As the city's largest animal rescue partner and no-kill animal shelter, the Philadelphia Animal Welfare Society (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. 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.
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, clean/validate 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 lake / data warehouse).
Through all of its 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 it 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.
This is a Code for Philly project operating under their code of conduct.
Goal: Create a central storage of data where
- Datasets from top 3 relevant sources can be uploaded as csvs to a central system: a) Donors, b) Volunteers, c) Adopters
- All datasets in the central system can be linked to each other on an ongoing basis
- Notifications can be sent out to relevant parties when inconsistencies need to be handled by a human
- Comprehensive report on a person’s interactions with PAWS can be pulled via a simple UI (must include full known history)
Goal: Expand above features to include all relevant datasets and further automate data uploads Datasets from all other relevant sources can be uploaded as csvs to a central system ( a) Adoption and Foster applicants, b) Foster Parents, c) Attendees, d) Clinic Clients e) Champions, f) Friends) Where APIs exist, create automated calls to those APIs to pull data
Goal: Create more customizable analytics reports and features (eg noshow rates in clinicHQ)