WHO IS PAWS - As the city's largest animal rescue partner and no-kill animal shelter, PAWS is working to make Philadelphia a place where every healthy and treatable pet is guaranteed a home. Since inception over 10 years ago, PAWS has rescued and placed 27,000+ animals in adoptive and foster homes, and has worked to prevent pet homelessness by providing 86,000+ low-cost spay/neuter services and affordable vet care to 227,000+ clinic patients. Just in 2018, 3,584 animals were rescued and 36,871 clinic patients were served. PAWS is funded 100% through donations, with 91 cents of every dollar collected going directly to the animals. Therefore, PAWS' rescue work (including 3 shelters and all rescue and animal care programs), administration and development efforts are coordinated by only about 70 staff members complemented by over 1500 volunteers.
DATA IS UNDERUTILIZED - Through this chain of operational and service activities, PAWS accumulates data regarding donations, adoptions, fosters, volunteers, merchandise sales, event attendees (to name a few), each in their own system and/or manual (Google Sheet) tally. This vital data that can drive insights remains siloed and is usually difficult to extract, manipulate, and analyze. Taking all of this data, making is readily available, and drawing inferences through analysis can drive many benefits: PAWS operations can be better informed and use data-driven decisions to guide programs and maximize effectiveness; supporters can be further engaged by suggesting additional opportunities for involvement based upon pattern analysis; multi-dimensional supporters can be consistently (and accurately) acknowledged for all the ways they support PAWS (i.e. a volunteer who donates and also fosters kittens), not to mention opportunities to further tap the potential of these enthusiastic supporters. And there are bound to be more leverage points as we get further into this project!
PROJECT MISSION - This project seeks to provide PAWS with an easy-to-use and easy-to-support tool to extract data from multiple source systems, confirm accuracy and appropriateness and process data where necessary (a data hygiene and wrangling step), and then load relevant data into one or more repositories to facilitate (1) a highly-accurate and rich 360-degree view of PAWS constituents (Salesforce is a likely candidate target system; already in use at PAWS) and (2) flexible ongoing data analysis and insights discovery (e.g. a data warehouse).
Want to join this project? Introduce yourself in the #paws_data_pipeline Slack channel.