A guide to HR predictions, trends, and forecasts
The internet contains thousands of forecasts about the future of HR. Lists of HR predictions and trends sprout up every year like mushrooms after a spring rain. Forecasts exist on things as broad as the overall future of work to as narrow as the future of background check automation technology. For several years, I compiled hundreds of HR predictions into a review called the “wine-bottle index”. This placed forecasts into categories and rated them based on whether they were truly new things or simply “old wine in new bottles”. The wine-bottle index morphed into the SAP HR Meta-trends report which uses generative AI to do the same thing but with less humor. RedThread Research publishes a similar summary of HR Mega trends. And I suspect before long someone will create a HR Mega-Meta trends summary summarizing summaries of HR trends. This proliferation of HR predictions poses a challenge to HR leaders who want to create future-forward strategies but don’t want to read endless lists of trends. And do not want to rely solely on predictions made by a few individuals or companies that represent just one perspective regarding the future of HR. This prompted me to write this guide on how to sift through HR predictions. The following eight lessons are based on reading literally thousands of HR forecasts over the years.
1. HR forecasts are about finding new solutions to familiar problems.
2. Most HR forecasts are designed to influence buying behavior
3. HR predictions often use new terms to describe existing issues
4. HR predictions are based more on speculation than science
5. The most influential HR trends are often the hardest to predict
6. Predictions based on HR technology often take years to unfold
7. Predictions based on “science” are often overblown and can be damaging
8. Making effective use of HR predictions depends on how you approach the challenge
1)HR forecasts are about finding new solutions to familiar problems. The primary purpose of HR is to ensure an organization is employing people who are able and willing to execute the company’s strategy while controlling headcount costs and meeting ethical standards and legal requirements. HR is about people, and the fundamental psychology of people changes little from one generation to the next. As a result, the core challenges of HR are fairly constant. How companies practice HR may radically change, but it is always about designing jobs, hiring people, developing employee capabilities, increasing workforce performance, retaining talent, complying with regulations, reducing operating costs, and building cultures. One way to make sense of HR predictions is to interpret them relative to the constant, perennial HR challenges every company must solve.
2)Most HR forecasts are designed to influence buying behavior. Most HR predictions are directly or indirectly created, funded and promoted by vendors and consultants who have an interest in influencing how companies spend their HR budget. HR forecasts are often designed to convince HR leaders that their companies have or will soon face problems that can be solved using certain kinds of solutions and services. For example, if a company sells employee engagement solutions, then their forecasts will emphasize things like talent attraction and retention that can be addressed through improving employee engagement. This does not mean HR forecasts are incorrect or insincere. But most come from people who have a commercially oriented perspective. There is nothing wrong with this! It is called sales and marketing, and it drives growth of economies. But it is worth remembering the following question when you read HR forecasts, “who wrote this and what is their goal in sharing this information with me?”
3) HR forecasts often use new terms to describe existing issues. Building a healthy workforce is like a building a healthy body in the sense that it is not something that is ever truly accomplished. Instead, it is maintained by continuously paying attention to enduring issues. When it comes to our bodies, these issues are things like weight, flexibility, strength, and mental wellbeing. When it comes to workforces, issues include workforce planning, organizational design, candidate recruiting, workforce communication, skill development, employee engagement, change management, operational efficiency and HR cost control. The relative importance of these issues changes in response to economic conditions and employee and business stakeholder expectations, but they are never truly resolved.
HR predictions often try to draw attention to certain issues by giving them clever names and acting as though they were something new. Examples include “quiet quitting” (aka, an aspect of engagement), “transparency” and “employee listening” (aka, methods for increasing communication), and “future ready workforce” (aka, everything companies are doing already but with more focus on the future). There may be value in giving familiar issues new names if it leads people to think about these issues in more productive ways. Nevertheless, many of these HR predictions are merely describing the world as it already is. To illustrate, here is an HR forecast that I could have made every year since I started working and that will still be relevant long after I am gone. The following seven issues will be top of mind for HR leaders next year: finding good talent, increasing workforce communication, strengthening employee engagement, building future ready skills, improving change management, optimizing operational efficiency, and reducing HR costs.
Recommended by LinkedIn
4) HR predictions are based more on speculation than science. A lot of HR forecasts are presented as research studies, but virtually none of them should be considered objective research. These studies are influenced by the goals of the researchers, or more specifically the goals of the people paying the researchers. This shapes the research design and data used to formulate HR predictions. HR forecast studies focus on what the researchers think is important about the future, which probably has more to do with their company’s goals than your company’s goals. This does not mean the studies are not valuable. It does mean they are looking at the future of HR from a specific viewpoint that may not align with yours.
The data used in some HR forecasts can also be somewhat questionable. For example, a lot of HR forecast data comes from panel surveys. Researchers who rely on panel data often do not know who is responding to their surveys with any level of specificity. They simply contract for data with a company that tells them something like “these are HR leaders from Fortune 1000 companies who are paid to complete the surveys”. I often wonder, who are these HR leaders taking all these panel surveys? Most HR leaders barely have enough time to complete surveys for their own company, let alone someone else’s.
