Not long ago, children in history class learned about only one Industrial Revolution, which happened in the nineteenth century when power from coal was harnessed for mass production. It can now be argued, however, that we are in the midst of another Industrial Revolution, the fourth. (The second may be said to have resulted from the creation of the electrical grid, and the third from mass communication.) In this fourth revolution, networked computing power has become so widespread that it is rapidly advancing technology in all areas simultaneously and may soon help create genetically edited human life and artificial intelligence (AI). The law lags behind these developments, leaving employers with uncertain safe harbor, but emerging workplace trends resulting from this latest revolution can provide some guidance.
As people and businesses use smart phones, home monitoring devices, and other computers constantly, they generate enormous amounts of data. This is the foundation of the Fourth Industrial Revolution. While managers may not yet be able to ask an AI assistant for conversational advice on any topic, Microsoft reports that, according to Gartner, a research and advisory company:
Industry analysts have predicted an explosion of experimentation, adoption and use of AI over the next few years. Gartner estimates that by 2020, 85 percent of CIOs will be piloting AI programs through a combination of buy, build and outsource efforts and that AI-generated business value will more than triple from $1.2 trillion in 2018 to $3.9 trillion by 2022.
Real-time predictive scheduling and decision-making assisted by access to myriad sources of data is already available, especially to larger businesses, and use of such tools is expected to increase. This trend is also already filtering down to such things as Google searches for local restaurants, for example.
Searches may not only provide location and menu information but also how busy a restaurant is. In turn, the restaurant may harness data to know how many customers may be appearing soon as a result of recent internet searches, and thus how many employees may need to be scheduled for nightly shifts.
This trend also is affecting recruitment. AI or sophisticated software may be configured to help prepare job descriptions, search online for candidates, and screen applications before a human takes the next steps. These tools can also help prepare qualifying questions, gather profiles from various sources, and create job-specific online games and tests to improve screening. Furthermore, data-driven recruiting can produce, monitor, and improve metrics of all kinds, including cost-to-hire, time-to-hire, retention, and benchmarking. Data analysis can also help employers steer clear of screening questions that could result in discrimination, making recruitment more objective, legal, and accurate in the process.
Beyond recruitment, big data may also be harnessed for employee monitoring, for example by creating journey maps. These are complete records of the employee’s experience from recruitment to separation, and they include everything from social media to time tracking reports. Put together, they can summarize an enormous amount of data into useful portraits of how employees are experiencing their work. These maps can in turn guide companies toward improvements in engagement. Although based on data, journey maps are about people and how they are engaging with their workplace. As such, journey maps can be a highly valuable tool for human resource managers in maintaining morale.
Data analytics scale well, allowing companies to monitor and predict even at the scale of the individual warehouse employee. Amazon, for example, has sought a patent on haptic wristbands that help guide warehouse workers to the right bins. Large employers are using predictive analytics to help managers make their smaller, day-to-day decisions with more accuracy and confidence, thus improving long-term performance gains.
Put journey maps and other data tools together, and managers will be much more confident about predicting the future. It is small wonder, then, that Forbes reports that IBM predicts that data scientists–the people who know how to extract useful information from big data–will continue to be in high demand. Forbes says: “It takes 53 days on average to fill an Analytics Manager position in Professional Services, making this position one most challenging to recruit for.” Data-driven analysis can help not only predict what employees will be doing next but also what employers should be doing next in a fast-moving, global market.
Every Company Is a Global Company
Around the world, big data is now guiding decisions as large as whether to completely change a business model (as, for example, when Netflix moved from mailing DVDs to streaming and content creation) or as small as scheduling a local office. While the internet makes a business visible around the world and can help smaller businesses stay competitive, it can also quickly bring a business to ruin. Social media stories can spread quickly, making millions aware of a discriminatory act by one franchise manager, for example, damaging a large company’s reputation globally. Similarly, the internet communications of employees and customers can influence a company’s reputation and bottom line.
The law may not be keeping pace with all aspects of the Fourth Industrial Revolution, but it does provide guidance on reputation management. Cases such as Romano v. Steelcase, Inc., EEOC v. Simply Storage Management, Mackelprang v. Fidelity National Title Agency of Nevada, Inc., and American Medical Response of Connecticut, Inc. v. International Brotherhood of Teamsters, Local 443 offer lessons on how companies can protect their reputation online. The gist of these cases is that no one should expect that their online communications, including on “private” social media accounts, are actually private. When you communicate on the world wide web, you are communicating with the world.
As each industrial revolution shrinks the world, every company and employee is more accessible anywhere. This leads to another trend: remote, semi-remote, and plug-and-play office work. Offices are getting smaller and easier to move, as more employees work remotely and access to office equipment and storage become less important. Similarly, big data supports “gig” employment, in which workers are assessed not so much on adherence to 9-5 schedules and appearance at the office and meetings but on performance analytics more specifically tied to each job. Another feature of a shrinking world is that employers–and work–are more likely to be international. For example, the Forbes article linked above cites McKinsey, a global management consulting firm, as having estimated that “by 2025, more than 45% of Fortune 500 companies will be from emerging markets, including greater China.” For Americans, this can mean working from home or a “plug-and-play” office site for a foreign company. One example of this trend involves English teachers in the United States who give lessons in Chinese classrooms remotely.
Trends in the United States
Also on the horizon for Americans is a push to increase the minimum wage. When Congress convened in January 2019, 181 Democrats signed on to a bill that would incrementally increase the federal minimum wage to $15 over the next few years. Whether this bill will pass as is, or whether it will be modified for regional costs of living, for example, could depend on the next presidential election. Another area of employment law that the two political parties may be able to reach a compromise on is immigration enforcement in the workplace. Immigration audits have increased in the last two years, and this trend may well continue no matter which party wins the White House in 2020. Finally, one additional trend worth noting is extreme weather. While some may not agree on whether global warming is to blame, recent fires in the West and storms in the South and East have demonstrated the need for businesses to plan for data distribution, emergency shutdowns, and shortages. This need reinforces the trend toward smaller, more easily moved facilities.