Impact of Digital Technology on the Labor Market

Digital media has forever changed how employers look for workers and how workers look for new opportunities. The notion of either being happy in your job or actively seeking a job has been changed by digital environments. For many in-demand workers, there is an ongoing stream of job opportunities from multiple digital channels such as the web, mobile, and social platforms that come in front of them all the time. Additionally, workers are more connected with one another and have an easier time understanding the real story of what it’s like to work in a particular company and what’s valued, as well as some of the negatives about a company.

As a result, the Internet and other digital environments have changed the workforce equation and revolutionized the overall talent sourcing and retention process, moving from a print-based to a digital-based effort. Digital technology has also enhanced the word-of-mouth channels through social networks and social hiring channels.

In addition, your employees see an ever-increasing number of recruitment messages from competitors from all directions. Media volume, including recruitment advertising and direct brand building that your employees see and that help form an impression of an employer, has been on the rise for quite some time. In the United States, companies send over 90 billion pieces of direct mail each year trying to influence the behavior of customers.⁷ Also, the Radicati Group estimates that nearly 90 trillion e-mails are sent each year,⁸ certainly a large percentage of which are helping your employees form an impression about a prospective employer organization. According to Media Dynamics, a media research group, the average American is exposed to a minimum combined total of 560 advertisements each day from radio, print, and television.⁹

At the same time, mobile recruitment usage continues to increase dramatically on a global basis, as does the use of social media and other online content such as blogs or tweets. There are roughly 6.5 billion mobile phone subscriptions worldwide, with some users having service on more than one device.¹⁰ Also, according to the Direct Marketing Association, 36 percent of workers now follow brands on social media platforms.¹¹

This new media is taking a lot of the friction out of learning about work opportunities and about choosing an employer. The good news from an analytics perspective is that, with the increase of new media and the multitude of ways to interact online, comes the increase of new data into the recruiting organization and the building blocks of People Analytics. For example, Internet sourcing created an explosion of digital talent data and metrics, and technology has enabled this information to be captured, stored, processed, analyzed, and managed. Every interaction that someone, whether a prospective employee or a current employee, has with your employer brand in an electronic medium such as an Internet search engine, a website, a social media platform, an electronic coupon provider, a blog post, or over a mobile device generates a data trail.

Other interaction points are also growing and generating massive amounts of data in their wake that can potentially be used for People Analytics of your workforce. For example, there are unknown quantities of digital location tracking sensors in shipping crates, electric meters, automobiles, industrial equipment, and various other devices used by employees at many organizations. Additionally, GPS, WiFi, and Bluetooth position tracking by mobile devices is widespread and generates massive streams of location data that companies are beginning to harness in their quest to use analytics to drive workforce optimization.

Given these issues influenced by the rise of digital environments, the world of multichannel talent acquisition and retention requires the effective use of People Analytics to untangle the complex patterns of employer brand and talent perception that arise from being exposed to so many employers from so many channels.

Employee Tenure and Loyalty Are Decreasing

Another trend leading to the greater importance of People Analytics is that worker loyalty is disappearing and workers are not staying with companies for as long as they did in the past. Employees are becoming more fickle, and loyalty for employers is rarer than ever before—so employee turnover is often a substantial business cost. As a result, more and more employees are becoming less engaged, and are planning to look for new work. The decline in employee loyalty is also seen to be affecting the quality of service provided to customers. According to a 2015 study by the American Management Association, employee loyalty has declined sharply over the past five years at North American companies and is thought to harm organizations by causing low morale, high turnover, disengagement, growing distrust, and lack of team spirit.¹²

In recent times, this issue has been laid at the feet of members of the millennial generation, who have a strong reputation for switching jobs frequently. However, the data tell a more complicated story. Certainly, millennials are part of the equation, but job tenure has been declining for at least 50 years, with both older workers and younger workers staying with companies for shorter and shorter periods of time.

