Using Data To Recruit Better Candidates (Next Training Mar 28)

A few blog posts ago I mentioned 2 important recruitment analytics data points that can be used to help better understand attrition; distance to work and difficulty of commute. If a recruitment team has a way to use data on these two metrics in their screening process, they will be able to spend less time on high risk candidates and more time on candidates who have a much higher chance of sticking with the company.

It is not hard to start tracking these data points, as long as you have their home address, a general knowledge of traffic patterns and two very useful free  tools to help in your analysis. The free tools can be found at and

Based on the 50 Customer Care Analysts my team has hired for our 17 seat customer care team over the past 2.5 years, you can see some clear patterns when you look at their home addresses and commute on a map.

As you can see below, the majority of our candidates who turn into long term hires live closer to the office and along easier traffic routes. As a general rule, one direct ride (bus, train or shuttle) generally equates to stickiness of the candidate. Even some who live closer distance wise, but face multiple rides have a higher attrition rate than those who live a little further but have one ride. For example, taking a bus from the central part of Quezon City might be easier then 2-3 jeepney rides from Taugig, even though the distance from Taguig is much closer.


The map, created in Tableau Public, is generated on knowing the latitude and longitude of their home address (from their resume), which can be looked on using itouchmap. The whole project took less then 2 hours to compile, organize and upload the data into Tableau, then seconds to build the map.

During our first year as we hired people from a wider range of places we had much higher attrition (65%), but as we matured as a business along with our understanding of these and other key metrics, our attrition has dropped significantly in the past year (28%).

As elaborated on more in detail in previous posts, distance to work and difficulty of commute are not on their own data points to be used to screen candidates, but when combined with their interview scores, test and assessment results and reference checks, you can have a much more well-rounded view of the candidate’s potential.

If you would like some help us setting up this same process of capturing distance to work and difficulty of commute and building a map to visualize them, feel free to reach out to me. I have a book, this blog, lots of training materials and I speak about analytics frequently. I’m here to help.

Our next training is March 14 in Ortigas, click here to learn more >>>

HR & Recruitment Analytics – The recruitment and retention of top talent is the biggest challenge facing just about every organization. You really have to Think Through The Box to come up with winning solutions to effectively attract, retain and manage talent in the Philippines today.

DMAIPH is a leading expert in empowering HR & Recruitment teams with analytics techniques to optimize their talent acquisition and management processes. Contact DMAIPH now at or connect with me directly to learn how to get more analytics in your HR & Recruitment process so you can rise to the top in the ever quickening demand for top talent.


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