How can there be anything more human than Human Resources? When it comes to HR technology transformations, the human in us seems to be downplayed when contrasted with the technology. Nothing could be further from the truth, however.
HR tech transformations are never easy. But why “transform” in the first place?
Imagine, if you will, an escalator in a mall that’s going down. Just for fun, you get on the escalator going down but then start walking up. If you climb the escalator at just the right pace, you can essentially stand still—in space—but you’re actually still climbing as the escalator goes down.
In the business world, it’s like being on an escalator that’s going down. If you work to maintain your position in the market, you can just barely stay in one place. But if you transform, you can leapfrog ahead and make a truly human performance and workforce impact on that organization’s success.
Which do you want to do: stand still and hang on, or be instrumental in an organization’s human capital success?
Common Transformation Challenges
What are the common challenges faced by organizations trying to transform their Human Resources departments? There are so many. Workers may be fearful or reluctant to change due to worries about job loss or not being technologically savvy enough. Leaders may be concerned about the work effort and time required to migrate off legacy systems. There may be concerns about the privacy and security of employee data due to the nature of jobs in Human Resources. Workers may wonder about how much training they’ll need to pack into an already full day to learn the new technologies and systems. Omnipresent budget issues may present themselves, and leaders may need to make tough choices. In legacy systems, data quality may have been an issue that escalated over time and without proper maintenance. Legal and regulatory issues around employee data may be confusing and could open an organization up to risk if not handled properly. A culture that doesn’t incentivize innovation and risk taking may override the need to transform. Leaders may worry about showing positive ROI for a transformation project.
Isn’t it better to play it safe and wait to see what happens?
Of course, that’s one way to go, but it’s important to keep in mind that doing nothing is still a decision, and it’s a decision that has risks and consequences, just like every other decision that is made. (Keep the escalator analogy in mind.) If an organization chooses to stand still and let others experiment and learn from those experiments, they will necessarily be falling behind. It’s not always possible to catch up, and catching up can be expensive.
But what about all the risks associated with pilots, trials, and learning experiments?
Privacy, Security and Risk
Mitigating risks and putting up guardrails around experiments is of the utmost importance when it comes to Human Capital and related data. There really is a way to have your cake and eat it too. It’s possible to start small, put limits on data, and learn—while fully mitigating risks at the same time. But how?
Data security is one of the first and foremost risks when it comes to Human Capital technology. If possible, find someone you work with who is a data security expert and recruit them to help with the difficult questions. If such a person doesn’t exist at work, you might be able to find someone similar in your personal life. So long as you don’t talk about organizational specifics, you can treat that person as your data security “guide.” It’s important to get all the relevant data security information before embarking on any experiment. You can find out about how any external collaboration partner or vendor handles security. Have they had any incidents? Do they adhere to recommended security protocols? Do they regularly employ a third party to test for vulnerabilities? Will they share the results of those tests with you?
What about privacy? Human Resource technology always needs to consider the implications of privacy. Again, the first order of business may be to make sure that the platform is as secure as possible and not vulnerable to hackers and nefarious attacks. However, let’s look at some more subtle vulnerabilities. What if an employee talks to an AI about a problem they are having with a colleague and they disclose that they are being bullied or subjected to discrimination? This conversation gets logged into the system. Has the employee been warned that certain conversations must be acted upon by law? What precautions has the vendor taken to make this clear before the conversation occurs? What commitments will need to be followed to ensure the organization abides by the law and addresses employees’ concerns, even if they are brought up using an AI agent?
In the not-too-distant past, there was a security incident at a well-known electronics manufacturer where an employee asked ChatGPT for help with his work. He unknowingly exposed company secrets to the Large Language Model (LLM) and those company secrets were used to improve the their-party model itself. How could this situation have been avoided, especially by ChatGPT itself?
For starters, a third-party (external) provider or vendor should be upfront about how a client’s data will be used. This sometimes happens at an account level, but what about at the individual employee level? If the employee who unknowingly disclosed company secrets had seen some sort of warning from ChatGPT, would that have made a difference? Like so many situations, human and social engineering is just as important (if not more so) as technological engineering. Human beings are the final line of defense in the security of information.
Let’s say that you’ve gone through all the worst-case scenarios and feel reasonably confident that data security and privacy risks are low and contained. What other roadblocks might you come across?
Managing Workers’ Feelings Toward Change
Workers’ feelings toward change might be something to consider. In the world of technological adoption, people are often categorized as Innovators, Early Adopters, Early Majority, Late Majority, and Laggers. A fact that’s often overlooked is that Innovators and Early Adopters are actually a very small percentage of the whole employee population. Furthermore, there tends to be a large gap between the Early Adopters and the Early Majority. This gap is so prevalent that there’s a lot of writing around the concept of “crossing the chasm” between early adopters and early majority.
What’s to be done about employees’ resistance to change?
First, it’s important to validate every person’s stance on change. There’s value in being an Innovator. There’s also value in being a Lagger. Perhaps most importantly, the Innovators need to see the value in the Laggers, and the Laggers need to see the value in the Innovators. This may seem obvious, but when change is happening, it may not play out this way.
In the case of the Late Majority or the Laggers, they may be present to balance out the blind enthusiasm of the Innovators. Their roles are critical to pointing out risks and thinking through worst-case scenarios, and perhaps protecting the organization from future harm. If they feel their roles are important, and that they have an important place in the technological transformation itself, they will be much more likely to get onboard with the change process.
Navigating the Pace of Technological Change
The pace of change has increased dramatically in the past decade or so. Much of this change has been brought about using technology. The changing pace is not inherently bad or good (think: the pace of improvement in medical technologies is undeniably good, but the pace of increase in online phishing scams and the proliferation of internet bad actors is undeniably bad.) How does the pace of change affect people’s work, people’s roles, and people’s jobs?
