Editor’s Note: We would never dream of trying to predict the future—that’s why we left it up to the futurists. In this series, we interview experts in HR, recruiting and the future of work to get their take on what’s next.
Machine learning, artificial intelligence, blockchain—these emerging technologies are shaking up industries across the board, but many HR professionals are still wary about applying them to the work they do, says HR digital transformation strategist Sherryanne Meyer.
All-too-common roadblocks like a shortage of resources, unchanging attitudes among leaders and a lack of understanding keep organizations from exploring the full potential of these technologies. However, machine learning, artificial intelligence and even blockchain will only rise in prominence over time, and HR professionals can’t put them off any longer.
Leaders who think they can eventually just push a button and these emerging technologies will start to work their magic have the wrong mindset. The key to success is realizing your technology is only as strong as the data that powers it. Meyers believes that “data is king,” and managing and protecting it has to become a core function of HR.
“Data management has to be taken seriously not only in terms of ensuring consistent data definitions and data entry culture, but also protecting the data,” she says. “The better you have those practices in place, the more your data can be used to make decisions and automate within an approved productivity.”
To help HR professionals get started, we talked with Meyer about applications of machine learning, AI and blockchain that organizations can start to test today, and the data best practices for effective execution.
AI is a complex technology, but the simplest definition is a machine that can not only learn, but also reason and act independently. And the first rule of AI is you can’t set it and forget it: It’s needs people to submit more data so it performs tasks better.
“Artificial intelligence will only get smarter as we learn more from our machines and we put more data into it—if the data is accurate,” Meyers says.
One area where AI can benefit HR departments today is in employee learning. There’s a lot to be desired in the employee learning experience. Many learning systems were built to administer required training, but they’re not designed for self-service. If an employee needs development in an area that doesn’t explicitly require training, or someone shows potential in an area not currently related to his or her job, it’s cumbersome to find the right training.
A learning platform with AI at its core can take in employee data from performance reviews, see the areas where someone needs development, and produce a list of generate a list of suggested courses for that employee available in the organization’s learning system.
According to a recent survey from IT service management company Sierra-Cedar, 8 percent of organizations adopted machine learning in 2018 and 21 percent said they’re evaluating the technology for future use. The report also notes that early forms of machine learning may be mistaken for AI in HR organizations, and that machine learning may already be embedded in existing technology without HR teams fully realizing it.
In layman’s terms, machine learning allows computers to complete tasks independently of humans, and they get better at doing those tasks over time . Essentially, the technology helps HR organizations learn more about their workforce, Meyers says.
So how can companies put machine learning to work when they’re ready? Industries like retail can use machine learning to get more insights into their staffing needs, which helps them improve their scheduling processes and prevents staff shortages. Today, managers at retail stores develop staff schedules based on the shopping season and sales generated in previous years—”But machine learning can bring other data points into staffing decisions, and connect data across sources,” Meyer explains.
Is there an event in the area that will drive more foot traffic? Is there a road closure that might bring more people past your store? For a gas station in particular, are your prices lower than your competitors that day? Drawing conclusions from a myriad of data points and trends gives machine learning an edge over traditional approaches, according to Meyer.
The Sierra-Cedar 2018-2019 HR Systems Survey found that just 3 percent of organizations use blockchain in human resources and a vast majority—85 percent—have no plans for blockchain. But Meyers sees an opportunity for HR to start using the technology in the recruiting.
Blockchain first came into the mainstream during the bitcoin craze, but its application extends far beyond finance. Blockchain is a universal ledger, which provides companies and individuals that use it a secure way to store and share digital records, or “blocks.” The ledger is unchangeable, thereby potentially reducing fraudulent activity.
One of the earliest experimental applications of blockchain in HR is resume verification. Through connected blocks of confidential data that candidates can’t alter, Meyers says, HR can instantly verify candidate resumes.
“Because of time constraints, it’s not often verified that an applicant actually got their diploma from where they say they did,” she says. “If those blocks of data existed confidentially in an environment where recruiting system could access and confirm them, we could go forward with confidence.”
Beyond some of these earliest applications, there are many other ways that AI, machine learning and blockchain may soon shake up the world of HR, and it’ll be up to organizations to identify the most effective methods of implementation. Regardless of the specific route they take, “HR leaders have to make technology a priority,” Meyer says, and not be afraid to take risks.
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