Are We Talking About The Same People?
Now you have the JSON representation of 20 employees and need to map them to the employees in your database.
Naturally, the approach you’ll choose will depend on the information you have available. Here are some suggestions for
matching up the employees in your database with the ones in ours. We recommend persisting the unique
that is returned by the Api, rather than redoing the match at the beginning of a pay period.
We provided email addresses with employee information specifically for matching employees between systems. For just under 75% companies on Gusto, every single employee has an email address available.
This assumes that employees provide the same email address to both systems, but for work applications this is by far the norm.
Date of Birth
Almost 98% of employees in the Gusto system have birthdays associated with them. Of those that do, ~81% have a unique birthday (comprised of year, month, and day).
Be careful when only comparing month and day, as it takes only 57 people to achieve a 99% probability of collision.
First and last name are required for employees in the Gusto system. Additionally, ~55% provide middle initials. If you can find an exact match based on full-name, then you’re finished.
Typos do happen, in which case checking the Hamming Distance can be helpful. If you have one unmatched set of employees with a Hamming Distance of 1, for example, it is pretty likely that they are the same person.