Skip to main content

In this HR Resources Post, we’ve created a YouTube tutorial which supplements the vLookUp tutorial we did earlier.  The single largest complaint I hear about vLookUps is the N/A ‘error’ which is returned when no data is present to be matched through the vLookup formula.  The IFERROR is a formatting formula, designed to return a blank (or a desired term determined by the excel user).  So if this is an issue you encounter when showing your spreadsheets to colleagues and/or end-users, take a look I’m sure you’ll find this formula helpful.

Brendan Lys
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.