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.
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: digital technology, Machine Learning and Cognitive Computing, Human Capital Management, HRMS, Learning Management, Payroll Optimization, Total Compensation Management, Work and Resource Management, Workforce Management, employee experience
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: Analytics, Business Intelligence, Cloud Computing, Collaboration, data science, Big Data, Machine Learning, Workforce Optimization, digital technology, Human Capital Management, HRMS, Learning Management, Workforce Management
I’m thrilled to announce to my HCM vendor and practitioner network as well as the ever-expanding Ventana Research community that I’m now directing Ventana’s HCM practice. I will be working closely with our CEO and Chief Research Officer Mark Smith, who is a fellow HCM enthusiast and thought leader.
Topics: Analytics, Cloud Computing, Collaboration, data science, Internet of Things, Mobile, Big Data, Machine Learning, Customer Digital Technology, Human Capital Management, HRMS, Learning Management, Payroll Optimization, Workforce Management
In 2016 Unit4 acquired Prevero, a financial performance management software company. The acquisition reflects a trend toward the convergence of transactional and analytical business applications. ERP and financial management software vendors increasingly are adding analytic capabilities – especially in financial performance management (FPM) – to the core functions of transaction processing and accounting in order to broaden the scope of their offerings. The integration of transaction processing and analytical software is especially valuable to Unit4’s core customer base of midsize organizations, which we define as those with 100 to 1,000 employees. Midsize entities have almost the same systems requirements as larger ones but lack the resources the latter enjoy.
Topics: Analytics, Business Intelligence, Cloud Computing, Collaboration, Workforce Management, Marketing, Office of Finance, Continuous Planning, Financial Performance Management, FPM, Operations & Supply Chain, Work and Resource Management, Sales Planning and Analytics