It’s difficult to read a news headline right now that doesn’t talk about how AI is taking people’s jobs. A robot might be pictured flipping someone’s hamburger. An AI might be drafting a chapter in a scientist’s report. An algorithm might be running calculations for the CFO, looking at probabilities of the company’s financial future. With the advent of Generative AI and beyond, what used to be a fear belonging to entry-level workers has propagated to professionals and expert-level workers everywhere. Is it any wonder?
Many talk about how the workers who really need to worry about their jobs are the ones who are not learning to work with their new, robotic counterparts. There may be some truth to this. Perhaps a better question is, how much effort are workers putting into studying how technology will change their jobs? Make their jobs easier? Make them more productive? Are they proactively experimenting with Generative AI to see how they might be able to leverage the technology in their job—either now, or in the future? The “ostrich in the sand technique” of dealing with new technology may not end up serving workers well.
Shared Responsibility in Adapting to New Technologies
Who is responsible for helping a workforce adapt and change when new technologies mandate change? It’s unlikely that the responsibility falls squarely on just workers or just employers. Steps taken by workers, employers, schools, governments, and perhaps others will, in concert, help to make this transition easier.
Back in the 1970s when the ATM (automated teller machine) was invented, there was mass speculation that bank tellers would cease to exist. However, that’s not what happened. As ATMs reached mass adoption during the 1990s, according to the American Enterprise Institute, “... the average bank branch in an urban area required about 21 tellers. That was cut because of the ATM machine to about 13 tellers. But that meant it was cheaper to operate a branch. Well, banks wanted, in part because of deregulation but just for deregulation but just for basic marketing reasons, to increase the number of branch offices. And when it became cheaper to do so, demand for branch offices increased. And as a result, demand for bank tellers increased.”
Another biproduct of ATMs was that tellers could take on more meaningful and interesting work. Instead of handing people five $20s and a $50, they could train to get more knowledgeable regarding long term financial planning, help a couple save for a house down payment, or explain the difference between various insurance products.
There is no question that the nature and types of jobs are changing, and they are changing at a rate never seen before in history. Blanket statements about AI and jobs, however, are unfounded. Is it possible that people will do less manual labor? Sure. Might fewer human beings need to be sent to do dangerous jobs? Absolutely. Will the nature of work become less rote and mundane? It’s highly probable. The sooner organizations and workers recognize how work is changing and how to get ahead of this curve instead of behind it, the lower stress levels will be, and the passionate workers can be about the future of work.
Learning from Success Stories
In 2020 when the world went into COVID lockdown mode, HubSpot—a customer relationship management software company—took a close look at how to foster human connections in a remote or hybrid work environment. One of the critical themes as determined by HubSpot was to educate workers, especially new hires, on its communication technology stack. That stack also had to be re-examined and revamped based on the sudden need for remote and hybrid word. (Reference: https://medium.com/@HubSpot/how-hubspot-makes-hybrid-work-work-3d992634f403) According to HubSpot, the biggest error companies make when transitioning to hybrid or remote work is just replicating the office environment in the new remote or hybrid world of work. In other words, you can’t just copy and paste what worked before; new ways of communicating, connecting, and working are needed. Almost anytime new ways of work are needed, new technologies are needed as well.
One of the standout modifications HubSpot made was with their new-hire onboarding process. When a new employee joins a fully remote or hybrid organization, the stakes are high. HubSpot recognized this and focused on their tech stack and their communications stack. This involved not just purchasing technology but specific training on when to use what. When should someone use Slack? Email? Zoom? HubSpot’s internal Wiki? How about other communication options like dialing your boss on their cell phone? HubSpot’s Learning & Development team was able to keep their new hire NPS even higher during the pandemic than it was before COVID hit.
In another example, Walmart implemented Virtual Reality (VR) training for their employees to help them prepare for specific events like Black Friday or the Christmas Holiday Season. (Reference: Walmart Revolutionizes Its Training with Virtual Reality (shrm.org) Why not just use traditional training? According to Walmart, many of their stores are open 24/7 and they didn’t have an opportunity to train their employees “after hours.” They also didn’t want to bother customers while they were shopping. Additionally, Walmart talked about using VR technology to recreate scenarios that were impossible using ordinary training like how to mitigate a dangerous situation or avoid an aggressive shopper.
In 2021, Best Buy was named one of Fast Company’s Best Workplaces for Innovators. Best Buy has long focused on fostering a culture of innovation, but during the COVID pandemic, Best Buy embraced a number of new employee technologies and did so in a smooth and speedy way. (Reference: Best Buy named one of Fast Company’s Best Workplaces for Innovators - Best Buy Corporate News and Information) When the pandemic hit, Best Buy struggled to understand how their customers’ technological needs were changing. They solicited feedback and ideas from their workforce and within just a few days, implemented new technologies that allowed employees to continue supporting customers— even from home. At the time, this was unprecedented for a “big box” retailer. Best Buy also whipped together a health screening employee app in just a matter of days that prevented infected (or suspected infected) employees from coming to work.
In looking through success stories, a few themes stuck out: 1) Communication was always central to any digital transformation, 2) Employees (or workers) were central—not tangential - to the transformation strategy, and 3) Starting small and fast was better than starting big and slow.
By following these best practices and—perhaps first and foremost—by not being afraid to experiment, learn and understand where safe and risky practices lie, we can move our profession ahead and be true, strategic leaders when it comes to technology adoption and digital transformation.
Thank you for joining us for this edition of the SHRMLabs WorkplaceTech Pulse! And thanks again to Carolyn for her incredible insights and contributions. Please click the link below to learn more about Humaxa and stay tuned for the next edition of WorkplaceTech Pulse.