Meet Dr. Hila Chalutz-Ben Gal

In one of her studies, Dr. Chalutz-Ben Gal collaborates with a startup that specializes in placement of engineers using analytical and predictive AI-based tools. "The system extracts data from LinkedIn, analyzes it, and generates tailored recommendations for employee recruitment," she explains. "Our research focused on identifying and correcting algorithmic AI-bias embedded in the recommendation system. We discovered that placement algorithms have inherent bias that stem from the training data set that discriminates [between men and] against women, or between candidates from diverse cultural backgrounds. We proposed structured ways to reduce bias. This field is called “AI Fairness”, and it is a crucial up-and-coming issue in the field of People Analytics and beyond."

Dr. Chalutz-Ben Gal specializes in the field of People Analytics (PA), data-driven tools and techniques to understand, analyze and optimize decision-making related to human resources (HR) in systems and organizations, which aims to use data-driven tools and artificial intelligence to analyze and improve decision-making processes related to human resources in organizations. "It’s a relatively new field, but is rapidly growing in demand. The introduction of digitization and artificial intelligence into our lives, along with the changes to the job market, require changes to the notions and paradigms that have ruled the field for years," she explains. "Collecting, processing, and analyzing human and organizational data allows us to achieve new insights regarding the behaviors and performance of people in various systems, in order to improve employee performance, projects, and organizations as a whole."

She claims that in most organizations, and certainly in high-tech, employee-related expenses such as recruitment, training, development, turnover and retention  - constitute the lion's share of the companies’ budget. It is therefore critical to manage this resource effectively and efficiently, especially in environments that offer relevant data. "Research in this field is intended to focus on work processes, performance and goals measurement, and examine recurring phenomena and patterns. For instance, why do employees leave certain positions after a short or long period of time," she elaborates. "The field is tightly bound with the industry and the world of information systems, because most of the data we research is found on the organization's servers, as well as in social networks, such as LinkedIn."

How is native language related to employee turnover?

Dr. Chalutz-Ben Gal began her academic journey at the Hebrew University. She then continued to attain her Master's degree at Brandeis University in Boston and gained significant hands-on experience in leading international companies. Upon returning to Israel, she pursued a PhD at the School of Management at the University of Haifa. She did her post-doctorate at the University of San Francisco, during which she took part in a collaborative research with Stanford University – the Digital Living 2030 project – and published her research in leading journals and conferences, such as the Academy of Management. In 2024, Dr. Chalutz-Ben Gal joined the Faculty of Engineering. She is now working on establishing the field of People Analytics at her specialized Laboratory in the Faculty of Engineering, as part of the Industrial Engineering and Information Systems Program.

Dr. Chalutz-Ben Gal’s lab is focused on three research domains. The first is classic People Analytics, covering topics such as data-driven research of employee turnover. "We tend to think that people leave their jobs because they're not satisfied with the position, or due to low pay, but there can be many other reasons for employee turnover, some of them hidden or counter-intuitive," she says. "For example, we had a very large organization that was dealing with the challange of engineers leaving certain positions. By applying machine learning models, we discovered that bilingual employees at native-speaker level have vastly different turnover patterns compared to the general population. These findings would not have been discovered without our analytical analysis."

Another research domain in her lab focuses on the effects of artificial intelligence on work processes. "In one study, we examine the effects of utilizing AI among doctors and patients in a medical work environment. AI can help with medical diagnostics, but we need new approaches for the successful implementation of the AI’s recommendations in various work environments. In a recently published follow-up study, we developed a recommendation system for optimal adoption of AI in the healthcare sector. It won an outstanding research award at the Academy of Management Conference held in Chicago in August 2024."

New ways to manage work processes

The lab’s third research domain investigates the massive changes to new work processes. In recent years, Dr. Chalutz-Ben Gal and her colleagues have been busy examining the rapidly changing job market. She says that the COVID-19 amplified these tides and exponentially accelerated processes. "These changes bring a huge rise in gig work - people who serve as external workforce.. Additionally, the market has partially turned to a remote or hybrid work model, alongside flexible work, which completely changed everything. The result is dismantling classic work processes and projects into ones that rely primarily on skills. In the past, companies put great effort into matching people with positions to meet the organization's needs and culture; a “one-to-one” candidate-to-job model. Now, however, the need to manage distributed process (“many-to-many”), where different portions of one job are conducted by different people, is growing – in order to offer a flexible response to new technologies and rapidly changing skills in dynamic work environments," she stresses. "As a result, managers must ensure that at any given moment, the organization has at its disposal a skillset that will allow it to handle a myriad of varying challenges in an environment that is harder to manage on a daily basis. Some of these skills, such as coding, will be held onto forever. Others can be on an ad-hoc basis, per project. This research was published last year in the prestigious Academy of Management Perspectives journal, and opened a door to a series of empirical studies we are currently conducting in the lab. In one of these studies, we are building a mathematical programming model (Integer Programming) that aims to examine an optimal mix of 'hard' and 'soft' skills for engineers, in order to quantify and prove that managing a skill-based work process is far more efficient than recruiting full-time engineers."

When she's not researching or teaching, Dr. Chalutz-Ben Gal likes hiking. She proudly shares that she has completed the entire “Israel Trail”, utilizing the very same format that she believes characterizes the new work process – in segments. "I couldn't walk the entire trail in one go, because I have three children, so I hiked a different segment each time. For each segment, I invited family members and friends to join. Some I hiked completely alone, some I ran with my dog, and in some, I thought about research ideas.. It took me three years to complete, partly because of COVID-19. I finished last year, on top of “Mount Tzfachot” in Eilat, surrounded by family and friends; this was a very special moment."

In much the same manner in which she looked for different partners for her journey across The Israel Trail, she is now looking for partners to join her research path. "I'm looking for graduate and doctoral students who are curious, highly motivated, and mathematically-orientated, who want to be part of the future of the People Analytics field and collaborate with leading research groups worldwide," she concludes. Sounds interesting? Reach out to Dr. Chalutz-Ben Gal at hila.chalutz@biu.ac.il.