Skip to main content
Popular insights
Employee Scheduling Software HRMS For Small Business Employee Management Systems
Subscribe
Articles
1 min read

MS Excel 2010 CountIF Tutorial For HR Practitioners

By Brendan Lys
QUICK SUMMARY

In this HR Resources Post, we’ve created a YouTube clip explaining the CountIF formula and how it can be used with data sets and data questions typically encountered by Human Resource Practitioners. In brief, the CountIF formula allows you to count the number of times a specific condition is met within the data. In this video, we […]

Excel 2010 CountIF Tutorial For HR Practitioners

In this HR Resources Post, we’ve created a YouTube clip explaining the CountIF formula and how it can be used with data sets and data questions typically encountered by Human Resource Practitioners. In brief, the CountIF formula allows you to count the number of times a specific condition is met within the data. In this video, we use CountIF to count the number of employees at specific office locations, the number of employees who have gained a certificate, and finally the number of employees who have been paid above a certain dollar amount in wages.

By Brendan Lys

Operating at the intersection of Human Resources and Data Science, I leverage extensive specialist experience within Human Resources, with the methodologies and approaches of Data Science. This focus on the discovery of actionable insights from data, has been applied to areas such as: remuneration & benefits, workforce planning, recruitment, health & safety, diversity, and training. But what does the application of data science to HR challenges and opportunities actually look like. Within an HR framework the data we work with typically comes directly from our HRMIS, an advantage of using data science methodologies is that we can bring in additional data either held within the organization or from external sources - data which is out of reach from a pure HR analytics approach. Consider for example position descriptions, these contain a wealth of data that we typically ignore as its not in a analysis ready format. A side project I'm working on currently (April 2019) is using text mining on job descriptions to provide insights into which job family the position may fit into. The insights of my work have been enjoyed by organizations across a diversity of sectors including: Government (Australia and New Zealand), ASX and NZX listed companies, utilities, not for profit and higher education.

Follow the author: Opens new window Opens new window

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.

You may also like