For example, the Federal Reserve Bank of Atlanta examined the median job tenure by age group and generation and found that job tenure decline was across the board, not just in millennials. As seen in Figure 1.1, when looking at 20- to 30-year-olds, we can see that the median job tenure was four years among those born in 1953 (baby boomers) when they were between 20 and 30 years old. However, for 20- to 30-year-olds born in 1993 (millennials), median job tenure is only one year.¹³ Similar—and some even more dramatic—declines occur across cohorts within each age group. Interestingly, there is also a five-year decline in median job tenure between 41- to 50-year-old “Depression babies” (born starting in 1933) and 41- to 50-year-old Gen Xers (born starting in 1973).

At the same time that worker tenure is decreasing across the board, employee loyalty is decreasing as well. Wharton School management professor Adam Cobb sees the declining loyalty as a symptom of an evolving relationship between organization and employee. Cobb sees employee behavior as being influenced by the major organizational restructuring that began 30 years ago. “Firms have always laid off workers, but in the 1980s, you started to see healthy firms laying off workers, mainly for shareholder value. Firms would say, ‘We are doing this in the long-term interest of our shareholders,’” Cobb noted. “You would also see cuts in employee benefits—401(k)s instead of defined benefit pensions, and health care costs being pushed on to employees. The trend was toward having the risks be borne by workers instead of firms. If I’m an employee, that’s a signal to me that I’m not going to let firms control my career.”¹⁴

The lower levels of employee loyalty and the declining job tenure are both creating a more urgent need for analytics to help understand which employees are engaged and which employees are at risk, as well as how to spot the signs early enough before it’s too late. Given all of this, it’s extremely critical for businesses to understand employee issues such as what drives attraction to you as an employer, current employee sentiment, and factors associated with a highly engaged and productive workforce. Understanding those issues must be grounded in solid analytics. Doing this without systematic analytics and voice-of-the-employee input is almost impossible.

The Influence of Millennials

Millennials have entered the workforce en masse, and many have different attitudes regarding the employer–employee relationship, what work means, and how they expect to be treated in the workplace. There’s a stereotype that millennials are entitled job hoppers; however, the data tell a different story. Younger workers are actually staying in their jobs longer than previous generations did. In the late 1980s, about 50 percent of 20- to 25-year-olds changed jobs each year, but that dropped to 35 percent after the recent recession, according to an analysis by the Washington Post.¹⁵ It’s not clear if millennials are holding on to those jobs by choice or if they are struggling to find better opportunities.

Regardless, there are some key differences between millennials and other workforce generations that make the importance of People Analytics more evident. For example, the millennial generation expects to be able to give and receive feedback openly and frequently. They expect this at all levels of the organization as well. So, it’s not unheard-of for a millennial worker to feel empowered to meet with the CEO and tell her what he thinks about recent happenings in the company. This also influences their expectations for what a manager relationship should look like.

Additionally, millennials have a stronger desire for their job or career to have personal meaning beyond the job task they are tackling. For example, is their company socially responsible, helping others in the community, helping to influence the industry or world, or achieving something great? In other words, buying into the vision and mission of their employer is more critical for this generation compared to previous generations.

As a result, People Analytics is critical to monitor and understand the early at-risk signs for this generation. Concepts like a traditional once-a-year check-in or annual performance review are not going to be enough to make sure you’re staying close to and mitigating the turnover risk of your millennial workers.

Globalization of the Workforce Economy

Another driver of the need for People Analytics is the globalization of the world economy. The labor market and competition for talent can no longer be viewed through a domestic lens. There are complex labor market dynamics at play that only analytics can help untangle. For example, Figure 1.2, from Aon Hewitt’s annual report 2015 Trends in Global Employee Engagement, shows the world’s largest economies and the world’s largest labor pools. Together these countries make up more than 80 percent of the global gross domestic product (GDP) and available labor. These countries also have very different dynamics in economic and population growth/stagnation and wide ranges of average employee engagement levels (from 38 percent in Japan to 78 percent in Mexico). China and the United States are the dominant markets from a GDP and labor perspective, with the U.S. GDP double that of China. Yet China, where 40 percent of the world’s workforce resides with almost 1.3 billion available workers, has a labor pool nearly five times that of the United States, whereas India has a very large labor pool but its economy is one-tenth the size of the United States’ and China’s economies combined.¹⁶

These data all point to the level of complexity leaders face in driving growth through talent strategies across global markets, all in various stages of growth and maturity. However, according to Aon Hewitt, there are two very compelling facts about these data. First, there is zero correlation between the size of the economy and growth. However, there is a significantly positive correlation (0.52) between available labor and economic growth. In other words, where there is available talent, there is growth.

