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: digital technology, Machine Learning and Cognitive Computing, Human Capital Management, HRMS, Learning Management, Work and Resource Management, Workforce Management, employee experience, Artificial intelligence, Chatbots, Personalization, Predictive HCM
This year, Teradata rebranded the Teradata users conference from "Partners" to "Analytics Universe", and there is a reason for it. For decades, Teradata has represented the high end of the analytic database, but new innovations and technologies are adding flexibility to Teradata's licensing as they compete. For the full breakdown of Teradata's Analytics Universe 2018, and my analysis of all the largest announcements, watch my hot take video.
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: digital technology, Machine Learning and Cognitive Computing, Human Capital Management, HRMS, Payroll Optimization, Total Compensation Management, Work and Resource Management, Workforce Management, employee experience, Artificial intelligence, RPA, Chatbots, Personalization, Predictive HCM
Dreamforce has become the largest enterprise software event for businesses in the United States, and it is evident why when looking at it this year. With over 170,000 business and IT professionals attending, Salesforce came to show off upcoming product announcements and innovations. This year's biggest focus was on Einstein Voice (a personalized and intelligent conversational assistant), integration with other platforms, and Salesforce Customer 360. The last of these is the start of an answer to a problem we have well documented; businesses struggle getting a full view of the customer and provide a frictionless response to issues and interactions. For the full breakdown of Dreamforce 2018, and my analysis of all the largest announcements, watch my hot take video.
Topics: Customer Experience, digital technology, Digital Marketing, Marketing, Voice of the Customer, AI, Machine Learning, natural language processing, SPM, Sales Performance Management, Robotic Process Automation, CRM, Salesforce.com, Dreamforce
In 2017 Strata + Hadoop World was changed to the Strata Data Conference. As I pointed out in my coverage of last year’s event, the focus was largely on machine learning and artificial intelligence (AI). That theme continued this year, but my impression of the event was of a community looking to get value out of data regardless of the technology being used to manage that data. The change was subtle: The location was the same; the exhibitors were largely the same; attendance was similar this year and last. But there was no particular vendor or technology dominating the event.
Topics: Analytics, Business Intelligence, data science, Big Data, Data Integration, Data Governance, Data Preparation, Information Optimization, Machine Learning, digital technology, Machine Learning and Cognitive Computing