In a recent overview of gamification technologies at Employee Benefit News, John Soat looked at the growing number of ways in which organizations are gamifying HR processes. Soat highlighted three areas in which gamification is most promising: pre-hire assessments for recruiting, training programs for current employees, and encouraging participation in wellbeing initiatives and other benefits programs. Game-like tools are popular and effective because they are fun and engaging, so employees are more likely to use them voluntarily, even outside working hours. This impact on engagement, Soat hears from vendors, is part of the often intangible ROI their clients see from gamification.
This is a trend we’ve been following both here at Talent Daily and in our research at CEB, now Gartner, for several years now. Looking at how various organizations have gamified their processes, we’ve discovered some surprising use cases for this approach and developed a robust understanding of what makes gamification initiatives most likely to succeed.
In the training space, it’s interesting to note that companies aren’t just using gamification for entry level or technical skills. In 2014, we profiled GE’s Experienced Leaders Challenge: a week-long, immersive development session for experienced GE leaders designed to help them develop a leadership mindset aligned to today’s inherently unpredictable business environment. A key part of the program is a simulation that lets leaders practice navigating common challenges and observe the unexpected consequences of their decisions or actions. (CEB Corporate Leadership Council members can check out the full case study here.)
The explosion of technology available to people outside the workplace is forcing employers to keep up with their employees’ digital expectations within it. In our 2018 Digital Employee Experience Survey, CEB, now Gartner, found that 74 percent of employees say they expect more access to state-of-the-art technology at work today than three years ago. However, these technologies can take different forms: Motorola’s modular phones, for instance, offer a multitude of features ranging from camera styles to gaming platforms, while the Light Phone markets itself as a “dumb phone” with features limited to calling and texting.
Both of these phones are at the leading edge of mobile technology, but they offer their users dramatically different experiences and are marketed to different sets of consumers with different preferences. HR leaders face a similar challenge in choosing from the growing range of options available to them how to most effectively deliver technology to their own consumers: employees.
When deploying new digital technologies, most HR functions focus on making as many digital solutions available to employees as possible. Many accomplish this by putting their HR resources into an app, providing “on-demand access” where all information is available anytime and anywhere. Just like we as consumers are used to having access to most types of information on demand outside of work, replicating that experience internally for employees has a certain appeal for organizations.
However, the results of an on-demand approach don’t live up to employers’ expectations: Our latest research on digitalization has found that deploying HR solutions through on-demand access only generates a 4 percent impact on employee performance, at most. This is better than no promotion of digital tools at all, but despite its intuitive appeal, in practice the on-demand approach overwhelms employees, confronting them with too much information and too many choices about how to use HR solutions.
Fortunately, there’s a better way.
In today’s digital organizations, HR departments are increasingly using algorithms to aid in their decision-making, by predicting who is a retention risk, who is ready for a promotion, and whom to hire. For the employees and candidates subjected to these decisions, these are important, even life-changing, events, and so we would would expect the people making them to be closely supervised and held to a set of known performance criteria. Does anyone supervise the algorithms in the same way?
Algorithms don’t monitor themselves. Replacing a portion of your recruiting team with AI doesn’t obviate the need to manage the performance of that AI in the same way you would have managed the performance of the recruiter. To ensure that the decisions of an AI-enhanced HR function are fair, accurate, and right for the business, organizations must establish performance criteria for algorithms and a process to review them periodically.
A recent special report in The Economist illustrates the significant extent to which AI is already changing the way HR works. The report covers eight major companies that are now using algorithms in human resource management, which they either developed internally or bought from a growing field of vendors for use cases including recruiting, internal mobility, retention risk, and pay equity. These practices are increasingly mainstream; 2018 may mark the year of transition between “early adopters” and “early majority” in the life cycle of this technology.
At this point in time, it is essential that leaders ask themselves whether their organizations have management practices in place to supervise the decisions of these algorithms. The Economist concludes their piece with a reminder about transparency, supervision, and bias, noting that companies “will need to ensure that algorithms are being constantly monitored,” particularly when it comes to the prevention of bias.
A recent report from the Organization for Economic Cooperation and Development finds that the number of jobs at risk of displacement due to automation in the coming years is probably smaller than previous forecasts have estimated. Nonetheless, the tens of millions of workers in developed countries are still at risk of having their jobs replaced or radically altered by AI and robotics. The Verge’s James Vincent summarizes the report’s findings:
The researchers found that only 14 percent of jobs in OECD countries … are “highly automatable,” meaning their probability of automation is 70 percent or higher. This forecast … is still significant, equating to around 66 million job losses.
In America alone, for example, the report suggests that 13 million jobs will be destroyed because of automation. “As job losses are unlikely to be distributed equally across the country, this would amount to several times the disruption in local economies caused by the 1950s decline of the car industry in Detroit where changes in technology and increased automation, among other factors, caused massive job losses,” the researchers write.