Employers Must Always Be Engaging Talent

Another force lending rise to People Analytics is that in the current climate, employers must now always be engaging their employees—current, future, and past. Nowadays, an employer must continually attract, acquire, and advance talent just as brands attract, acquire, and gain loyalty with customers over time. The reflection of this new reality can be seen in the Engagement Cycle framework developed by one of the authors of this book and published previously in Finding Keepers.¹⁷

The Engagement Cycle is a long-term practice combining employer branding, relationship management, and communication. The Engagement Cycle creates strong bonds between employers and potential candidates before, during, and after the brief period we call “recruiting.” Its practices ensure that when the economy strengthens—and talent once again becomes scarce—an employer has built a strong bench of talented individuals who are interested, open to discussion, and even grateful for the attention. The Engagement Cycle concept also helps employers take advantage of candidate psychology during a slowdown to attract top talent for the long term.

As companies move from the hiring-as-transaction view to the marketing view, the employer and the candidate follow a clear three-phase cycle in the course of their working relationship. The three phases of the Engagement Cycle determine the level and quality of engagement between employee and employer. Analytics at every phase of the cycle are critical. The three phases are:

1. Attract. The Attract phase is a long-term dance between you and the candidate. It includes every activity meant to position the organization as a potential employer in the mind of a candidate. You project a carefully crafted, authentic image as an employer; the candidate becomes aware of your organization’s specific attributes. Your employees spread your reputation as an employer; the candidate listens and assesses your company as a potential workplace. It’s a similar dance to the way consumers are drawn to brands in the marketplace.
2. Acquire. This phase involves all the interactions between you and candidates from the moment they reach out to you. You advertise a position and they apply. You treat their application a certain way, and they react. You find their resume and approach them, and they judge you by your image and your behavior. Your interview process is a series of interactions with different parts of your organization. Both candidate and employer set expectations throughout this process that will be critical in making a good hire and later in holding onto the best talent. The Acquire stage also includes the honeymoon period right after an employee starts working, in which expectations will be tested against reality. In terms of consumer branding, this is the purchase of a product and its aftermath: Does the product perform as advertised? Is the customer so satisfied that he or she would recommend the product?
3. Advance. Keep critical talent moving, not necessarily up, but growing in experience, responsibility, money, or other tangible and intangible ways. Advancing talent in your organization is a key to retaining good people and vital to your company’s ability to change as opportunity or necessity require. Retention is the “hold” part of hire and hold; in consumer branding terms, it’s the equivalent of customers’ becoming loyal to a brand and identifying with the brand’s attributes.

Increased Competition for Talent

Part of the increased need for People Analytics is the increased competition for talent. In order to be successful in the war for skilled workers, your company must monitor and stay one step ahead of your primary competition for talent—tracking, analyzing, and integrating everything you know about them into the talent acquisition processes of your own company. For example, do you know the strategies and tactics your competitors use to attract talent, how your employer brand and work environment is perceived compared to theirs, which of your talent segments are more likely to defect to the competition, or whether your talent acquisition costs are higher than your competitors’? Many companies rely, at most, on informal feedback on their competitors and do not have solid analytical systems in place to address these issues.

Given intense business competition, existing companies must continually monitor their employees’ behaviors and perceptions, remaining on guard for precursors to employee turnover. Companies are under great pressure to continually and rapidly reinvent themselves and how they offer value to employees and customers. Failing to accurately listen, track, and take action on employee attitudes often results in very high employee turnover costs compared to peer organizations. Take the case of Piper Windows, a UK-based company that started operating in 1980 as a manufacturer of windows for commercial and residential markets with projects ranging in value from £50,000 to £1.5 million. Piper’s customers included local government agencies, housing associations, schools, and hospitals, and its annual revenues were about £10.1 million. Although Piper was growing slightly faster than the market, its management believed that the company could gain a bigger market share by being more competitive and by fully using its current capacity. Piper was operating on a single site, split into two units, one for commercial and one for domestic business. The business was buying preformed extruded plastic, and then transforming it into the window/door units. It used two profiles of plastic from two suppliers, with the two units manufacturing one type each.

