The practical applications of clustering are vast. With the ability to identify groups in the data based on their shared characteristics, future customers, employees and stakeholders can be marketed and delivered products and services that are most likely to be pertinent to their specific needs.
Posts By Matthew Albucher
A national conversation is continuing to brew over whether Science, Technology, Engineering, and Math (STEM) skills should be emphasized in schools and universities over humanities and liberal arts education. Several recent studies have found that the perceived higher marketplace value of STEM skills has led to a drop in the percentage of students pursuing humanitiesRead… Read more »
Data visualization software can help data analysts more efficiently distill and communicate pertinent information to their customers. Likewise, the customization available in many data visualization packages enables consumers of data to more easily obtain and sort through the information they need. In a previous blog post, I explored how the U.S. General Services Administration isRead… Read more »
At the U.S. General Services Administration, analysts in the agency’s Human Capital Analytics Division have leveraged data visualization technology to create a dynamic, highly customizable internal HR data dashboard
Maintaining a diverse federal workforce and eliminating barriers to equal employment opportunity are not only required practices for federal agencies under the Equal Employment Opportunity Commission’s Management Directive 715, but are also crucial to encouraging a more effective and creative workforce with less internal strife. The private sector is now investing heavily in diversity programsRead… Read more »
Federal HR professionals with access to electronic employee databases typically have access to a wealth of so-called “structured” employee data, or information that can be quickly counted and analyzed in spreadsheet programs to create pivot tables and reports. Examples of structured HR data include employee salary and demographic information and employee survey responses, all ofRead… Read more »
Last week, I explored how federal agencies can use HR data to build predictive models to evaluate and reduce costly employee turnover. An article published in Business Insider this month described how HR software company Workday built an app to help employers do just that. Workday claims its software can not only predict who isRead… Read more »
Using a regression model is not only useful for diagnosing employee turnover in the present, but also can help predict who is likely to leave in the future.
HR professionals can use employee opinions to predict real employment outcomes, and directly compare survey responses with HR data to verify how perceptions manifest in reality.