Analytical skills are becoming a crucial job requirement for HR as organizations strive to become more data-driven. Unfortunately, there is a shortage of analytical talent to meet this need. Less than 20% of companies identify as having a strong HR analytics function in their business, and over 75% of HR professionals reported difficulty recruiting for essential data analysis positions. To remain competitive, organizations need to rapidly upskill their HR talent. In this course students will develop and sharpen HR analytics skills as they analyze and visualize data to inform recommendations and decisions.
Drawing on his experience and research, John Hausknecht, Professor of HR Studies at Cornell's ILR School, guides students through key steps in identifying insights from HR data and analysis. Students will review HR data, identify key questions that drive the analytical process, and explore basic calculations for correlation and regression. Taking this a step further, students will mindfully interpret findings, looking beyond data as they take a holistic view of the situations they encounter. Through a course project, students will compose a presentation to visualize essential HR data and communicate findings to key decision makers.
This course does not assume students have prior analytical training or knowledge, nor does it require access to current HR data or metrics. Using Excel and datasets provided, this program equips students with the concepts, tools, and language to start their journey in HR analytics.
More than ever, HR leaders are expected to be proficient in the use of HR data and analytics. However, figuring out where to start with analytics, how to evaluate and critique HR data, and how to best communicate and translate results to the broader organization remain key challenges.
This course focuses on building analytical acumen and taking a strategic view of talent analytics. Using a framework presented in this course, students will examine outcomes and drivers throughout an organization to assess strategic needs. As they complete activities throughout the course, they will also fine tune their evaluative, presentation, and communication skills using critical thinking coupled with analytical best practices shared by Professor Hausknecht.
This course is designed for HR professionals who want to build their organization’s HR analytics capabilities, derive meaning from metrics and results, and tell persuasive stories involving HR and organizational data. With these skills, students will have a stronger voice in using talent analytics to persuade others toward actions that best align with organizational goals.
As organizations strive to succeed in a continuously evolving world, talent must be continuously assessed and evaluated to ensure alignment with strategic goals. It is no longer acceptable to serve in a consultant capacity on problems that arise or to offer strategic advice based solely on experience and policy. Today, HR teams must partner with senior leadership in driving effective and efficient change based on solid data and analysis.
Predictive analytics help organizations anticipate and plan appropriately for the future. In this course, learners will apply rigorous measurement and analysis techniques to common HR areas involving hiring top talent, evaluating workforce diversity, engaging the workforce, and managing retention. Through activities and assignments, learners will explore foundational frameworks that are relevant to analyses ranging from basic descriptions to more advanced predictive models that involve machine learning, artificial intelligence, or big data. As learners examine key inputs and data sources, they will use data to predict patterns and trends in areas such as diversity, engagement, and performance. Ultimately, students will use metrics and analytics to assess the current talent landscape of an organization and outline recommendations as they create a presentation for senior leadership.
This course assumes a basic comfort level in working with HR data and analysis. It is designed to equip students with the concepts, tools, and language specific to key areas within HR analytics. The course provides examples using Excel. Other data analytics software will not be presented, although the information shared is transferable for those fluent in other programs.
The need to justify spending and the use of resources applies as much to talent as it does to business in general. With that in mind, how can HR professionals show the return on investment in human resource programs? In this course, learners will walk through the steps involved in conducting a credible return on investment (ROI) analysis and will be provided strategies for overcoming common ROI challenges such as isolating the impact of a program and converting the benefits of a program to a monetary value. This course also goes beyond the steps involved in calculating ROI – it provides learners with a framework to decide when ROI makes sense (and when it does not) as well as tools for planning a successful ROI and effectively communicating the results to key stakeholders.
This course does not assume learners have a data analytics background but does assume learners possess basic exposure to HR analytics (from experience or a prior course such as Applied Predictive Analytics in HR).