The analysis from the OECD, an inter-governmental organization representing the world’s 35 richest countries, is considerably less disconcerting than previous studies that have calculated the risk of automation at anywhere from 30 percent to fully half of all the work currently being performed globally. One difference between this study and previous ones, Vincent explains, is that it pays greater attention to details like whether a job can be fully or only partly automated and the variations among jobs that may have the same title but whose work differs substantially:
In a recent Harvard Business Review article, Thomas H. Davenport and George Westerman, researchers with the MIT Initiative on the Digital Economy, consider several recent cases in which high-profile companies like GE, Ford, and Procter & Gamble made massive investments in digital transformations that ultimately failed to achieve their goals. “What can we learn from these examples of digital dreams deferred?” they ask. “How did these smart, experienced leaders make decisions that don’t look so smart in hindsight?”
The issue, the authors posit, is fundamental to the adoption of transformative business technologies. Very similar high-profile change failures happened with the rise of e-commerce and big data, they note. There’s something about digitalization that leads businesses to slip up in specific ways:
Several key lessons emerge when heavy commitments to digital capability development meet basic financial performance problems. A clear one is that there are many factors, such as the economy or the desirability of your products, that can affect a company’s success as much or more than its digital capabilities. Therefore, no managers should view digital — or any other major technological innovation — as their sure salvation.
Second, digital is not just a thing that you can you can buy and plug into the organization. It is multi-faceted and diffuse, and doesn’t just involve technology. Digital transformation is an ongoing process of changing the way you do business. It requires foundational investments in skills, projects, infrastructure, and, often, in cleaning up IT systems. It requires mixing people, machines, and business processes, with all of the messiness that entails. It also requires continuous monitoring and intervention, from the top, to ensure that both digital leaders and non-digital leaders are making good decisions about their transformation efforts.
From our research at CEB, now Gartner, we know that enterprise change is hard. Most change efforts fail either partly or completely, and in today’s business environment, change is happening faster than ever before. The CEB Corporate Leadership Council’s ongoing research on Creating a Talent Strategy for the Digital Age also points to the unique challenges Davenport and Westerman identify with digital transformations.
SHRM’s Roy Maurer recently highlighted a survey from KPMG showing that corporate leaders around the world remain distrustful toward their organizations’ data and analytics when it comes to using these tools to make business decisions:
In the survey of 2,190 senior executives from Australia, Brazil, China, France, Germany, India, South Africa, the U.K. and the U.S., just 35 percent said they have a high level of trust in their organization’s use of data and analytics. Another 40 percent said they had reservations about relying on the data and analytics they produce, and 25 percent admitted they have either limited trust or active distrust in their data and analytics. Nearly all respondents (92 percent) worry about the impact flawed data could have on their company’s business and reputation.
“Executives and managers are being asked to make major decisions based on the output of an algorithm that they didn’t create and don’t always fully understand,” said Thomas Erwin, global head of KPMG International’s Lighthouse, the firm’s center of excellence for data, analytics and intelligent automation. “As a decision-maker, you really need to have confidence that the insights you are getting are reliable and accurate, but many of these executives can’t even be sure if their models are of sufficient quality to be trusted. It’s an uncomfortable situation for any decision-maker to be in.”
One barrier to the credibility of analytics for business leaders is the prevalence of incomplete data; another is that the metrics against which organizations are measuring are often ill-defined. HR metrics like source of hire and quality of hire are particularly hard to measure accurately, Kevin Wheeler, founder and president of the Future of Talent Institute, tells Maurer, and there is significant disagreement on how best to define them.
The second annual Future Workforce Report from the freelance hiring platform Upwork finds that even though most US managers expect more of their team members to work remotely in the coming years, most also say their organization lacks a specific policy on remote work:
Sixty-four percent of hiring managers feel that their company has the resources and processes in place to support a remote workforce, yet the majority (57 percent) lack a remote work policy. …
Over half (55%) of hiring managers agree that remote work has become more commonplace as compared to three years ago. Five times as many hiring managers expect more of their team to work remotely in the next ten years than expect less. In the next ten years, hiring managers predict that 38 percent of their full-time, permanent employees will work predominantly remotely.
Among those companies that do have remote work policies, many respondents indicated that these policies are evolving to become more flexible and inclusive, which is helping them attract talent in a tight labor market:
Nearly half (45%) of hiring managers said their company’s work-from-home policy has changed in the past five years, with 60 percent saying it has become more lenient and inclusive. This increased inclusivity is making it easier for companies to find the talent they need. Over half (52%) of hiring managers that work at companies with work-from-home policies believe hiring has become easier in the past year.