In 2000, the company was struggling with how to increase plant output while still maintaining quality. Management believed that the ongoing struggle to achieve greater growth was a result of poor productivity and quality control by frontline staff. The UK Department of Trade was enlisted for advice on improving factory output and quality. After some analysis, it was discovered that productivity and quality control were indeed very serious threats, but the cause of those issues was surprising to management. Despite leadership insistence that problems were due to poor use of equipment, bad layout, and quality issues, it was identified that the basic cause was due to the poor levels of employment and high staff turnover.¹⁸

Apparently, there were a number of deep-seated issues within the operation that were leading to high staff turnover. The company had consistently won a number of regional awards for training and training initiatives, but this was all initial training for new hires, and there was no ongoing training or staff development. It proved hard to convince leadership that turnover was a major threat to the business, as they were convinced that the answer was better performance through better use of their current operations. This may have been true in the long run, but would not be achievable unless leadership acknowledged that high turnover was a threat. Piper failed to do this, and in the long run it hurt the company. The company finally filed for bankruptcy in late 2013.¹⁹

HR Is under Pressure

Anyone who works in HR knows there’s pressure. The clock is ticking. Business leaders, HR leaders, and boards are recognizing the changing and growing critical business needs related to HR and talent— leadership, organizational change, and talent development are at the top of the list. The time for HR business as usual is over. The CFO is asking to understand the ROI, the CEO is asking for a labor force to carry out a vision, and employees are demanding more benefits—HR is hit from all sides.

At the same time, they’re shifting their role from the tactical “where’s my paycheck?” function toward being a strategic business partner. HR now has access to huge amounts of computer processing power that makes it possible to take vast quantities of information— so-called Big Data—about the organization and its employees, and analyze it using specialized workforce and predictive analytics tools. These tools interrogate the data and connect different bits in different ways that might never have been thought of before. So they reveal new things, offering insights into what has happened in the past, what is happening at present, and even what is likely to happen in the future.

However, HR is struggling under the pressure. The Sierra-Cedar HR Systems Survey, now in its 17th year, gathers information from organizations across the globe that track the adoption and deployment of HR analytics solutions, gathering data on process maturity as well as the type and amount of data that HR organizations are capturing. According to Sierra’s most recent study, only 9 percent of companies use predictive analytics or Big Data to analyze trends related to human capital.²⁰

Skills Gap in the Labor Market

Another trend giving rise to People Analytics is the global skills gap in the labor force. And it’s going to get worse before it gets better. There are currently millions of unemployed and underemployed workers in the United States as well as millions of job openings. However, many of those workers will remain unemployed and those positions will go unfilled.

In the United States, labor force participation remains historically low, and a jobless economic recovery seems the new normal. Increasingly, jobs are being automated, yet a shortage of skilled workers is looming worldwide, even in China, despite its huge labor force. Technology also makes it possible for employers to redesign and partition work, and to reassign routine tasks to lower-skilled employees. In health care, for example, chronic disease management can be assigned to nurse practitioners rather than to physicians.

These and other changes are part of the larger disruptive forces that are reshaping the global economy. In the labor market, some of these shifts are already evident—and the disruption they bring about will only get larger. As a result, People Analytics becomes a critical factor in sourcing, attracting, acquiring, and retaining the skills needed in your workforce.

Talent Is One of the Last Competitive Differentiators

Another phenomenon giving rise to the importance of talent analytics is the increasing value of talent to the bottom line, and the diminishing value of other assets to make a difference.

In the development of new economies, stand-by competitive differentiators have often faded. For example, capital forms much more freely than in the past, new products are quickly copied, location matters less as workplaces become decentralized, and distribution channel relationships fail to prevent competitors from entering through online channels. These structural changes don’t mean these things are no longer important, just that their relative importance is declining.

