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The question of how to draw the lines between generations is always an interesting one. Even ancient Sumerian clay tablets are said to have contained text complaining about a poorly behaved son — so the situation in which the older generation finds the younger one new and unfamiliar, and is not sure how to respond, seems to have been the same in ancient times as it is today.
HR has also been making the effort to reasonably segment employees — from Baby Boomers to Generation X, the Millennials, and most recently Generation Z — in order to apply differentiated HR practices. But with recent rapid social change and the resulting changes in workforce characteristics, the approach of using "generation" as a single criterion is increasingly showing its limits.
In a social sense, understanding the dividing points and characteristics of each generation, and using that to differentiate how HR is run for each group, certainly has positive
effects. For example, many Korean companies have recently used various communication programs that draw on the communication styles of the Millennial generation — preventing intergenerational conflict in advance and contributing significantly to integrating the entire workforce. And as long as there is a consistent and clear difference between generations, this strategy continues to be valid.
The problem is that the boundaries between generations are breaking down quickly. According to a recent Deloitte study, the perception gaps between generations on values like work-life balance and on expectations around job security and promotion are projected to narrow rapidly over the next three years.
It used to be widely held that valuing work-life balance over monetary compensation, and showing low expectations for job security and promotion, were defining traits of the Millennial generation. Going forward, that generalization may no longer hold. Related research has also found that performance management, compensation, and benefits programs in particular show relatively low correlation with generational characteristics.
The reasons for these findings are many, but the most important is probably the breakdown of the usual proportional relationship between position on the career life cycle, age, and role — driven by social and economic changes such as extended retirement ages, the re-employment of older workers, and the loosening of seniority in role assignments.
As the meaning of generation as a basis for workforce segmentation grows fuzzier, leading companies are showing a tendency to break down their HR operating standards even further — to the level of "the individual" — and run them in a differentiated way. This is both a reflection that "one size fits all HR" is no longer valid, and a borrowing of the recent marketing methodology of maximizing performance through personalized customer experience (CX).
By providing an employee experience (EX) similar to customer experience, companies can motivate their people more effectively and lift their results. According to research by market research firm Gartner, companies that deliver more personalized, consumer-oriented employee experience services see average performance rise by about 17%.
From the employee's standpoint, too, people hope to be treated as important members of the company throughout their lifecycle — from joining to leaving — and to enjoy positive experiences along the way. According to a recent Towers Watson survey, about 56% of respondents expected their company to make the effort to understand its employees at the level it understands its consumers, while only about 39% felt that expectation was being met.
Personalized HR requires a new lens that can comprehensively view the complex and varied personal traits of an individual — interests, values, preferences, and opinions on specific issues — and gain insight from them. In this respect, MetLife's case, which applies a variety of perspectives on employees including generation, is worth referencing. MetLife segments its employees by a total of five criteria, and specifically pursues a comprehensive understanding of each individual through the following lenses.
① Demographics (age, gender, income, education level, etc.)
② Firmographics (job tenure, company size, industry, role, job family, etc.)
③ Attitude toward life (optimism, future- vs. present-orientation, attitude toward change, sources of joy and stress, etc.)
④ Attitude toward work (work-life balance, intent to leave, motivations affecting tenure, etc.)
⑤ Needs from employer (career development support, compensation, benefits, culture, etc.)
Regardless of company size or shape, personalizing HR operations requires the help of new technology — particularly digital automation systems like AI and big data analytics. Even the most capable HR cannot, through human effort alone, identify the individual needs of every employee and provide a fitting solution. The recent trend of leading global companies — those with strong AI capabilities — being the first to attempt personalized HR is a natural result of this.
The IBM HR system introduced below is one of the most representative examples of personalized HR using AI. Originally developed to improve HR operations and satisfaction for IBM's own employees, it has recently been expanded into a solution business that external corporate customers can also use.
IBM provides AI-based, personalized HR services from the application stage all the way through post-hire growth, as follows.
· Attract: "Watson Candidate Assistant (WCA)" provides information through chatbots based on natural language processing (NLP), and uses skill-matching algorithms to analyze applications and guide candidates toward fitting positions.
· Hire: "IBM Watson Recruitment (IWR)" rapidly matches the skills required by a job to applications, and uses existing data to predict future performance — helping screen applicants without bias.
· Engage: "AI Manager Alerts at IBM" supports manager decision-making by alerting managers to facts that significantly affect workforce operation — promotion likelihood for employees with certain skills, intent to leave, risk of missing performance targets. "AI Chatter Analysis at IBM" surfaces the three core issues found on internal social media and recommends fitting solutions to managers, including suggested feedback for specific employees.
· Develop: "Your Learning" recommends personalized learning content and channels by comprehensively considering job role, organization, required skills, and training history.
· Grow: "Watson Career Coach (WCC)" offers career advice through Q&A based on personal career information, and "Career Navigator" recommends fitting paths and tailored learning based on career goals.
Compared with global leaders like IBM, in Korea it is still hard to find cases of personalized HR built across the board. Some attempts to introduce AI in recruiting are currently underway. That said, even short of full AI-driven automation, an early stage of personalization — systems where employees can self-service their own work-environment needs — is being applied at a few companies.
For example, POSCO's groupware lets employees selectively download apps for their own work — mail, messenger, shared storage — much like Apple's App Store, and lets them freely arrange their portlets (screen layout) by frequency of use and personal preference.
Applying AI-based personalized HR at the current level, with no preparation at all, is somewhat unrealistic for Korean companies. Whether internally or externally, securing the necessary technology capabilities — including AI — is one priority, but the immediate task is to begin accumulating the complex needs of individual employees as big data.
To do that, a practical approach is to use the regular surveys companies already run each year. As mentioned, this will require an advanced survey tool that can categorize employees not only by traditional demographic divisions like generation and age but by more granular criteria. The survey questions should also be designed more carefully — to capture each individual's values — rather than simply asking about satisfaction.
And as techniques like natural language processing (NLP) have advanced, the possibility of analyzing unstructured data — open-ended responses, for example — and extracting meaningful insights has grown significantly compared with the past.
Finally, if it is hard to apply the identified individual needs across all of HR, you should approach personalization in stages, starting with areas where it is relatively easy. For example, building a system in which employees can choose benefits according to their preferences within a fixed total cap is worth considering as a starting point for personalized HR.
Today's employees, as internal customers, want their company to deliver the best experience throughout their entire lifecycle from joining to leaving.
And that experience is grounded thoroughly in the differentiated needs of each individual. Starbucks drew a lot of attention with its "call my name" service — calling out the name of the customer who placed the order, instead of an order number on the receipt, when handing them their coffee. Going forward, doesn't HR also need to respond to a single individual with their own personality, character, and needs — rather than as one of many in a particular generation?