5)The most influential HR trends are often the hardest to predict. The greatest changes in HR occur when they are driven by customer needs instead of vendor marketing budgets. This occurs when businesses encounter problems they must solve but cannot solve with existing resources or programs. There are two conditions when his happens, and neither are easy to predict.
Disruptive socio-economic events are hard to predict because what makes them disruptive is their unexpected nature. Disruptive technological innovations are hard to predict because whether they are disruptive depends on how companies choose to use the technology. A potentially disruptive technological innovation may sit unused for years until a triggering event leads to rapid, widespread adoption. For example, the technology required to support hybrid work models existed for years before the COVID pandemic forced companies to adopt it in a widespread manner.
6) Predictions based on HR technology often take years to unfold. A few HR predictions tied to technological innovation have experienced exponential growth in adoption over the course of one or two years (e.g., generative AI). But most plod along for decades. For example, predictions were made in the early 2000s about HR moving to cloud technology. Cloud technology has been steadily adopted since then, but many companies still use on-premise HR systems dating back to the 1990s. Similar examples can be found regarding predictions about blockchain, metaverse, and skill ontology technologies revolutionizing HR practices. Trends based on technological innovation follow slower trajectories compared to trends caused by disruptive events because they depend on companies choosing to invest in the potential of technology, as opposed to companies being forced to use technology to respond to external events they cannot control.
7)Predictions based on “science” are often overblown and can be damaging. Being a behavioral scientist myself, it often saddens me when HR forecasts claim “behavioral science” shows companies must change how they manage people. Behavioral science is messy and rarely conclusively shows anything[1]. Every peer-review research article discusses why the study findings might not generalize to other settings. Problems can occur when companies radically change how they manage people based on questionable scientific advice. Examples include past trends that used "science" to encourage companies to get rid of performance ratings only to damage procedural justice by decreasing transparency or embrace generational differences which increased ageism by viewing people differently based on the year they were born.
When you read a trend or forecast that claims to be based on a scientific discovery from the world of psychology, neuroscience or behavioral economics try to seek out an impartial professional from the field and get their opinion. Scientific research is valuable for challenging assumptions about workforce management and suggesting ways to improve workforce performance. But never do something solely because someone claims it is based on science. Nor should you accept the claims of any single researcher as being representative of their entire field. This includes academic professors who arguably spend more time marketing themselves than they do conducting actual research.
8) Making effective use of HR forecasts depends on how you approach the challenge The intention of this article is not to question the value of reading HR predictions and trends. Quite the contrary. After all, I do not just read these predictions, I also write them! The goal of the article is to enable better use of HR forecasts to guide business decisions while guarding against risks caused by their inherent limitations and biases. With that in mind, here are five specific suggestions on how to get the most value from HR trends, forecasts, and predictions:
Last, when thinking about the future of HR do not be afraid to challenge business leaders whether the way they managed people in the past is the right way to manage them in the future. Are we doing things because they are effective, or simply doing them because they are familiar? One benefit of HR forecasts is they can help leaders embrace the reality that companies must continuously adapt their HR methods or they will not have a future.
[1] With the exception of extremely well-researched topics such as goal setting, procedural justice, or performance feedback.
CEO at Syndio | Co-founder of Smartsheet | B2B SaaS | HRTech
1wThis is great behind-the-scenes, VIP advice from one of the architects of the OG HR prediction machine! Thank you! Also, I’d argue the EU Pay Transparency Directive is one of those social-economic shifts that will cause upheaval in how multinational companies approach pay, promotion and benefit explainability. My two cents from the cheap seats!
Top 100 HR Global HR Influencer | HRE's 2024 Top 100 HR Tech Influencers | Speaker | Future of HR
2wMy friend, this is beyond spot on. Bravo. Especially the one about research to influence buyers behaviors, instead of research to influence HR tech products adapted to real needs (by the way, most of this bullshit kind of research comes from the same person….. 🤔)
Chief Workplace Psychologist | XM Institute
2wGreat piece, Steve! Much of this deeply resonates with me as a consumer and author of these sorts of trends. I'll only add that as a scientist, I've run across many other scientists in my own and related fields who completely dismiss things like new terms for old concept (trashing the ideas in academic forums or on social media), or dismiss research that was not conducted in an academic setting, often due to the inherent conflicts you cite (as if the pressures in academia don't exist or their own personal passions don't drive their curiosity). I love your guidance here - very balanced! And I hope that all of us in the scientific community can remember that we are communicating with people who don't always have the same background as we do - weaving into the nomenclature of today IS important imo (even if its old wine in new skins - this is a perfect opportunity to redirect). And also to remember that science is iterative and represents the best we know today...which enviably changes as we learn more.
Vice President, People Sciences & Org Capability @ T-Mobile | Ex-Amazon Executive
2wAllan Church, Ph.D. Shane Driggers Alexis Fink
Keeping the People in People Analytics | People Analytics speaker, blogger, keynote, & podcast guest | People Analytics Strategy at One Model
2w"who wrote this and what is their goal in sharing with me" 👏👏👏 Awesome article and a great reminder for everyone heading into end of year predictions