A review of definitions, measures, and assessment tools of data literacy, and interpretation following the experience of educating and training HR professionals in People Analytics, to support the HR sector’s transformation to become a better client of data.
What should HR professionals expect when working with a data scientist? What should HR professionals do for a successful data science project? How should you deal with insignificant results in the analysis? The article addresses these questions.
The Employee lifetime value is a scheme that connects the people processes to the business outcomes. It refers to the expected value the organization gains in the entire time an employee in a particular role spends working, quantifying how “people are our most important asset.”
Whatever you do to educate yourselves, ensure that your learning opportunities include experiments with your own data. Master business questions in your organization and your own data, so you can build your company’s HR data strategy in the near future.
HR people can overcome their analytics barriers when they exercise. Online courses do offer a lot of exercises. However, only when HR people practice with real data, their own organizational data, they can bypass the obstacles.
This interview with an HR manager in a fireside chat during a People Analytics class offers an introspective approach to a joint journey, as a mentee and mentor: the motives, the obstacles, the quick win, the team participation, and more.
In a public talk, I challenged myself to describe the state of People Analytics in five sentences. Each point I made implies a myth. HR leaders should be aware of the following five misconceptions, or otherwise, continue to let these false ideas inhibit their advancement.
People Analytics and dashboards of HR Analytics deal with Performance. However, each practice has a different approach: Dashboards enable us to present KPIs, and to answer questions such as: Did we reach our goals? However, by using dashboards, we can’t answer the question: Why?