Talent creates the vast majority of value in the developed world’s companies, and those who calculate the intangible assets of organizations (e.g., know-how, patents, brand names, ideas, and processes) put the products of brainpower from employees at 80 percent of a company’s value.²¹

Globalization plays a part as businesses in more developed economies cede manufacturing and low-end services to emerging economies. Their survival depends on the products of high-end talent, whereas information-rich products and services, business innovation, sophisticated new technologies, better management, and more creative solutions drive the established economies.

This permanent change has increased the value of talent because talent is the last remaining factor that consistently delivers profits. Companies espouse innovation, but it’s talent that innovates. A large retailer revolutionizes supply-chain management and then discovers that midlevel store managers are the linchpins that determine whether all the efficiently delivered merchandise gets purchased by the consumer.

This, coupled with the shortage of critical skills in the labor market, means that more than ever, People Analytics is critical in order to give you the advantage over your competition in the talent war.

HR Evolves into Talent Management

Human capital or talent management (TM) is evolving in much the same way as the finance function grew into a decision science, separate from accounting, or the evolution of marketing as a decision science separate from sales. Executives who are focused on talent management must now work side by side with the CEO and other business leaders to identify ways that talent can be used to create new products and services and to inspire new strategies. People Analytics becomes a key enabler of this evolution, helping to understand worker sentiment, predict factors that lead to an engaged and productive workforce, as well as help uncover hidden opportunities for talent-related programs to contribute to the company’s bottom line. Figure 1.3 lists some of the ways that HR is evolving from a process-based department into a strategic partner.

Putting It into Practice

To illustrate some of the challenges to People Analytics success, let’s take the case of a company we spoke with as part of the background research for this book. Out of respect for the company we won’t name it; however, let’s just say that it is a fairly well-known media company. This media company expressed some analytical angst to us during our interview. The interviewees said they realized a few years ago that their unstructured data from employee engagement surveys was an untapped resource to help their people strategy as well as their business strategy. So they went searching for someone with the requisite degrees and experience who could lead the work with their data to help them unleash its potential. They searched for seven months (these data analysis people are in demand) and finally found someone with a statistics degree, computer science experience, great references, and a solid track record of helping well-known brands analyze their data. They hired him and put the existing four HR analysts already at the company under his management. They were very optimistic with their new key hire and set him immediately to work on analyzing data from long-tenured employees versus those new to the organization in order to understand how to better target new prospective talent so as to yield long-term employee engagement and a solid return on their recruiting dollar.

They said things started off well at first—the team was optimistic and energized with the new team member. However, problems gradually started to develop. First, the People Analytics team went away for weeks at a time with little data analysis completed, and then when something was delivered it was usually lots of raw data and a graph or two that was difficult for the business’s people to understand. Second, the new team occasionally provided statistics that were in conflict with those from other teams in the company or what had been common company wisdom in the past, setting off ill will between departments and spates of dueling data that often took weeks to untangle. Next, it seemed as though the analysts would come out with numbers that were different from the analysis they had provided just a few months earlier, which frustrated the business to no end.

The company attributed these challenges to the difficulty of doing People Analytics and tended to blame the analytics team for these problems. However, as a result of our interview, they gained an expanded view that it was very likely that the overall organizational dynamics within the company may have been the cause of their People Analytics difficulties.

First, we asked what company leadership sponsored the hiring and formation of this People Analytics team. It was explained to us that a long-tenured vice president of human resources commissioned this initiative, and everyone had great faith that she could make the best use of these analytical resources. When we followed up regarding whether the most senior corporate or functional leaders were also in favor of forming this team, we were told that they were not completely sure as nobody beyond the senior vice president to whom the human resources vice president reported was consulted. This illustrates the first internal challenge that People Analytics must overcome: weak executive sponsorship. Unless a senior driving leadership force within the organization is aware of, supports, and believes in the mission of the People Analytics discipline over the long term, then it will likely have difficulties thriving and eventually fail due to shifting corporate priorities, company politics, and lack of corporate accountability.

