This used to be my favorite time of the year. As a writer, it was my perfect chance to get attention when the rest of the year was spent in oblivion. The performance review time of the year was a unique opportunity for every writer, budding writer, or aspirant to test their creativity by turning every strength into The Wall from Game of Thrones that keeps the white walkers away, and mitigating risk around their areas of development by dodging difficult conversations (during calibrations later) in ‘Matrix’ style! But Artificial Intelligence showed up and ruined it for all of us. Performance reviews are only a part of it though. There are so many aspects of human resource management where Artificial Intelligence and Machine Learning are leaving an indelible impression. Let’s find out more:
- Employee Advocacy – The vast amount of information shared on social media can tell a lot to organizations about their employees behavior, feelings, and loyalty towards their brand. Sentiment analysis of tweets, posts, and images reveals a lot about employee engagement and organizational values that are appreciated or underappreciated by employees. Another popular method is, of course, conducting surveys. Thought-through surveys can reveal data on most to least engaged employees even if it is anonymous. Several companies include psychometric analysis questions to make sure that recorded responses are credible.
- Gender Gap – Several companies talk about pay equality and diversity right from their senior leadership team to their support staff. But all the emails and memorandums are far from reality. Palatine Analytics founder, Archil Cheishvili, told Quartz, “Gender bias is a reality and it can only be eradicated when we show where it occurs and become conscious of it, then take steps to change our systems.” A Stanford University study 2016 on performance reviews revealed that performance reviews for men had clearer guidelines and feedback for improvement while women had feedback based more on their personality than actual achievements. The Great Learning Analytics Salary Study 2018, done in collaboration with Analytics India Magazine also reveals that women get 32% less salaries in the analytics industry. With the use of artificial intelligence and machine learning in performance reviews, it will be easier to close the gender gap when it comes to salary, or the positions that women hold in offices based on their skill set and experience.
- Employee Voice – In case of internal team issues or a tense relationship with manager, employees tend to keep it to themselves until it is too late. At the time of the exit interview, they choose to spill out whatever it is that bothered them till they were a part of the company. Artificial intelligence makes it possible for managers to track employee engagement, commitment to work, signs of leaving, etc. through behavioral analysis. The first obvious way is conducting surveys. But AI and machine learning now make it possible for companies to monitor emails and predict to higher accuracy if an employee is more likely to continue work or not. Immediate measures and conversations can then be held to talk to an employee before he or she takes any drastic steps.
- Performance Reviews – It won’t be long before machines start writing our performance reviews for us. A UK based company, WorkCompass is already using artificial intelligence and machine learning to analyze the quality of yearly or monthly goals of employees. They claim that their value-add has an average of 11.4% “increased employee productivity” for client companies. They make suggestions based on AI calculations in order to monitor performance throughout the year as opposed to twice a year with formal reviews. Complex hierarchical levels in an organization and reporting hassles (in case you report to two or more people for different aspects of your work) was once difficult to manage as cumulative feedback never covered all aspects of your job and employees would go dissatisfied with their review scores. Artificial intelligence makes it easy by assigning weightage to each of your goals and tasks and maps it with your performance all around the year.
- Rewards and Punishments – Not every employee likes to wait an entire year to hear that their manager recognizes their areas of strength and development. Neither do they appreciate if one employee keeps on getting all the recognition emails. A lot of discontentment arises from absence of recognition, challenging projects, adequate training, and feedback. Personalized packages instead of reward bands can also make a lot of difference. Natural Language Processing makes it possible for managers and HR to pinpoint areas of dissatisfaction and suggestions for course correction. Language is plagued with semantics, tone, context, and subtle nuances. As more accuracy is attained in NPL, it will be a game changer for managing human resources.
Any workplace is a dynamic environment and managing human resources is a continuous process right from recruitment to exit. But artificial intelligence and machine learning will soon eliminate the culture of ambiguity and anguish.1