Animal Welfare Professionals

How Do You USE Your Data?

Hi there friends. As some of you may have heard, I tend toward the "numerical" side of things. With total support from Maddie's fund, two colleagues and I recently published a practical guidebook on the subject (shameless plug: Every Nose Counts: Using Metrics in Animal Shelters). We're now in the process of developing some more resources based on these ideas and we wan to get YOU involved. So here's the question:

We know that a lot of shelters/rescues collect data, but we want to know how you use this stuff. What metrics/data do you use at your shelter to help guide decisions? Do you have specific goals that you're working toward, and do you measure progress with data? Do you have a cool "data story"? (okay, I realize that "cool" and data may not necessarily mix, but you get the picture).

Whatever it is, I'd love to hear about it.

Thanks so much!!

We monitor  intakes, adoptions and outcomes monthly. We publish the adoptions and returns for all the staff and BOD to see. We continually look at return reasons to drive education on how to integrate a dog into the home, introduce to another dog and children. We also publish a monthly financial statement to the BOD and look at our budget to improve our financial standing. The metrics are also often a requirement for grants.

Whoever doesn't think data is cool is totally missing out. At our shelter we LOVE data! Our of our favorite things is when it proves us wrong. One year, several years ago, we thought our FIV adoptions were way up. Our FIV-positive cats were getting placed so quickly when we'd get them in. But at the end of the year our numbers were actually lower than the previous year. Because so many of our source shelters were having better success themselves with placing FIV+ cats, we weren't re-filling our FIV slots as quickly when our cats were getting adopted and we sometimes didn't have cats on our waiting list. So although our length of stay for those cats went down, adoption numbers decreased when we thought they'd increased. 

We look at and use more data than anyone wants to read about on a message board (except maybe you, Mike), but I'll share a few examples:

We just did an in-depth look at URI in our isolation wards with detailed reports that Shelter Buddy helped us create. That helped us understand some potentially high-impact areas we could focus on to reduce illness. For example, a disproportionate number of cats from two of our source shelters are starting treatment for URIs within the first 3-5 days after arrival. We take a lot of cats from both of these shelters, so it makes sense to try to work with them to reduce illness rates in their populations. We had already been planning to work with several of our source shelters this year, but had been thinking of other shelters. The data we looked at made it clear that work with these shelters would be better leveraged. 

We use trends in our public spay/neuter numbers to project numbers for the next year, including budgeting revenue and expenses and scheduling staff. (Demand for low-cost spay/neuter has been decreasing slightly each year over the past several years in our metro area since we hit what seems to have been a saturation point.) We also use data on what months are busiest for spay/neuter to schedule surgery days and figure out staff scheduling. Our schedule used to just be the same as the previous year and the same month-to-month. 

Last spring we started tracking our cat bites, including what was happening when the bite occurred. I was surprised that so (relatively) few of our bites occurred during veterinary treatment. Most of them bite when they're just being petted. The goal of tracking bite data is to best target safety training. 

Our management team reviews dozens of shelter statistics each week in our weekly meeting. We look for outliers, trends, and anything else that calls for our attention. Bi-monthly our board reviews another dashboard. Team members frequently call or pop-in on each other to talk about something we just discovered by running some report. We rarely make an even moderately significant decision without gathering and reflecting on data first. 

Three cheers for data!