Second, we asked what process the company had undergone to make sure its corporate business objectives were in line with the objectives of this new analytics team. We uncovered that they didn’t really communicate corporate objectives to the new analytics lead or his team, as they thought the team just needed to analyze data, not worry about corporate priorities. This illustrates the second internal challenge that a People Analytics function must overcome: failure to communicate and align People Analytics priorities with corporate priorities.

Third, we noted that surely technology systems and resources were required to help the People Analytics team do their work, so we asked how the analytics team worked with the technology team that supported these analytics initiatives. For example, did the technology resources report into the new analytics team? Was there a direct line of accountability in some other way? We were told that they did not set up any formal arrangement, but relied on the new People Analytics manager to build a bridge and work across the departments. This illustrates the third internal challenge that the practice of People Analytics must overcome: weak alignment and accountability from the technology support function.

Next, we asked whether there was any data quality or governance function within the company to ensure that definitions were standardized and data were accurate. We were told no, that it was the analytics team’s responsibility to make sure that whatever data and analysis were distributed were accurate and reliable. This leads us to the fourth internal challenge: lack of formal data governance. It takes dedicated and diligent effort from business and technology to ensure that data being published from various systems are accurate and reliable, and this cannot be just a matter of an afterthought by a few analysts because they happen to be last in the chain of data distribution.

Then we asked how the new People Analytics team’s activities were rationalized against other People Analytics–related activities across the enterprise from departments such as finance, strategy, or international business units. We were told that they did not really communicate with one another formally and didn’t initially think it was necessary because those teams were working on different analytical tasks. This illustrates the fifth internal challenge: weak alignment of existing People Analytics resources within an organization. We explained that in order to reduce the likelihood of duplication of efforts and dueling data as well as to ensure that the company is leveraging the collective knowledge of the analytical resources most effectively, there must be some type of formal alignment across People Analytics teams throughout the company; whether that is a reporting relationship to a single manager or just a formal communication and management cadence depends on the corporate culture and is open for debate, as we have seen each work well under different circumstances.

There will be many internal challenges on the way. These are just some of the internal challenges a People Analytics function must rise to meet in order to become business-relevant, fast, insightful, and predictive; to have a bias toward action; and to become part of the corporate culture.

Given that economic pressures remain in many parts of the global economy, that the war for talent is more intense than ever, that employee loyalty is all but gone, and that new media and digital technologies are on the rise, it’s no surprise that the use of People Analytics is gaining new prominence. These are the challenges for the People Analytics discipline—the challenge to help organizations thrive and prosper. It’s clear that effective People Analytics is seen as a way to address these key talent challenges and that People Analytics holds great promise to help organizations understand what their employees want from them, how to acquire new ones, and what will lead to an engaged employee. However, most organizations we speak with are struggling to make sense of what this data can tell them or how they can use it. Therefore, we have designed this book to help businesses think about, organize, and make the most of the people-related analytical assets available to them.

We don’t claim this book will solve all of these issues for everyone. However, we know that the best practices, lessons learned, and assessment tools within will go a long way toward helping you to make sure your People Analytics is world-class. Throughout this book, we provide examples of companies that are doing it well, as well as some that are not.

This book is organized in such a way to help you build upon your knowledge as you read from chapter to chapter. We have also attempted to define and organize the chapters so they can stand on their own. For example, if you are primarily interested in learning about using People Analytics effectively for employee onboarding, you can jump to Chapter 7, Onboarding and Culture Fit. However, if you want to learn about how to successfully use People Analytics to leverage talent strategically to meet your business objectives, then we suggest you read the chapters in order and ask yourself the hard questions about whether your company is doing everything it can to leverage People Analytics.

Organizations are in an ongoing war—a war for talent. Everyone working in human capital knows it, business leaders know it, line managers know it, and the most talented employees know it. With some effort (increasingly less and less effort), talented employees can leave you forever. The time and money you spent training them, giving them experience and development opportunities, building key relationships within your organization—they’re all gone as soon as your talent walks out the door. So, leverage People Analytics to make sure your talent strategy adds to your organization’s bottom line, not just takes from it.