Using R, the Tidyverse, H2O, and Shiny to reduce employee attrition

An organization that loses 200 high-performing employees per year has a lost productivity cost of about $15M/year. This cost is massive, yet many organizations don’t know it exists.

Using R, the Tidyverse, H2O, and Shiny to reduce employee attrition

January 25, 2019

An organization that loses 200 high-performing employees per year has a lost productivity cost of about $15M/year. This cost is massive, yet many organizations don’t know it exists. It doesn’t show up on a financial statement. Therefore, it goes unnoticed. This presentation showcases how several open source tools integrate to form a solution to the employee attrition problem. Specifically: (1) How the Tidyverse enables problem identification through visualization. (2) How recipes + H2O can be combined to explain key relationships to attrition and predict employee attrition. (3) How Shiny can be used to create a powerful dashboard that empowers business leaders to make data-driven decisions across the organization.


About the speaker

Matt Dancho

Matt Dancho is the founder of Business Science (www.business-science.io), a consulting firm that assists organizations in applying data science to business applications. He is the creator of R packages tidyquant and timetk and has been working with data science for business and financial analysis since 2011. Matt holds master’s degrees in business and engineering and has extensive experience in business intelligence, data mining, time series analysis, statistics, and machine learning.