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, Work and Resource Management, Machine Learning and Cognitive Computing, Payroll Optimization, Artificial intelligence, Total Compensation Management, RPA, employee experience, Chatbots, Personalization, Predictive HCM
Recent advances in workforce management (WFM) software are rewriting the way organizations tackle hourly workforce management and related administrative challenges. This is largely due to improvements in the design of business processes and a focus on enabling more hassle-free user experiences. The result is fundamental changes in how workers account for their time and request PTO, as well as how they access information on payroll, benefits and other company policies. These advances are also enabling managers to more readily consider workers’ as well as the organization’s needs when they forecast and schedule shifts. Scheduling that minimizes worker burnout from too many double shifts, for example, only makes management sense and should be a common interest.