggregating individual team–based information). Ashley admitted that Cisco doesn't have all the answers, but they are learning and adapting as they go, always with the aim of empowering teams to become better.

Organizations must do their own internal research to find out their own truth. What I mean by that is it's easy for us to read research reports and studies from analyst and consulting firms and then assume that what we read applies to us. If a study says millennials are job‐hopping, then it means our millennials are job hoppers. If a study says diversity is an issue, then diversity must be an issue for us. If a research report says engagement is at an all‐time low, then our engagement must be at an all‐time low. None of these conclusions make sense. Although looking at external research can provide some broader context around certain things, the information should all be taken with a grain of salt. If you truly want answers to questions and if you truly want to know what the research says, then conduct your own inside of your organization. That's the only way to make business decisions, especially those that pertain to your people.

The Future of People Analytics

According to Ben Waber, the founder and CEO of Humanyze, this is all just the tip of the iceberg. I first met Ben in Madrid, where we were both speaking at a conference. Ben got his PhD at Massachusetts Institute of Technology in the Human Dynamics group and has studied behavioral analytics for many years. His company creates badges (just like employee ID badges) that employees wear at work. Except these badges are different. They are equipped with a variety of sensors, such as radio‐frequency ID that allow the badges to act like true ID badges, Bluetooth that measures someone's location in an office, infrared that can tell who you are facing, and a microphone that measures not what you say, but how you say it and how much time you spend speaking. These are things that actually measure human behavior, which according to Ben is something that most organizations don't measure.

This type of data can be used to help organizations understand things such as whether marketing is talking to engineering, whether the manager of a team actually spends time with his or her people, what the top‐performing employees in certain roles do differently, and how the most successful salespeople speak with their customers. Although organizations oftentimes do A/B testing for customer‐facing initiatives, this type of approach is rarely done inside of organizations simply because the behavioral data doesn't exist, but eventually it will. This will allow organizations to optimize and improve everything from how teams are structured to how compensation packages are created. Imagine being able to A/B test how work gets done regularly. Ben acknowledges that survey data is still useful and important to have, but it paints only a part of the picture. In the next decade or so, only a handful of companies will get to this level of behavior analytics.

In most organizations I have observed, the people analytics function sits in HR or sometimes it's a separate function. This makes perfect sense because HR typically deals with people. The challenge today is that many HR teams don't have this capability because it's a new skill set. HR has primarily always been about dealing with people and their interactions, legal, hiring, and firing versus actually analyzing people from a data science perspective. However, as this area becomes more advanced, it is quite possible that it will grow into its own department that reports directly to the CEO.

There is, of course, a dark side to people analytics because data can be used to make decisions that either positively affect people or negatively affect people. For example, people analytics can be used for calculating mass layoffs or for determining ways to manipulate people. This is a delicate balance that organizations have to be careful of, not to mention the potential creepy factor of employees having data collected about their every move and action! Not only that but people analytics models are designed by people which means they will be inherently flawed. In her wonderful book, Weapons of Math Destruction, Cathy O'Neil tells the story of a middle‐school teacher named Sarah Wysocki who was let go from a job with the Washington DC school district because an algorithm decided that she was doing a poor job. The school district was determined to improve underperforming schools by eliminating bad teachers. Although she got rave reviews from the principal and from parents, somehow she was classified as being in the bottom 2% of teachers. It turns out the elementary school where Susan's students came from was one of several schools under investigation for a high likelihood of cheating on standardized tests by teachers who were erasing the wrong answers and filling in the correct ones. They did this to help preserve their own jobs. This meant that when Susan's students took standardized tests where no cheating was involved, their scores dropped considerably, thus making it look like they weren't getting the education they should have been. Naturally the teacher was to blame. In this situation the algorithm would have no way of picking this up and as a result Susan and over 200 other teachers were fired. This story illustrates just how important it is for us to not place all of our decision‐making eggs in the people analytics basket.

Today we are still at the very early stages of what's possible. Perhaps the biggest challenge for companies today is organizing, cleaning, aggregating, and standardizing data, a project that can easily take years, depending on the size of the organization.

With technology advances and the integration of AI, you will one day be able to use voice commands to ask a smart assistant (think Siri, Cortana, Watson, Viv, or Echo) things like:

• “What's the employee turnover?”
• “Who are the top three employees on my team at risk for leaving the organization?”
• “How many contingent workers are we using, and how much are we paying them each year?”
• “What are the top skills and weaknesses on my team?”
• “Which teams are the highest performing inside of our organization?”
• “I need to build a new marketing team in California composed of five individuals; which employees should I consider?”

People analytics is absolutely growing into a core business capability that every organization must invest in heavily and it's the foundation of employee experience