Shelter’s Edge

Dirty, dirty data… We can get there many different ways – from sloppy data entry, poor spelling and more… The dirtiest data, I would argue, is the data that is entered intentionally – that is, with the wrong intentions.

An example may help to clarify. There have recently been some great conversations on the SAWA list-serv about pit-type dogs. The discussion focused on how cautious we should be of labeling them if we do not know their real heritage. Suggestions included using a generic mix-breed label for them. That is a great intention – but is not data- and risk-intentional. We know that in many agencies, dogs who appear to have bully-type breeds in their mix (whether they actually do or not) tend to be at higher risk than those without. If we cannot accurately track where those animals are coming from, and what happens to them when they are in our shelters, how can we measure the impact of program designed to support them?

Another common one we run into is the coding of cats as “owned” by some arbitrary number of days they are fed by a Good Samaritan who considers the cat a stray. While I understand some city ordinances state if a cat is fed X number of days he is owned – and I understand that some of those who work in shelters identify feeding as ownership – from our perspective, we can miss some important data by coding these cats as owned. Imagine I want to develop an intervention to provide spay/neuter for owners in a particular area. I flood the area with information about the spay/neuter services we can provide for their cats – but we’d be completely missing those that are just feeding cats they consider stray, as they do not consider themselves the “owner.”

Sometimes data is coded a certain way to get around a local ordinance or simply to get around a shelter software issue. We have found some dirty data where shelters “push” though a low-cost spay/neuter of a public animal by coding the animal as an intake and then out as an adoption at the end of the surgery day! As you can imagine, this can be an issue when looking at impact of spay/neuter on intake…

What is the intention with your data entry? What are you using your data for? If it is to track progress and impact, as well as your ROI – are you sure that is how your data is entered? It may be time to check…

Resources on naked data:
Shelter Data 101: What, why and how to collect
Basic Data Matrix
Naked Data posts on ASPCA Shelters’ Edge blog

Tags: Intake, Research, Research & Data, Saving Lives, Shelter Health

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