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
After more than a decade of steady development, ERP systems today are changing fundamentally, facilitated by the availability of advances such as cloud computing, advanced database architecture, collaboration, improved user-interface design, mobility, analytics and planning. This was evident when Oracle recently held its third analysts-only ERP Cloud Summit in New York to coincide with its Modern Finance Experience event. Oracle now has an increasingly robust set of business applications that reside in the cloud and a growing list of live customers – large and midsize – from a range of industries across the world, both of which were offered as part of the here-and-now technology theme at the event.
SAP recently held a teleconference to highlight its blockchain strategy. Lately, the major business software vendors have been calling attention to their blockchain initiatives. While the focus on this technology might seem premature to those who still equate it with cryptocurrencies, evidence is pointing to a future pace of adoption similar to the rapid take-up of the internet in the 1990s. That blockchain is useful for a wide range of business functions isn’t news – just google “blockchain use cases.” Payment, provenance, testament and efficiency are four main themes driving a multitude of applications of the technology. That said, blockchain isn’t technology in search of a mission but is something more like the internet, both in its broad utility and in value multiplication through network effects.
Robots of the physical sort are not about to take over finance and accounting but we have arrived at the age of “Robotic Finance”. I coined this term to focus on four key technologies with transformative capabilities: artificial intelligence and machine learning, robotic process automation, bots and natural language processing and blockchain distributed ledger technology. Embracing these technologies will enable any department to redefine itself as a forward-looking strategic partner to the rest of the company.
We at Ventana Research recently published our research agendas for 2018. Analytics and business intelligence are evolving and so is our research on their use across practice areas. Earlier research has shown that analytics can deliver significant value to organizations; for example, our predictive analytics research shows that 57 percent of organizations reported achieving a competitive advantage and half created new revenue opportunities with predictive analytics. Waves of investment in self-service analytics have propelled the market for analytics tools, significantly empowering line-of-business organizations to create their own analytics and set their own analytic priorities. But organizations are also beginning to recognize some of the limitations of current analytics implementations – for self-service, for example. Our Data Preparation Benchmark Research reveals that fewer than half (42%) of organizations are comfortable allowing business users to work with data not prepared by IT. Our research this year will continue to explore both the successes and challenges organizations face as they continue to use analytics and BI.
The Strata Data Conference is changing and it’s changing in a good way. At the recent Strata Data Conference in New York, Mike Olson, chief strategy officer at Cloudera, which co-sponsored the event, commented that at prior events we used to talk about the “Hadoop zoo animals,” meaning the various components of the Hadoop ecosystem of which I have written previously. Following last fall’s Strata event, I observed that the conference was evolving to focus on the use of data. Advancing that evolution, this year’s event focused on a particular type of usage: artificial intelligence (AI) and machine learning. The evolution from a focus on zoo animals to a focus on business value using advanced analytics shows further maturation of the big data market.
Fra Luca Pacioli, a 15th-century Franciscan friar living in what’s now Italy, is credited with codifying double-entry bookkeeping, which is the foundation of accounting. Pacioli, a polymath, was well acquainted with his contemporary and fellow polymath Leonardo Da Vinci. So, given they were at times collaborators, it’s fitting that one of the most important applications of SAP’s Leonardo technology will be in helping to disrupt finance and accounting organizations in corporations.