It’s no secret that employees are overwhelmed. They’re having to use an array of systems and enterprise tools in the flow of work and deal with an explosion of email messages and other communications requiring some response or action and mountains of content to consume and retain. On top of these time demands, employees must try to keep up with a staggering amount of organizational change.
Roughly half of my more than 30-year career in human capital management was spent as a line manager responsible for HR technology strategy, selection and deployment. I learned a number of lessons during these years — some just in time, some after the fact. If I had to identify one common thread that unites these insights, it would be that inadequate attention to change management is an ROI-killer on these strategic initiatives every time.
Learning management technology, either as part of a larger HCM software suite or as a standalone niche solution, has evolved from its classroom-based, instructor-led origins. Modern systems deliver information the way many employees learn best, through informal social learning that is personalized and engaging. Some of these new, often mobile-enabled approaches deliver education via short (three to five minute) on-demand videos that are tailored to an individual’s specific job responsibilities or interests and increasingly involve artificial intelligence (AI) technology. AI’s role in this context is to better personalize learning content, modality and the pace of learning. In short, this is all about delivering learning the way each person learns best.
Topics: Human Capital Management, Learning Management, HRMS, Workforce Management, Digital Technology, Work and Resource Management, Machine Learning and Cognitive Computing, Artificial intelligence, employee experience, Chatbots, Personalization, Predictive HCM
The early days of my career were spent in HR and payroll systems inside brokerage houses and investment banks. The first CHRO I reported to thought the best way to develop a plan for automating payroll management was for me to run the function’s day-to-day operations. I had no previous experience in payroll but it was a good call, as the trenches of any operations area typically reveal a cornucopia of automation opportunities. Then again, it was a different time; back then the words strategy, decision support and employee experience were rarely heard in a payroll department.
Topics: Human Capital Management, HRMS, Workforce Management, Digital Technology, Machine Learning and Cognitive Computing, Payroll Optimization, Artificial intelligence, Total Compensation Management, RPA, employee experience, Chatbots, Personalization, Predictive HCM
Over the last two years, investments in digital technologies such as artificial intelligence (AI) by nearly every major provider of HCM systems and tools have transformed the HR technology landscape. Many of the investments have gone into developing distinctive product capabilities, particularly capabilities that rely on machine learning technology.
Topics: Human Capital Management, Learning Management, HRMS, Workforce Management, Digital Technology, Work and Resource Management, Machine Learning and Cognitive Computing, Payroll Optimization, Total Compensation Management, candidate engagement
Employee engagement has been a dominant theme in both human capital management (HCM) and the systems to manage it in recent years; lately (though not necessarily appropriately) it is a topic often equated with the notion of the employee experience. On a related point, Gallup’s annual employee engagement survey has consistently found the majority of today’s workforce to be disengaged, defined as “not enthusiastic or passionate about their work.” Interest in the degree to which HCM technology can improve employee engagement (or mitigate disengagement) now rivals the attention given to such perennial chief human resources officer (CHRO) concerns as attracting and retaining top talent and retooling the workforce.
Topics: Big Data, Data Science, Human Capital Management, Machine Learning, Learning Management, Analytics, Business Intelligence, Cloud Computing, Collaboration, HRMS, Workforce Management, Digital Technology, Workforce Optimization