The Roper Center for Public Opinion Research, located at Cornell University, is one of the world’s leading archives of social science data, specializing in data from public opinion surveys. The Center’s mission is to collect, preserve, and disseminate public opinion data; to serve as a resource to help improve the practice of survey research; and to broaden the understanding of public opinion through the use of survey data in the United States and abroad. Founded in 1947, the Roper Center holds data ranging from the 1930s, when survey research was in its infancy, to the present. Its collection now includes over 22,000 datasets and adds hundreds more each year. In total, the archive contains responses from millions of individuals on a vast range of topics. (Source: http://ropercenter.cornell.edu/about-the-center/)
When they came to DaizyLogik, the Roper Center was manually managing data distributed across several different systems and/or in the heads of members of the team. They had acquired Salesforce but sought assistance getting it up and running and getting their data into the system. They were starting their implementation to Salesforce from scratch. Since they wanted a system to manage membership and data contributions to their system, not donors, they decided not to use the Non-Profit Success Pack.
DaizyLogik worked with them to understand the key processes they were hoping to make more efficient – notably managing members who subscribe to the resources the Roper Center provides, and data providers who provide the data the Roper Center makes available. While neither involve large volumes of data, they do have some complex relationships and require management and updates in a timely fashion.
Managing Complex Relationships
The Roper Center receives data from a relatively small number of data providers. The data may be generated by the organization which provides it or by several organizations in collaboration, of which one usually is the primary data provider. Because data is provided on an on-going basis and participants in the collaboration sometimes change, the Roper Center must be cognizant of who those participants are so that it is possible to track down missing data, even if the primary provider of the data is no longer available. This requires the ability to track complex and changing relationships among organizations with whom the Roper Center interacts.
DaizyLogik worked with the Roper Center to articulate how the relationships among data providers works and to identify what information about those relationships is essential to allow the Roper Center to obtain the data it relies on efficiently. To ensure the Roper Center is able to track the shifting relationships among data providers, DaizyLogik built a set of custom objects using the Salesforce Lightning Interface. These objects allow for the flexible linking of data providers in collaborations as well as identification of the particular data sets each collaboration produces and the current active provider of each data set.
The Roper Center is a membership organization, and it’s vital that the team be able to effectively and efficiently track membership history and growth. Members may come and go, and sometimes return again, and the team wanted to be able to measure their membership metrics such as new member growth, loss rates, retention rates, etc. Effective membership tracking also required that the team pay attention to details such as post-expiration grace periods for renewal and business rules about how to count lapsed members who return, among others.
While it would have been possible to build a fully-automated solution to account for all of the business rules, DaizyLogik worked with the Roper Center to evaluate the relative value of that investment versus the cost of a more manual approach. Given the modest volume of data under management, we advised the Roper Center to use a more manual approach that still allows the Center to understand their membership history, identify membership gains and losses, evaluate retention, etc., but relies on the team to enter some additional data. Because the additional data entry occurs on, at most, an annual basis and for a relatively small amount of data, it requires minimal time from the team to do the additional data entry, and opting for the manual approach allowed them to redirect consulting time from our team to other priorities.