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Sheetal Singh

Sheetal Singh (@multi_tude) is Senior Director of Global Media at TechSoup Global. In this position, she oversees the content and community activities of the TechSoup and NetSquared programs and is responsible for the media strategy for the TechSoup Global Network.

Making Data An Afterthought

26 Mar, 2013

afterthoughtFast forward to a social sector in which the data practices we are currently imagining are implicit in both our day-to-day activities and in the strategic underpinnings of our work. Sheetal Singh (@multi_tude), Senior Director of Global Media at TechSoup Global provides a case study that looks into that future and suggests a way to get there.

Social sector data is most meaningful when it is collected and shared en masse. We can probably all agree on this point. What is more difficult to come to terms with is how to collect that data.

Often, the most useful data around social problems is “potential data”: data that that is currently not being collected or considered. It is what we don’t know, but easily could. Consider the challenges of domestic violence (DV) agencies.

Many agencies operate emergency shelters for DV victims, and very often, they receive more requests for shelter than they are able to accommodate. According to the National Network to End Domestic Violence’s 2011 Domestic Violence Counts California State Summary, on a single day, September 15, 2011, 5,363 individuals were served by DV agencies in California. But on that same day, there were 924 unmet requests. 612 of those requests were for emergency shelter.

How many people did those 612 requests represent and why were they turned away? We don’t know. We can assume most were turned away because of a lack of shelter space or lack of funds for hotel rooms. But some may have been turned away because they did not fit the criteria for a particular shelter. For example, some shelters don’t accept male children over a certain age or don’t accept clients who are substance abusers.

Each individual agency is probably tracking unmet service requests and can use that information to adjust their own service provision to better meet the needs of victims. But if every agency in California shared that information, we would have a greater body of evidence and a state-wide view of the problem, which could be used to advocate for funding streams and policy change.

So, how do we get the agencies to share that aggregate information? At TechSoup, we have been working with the DV agencies for over 10 years, helping them to better use technology and data to serve their clients. When it came to data and data sharing, which is sensitive for DV agencies because of privacy issues, we initially went the route of education. We ran training sessions and published papers espousing data collection and analysis. Our advice fell on deaf ears. Then we tried a different approach.

We realized that when you are working with small organizations in constant crisis mode, thinking about data is a luxury. If we wanted the agencies to track and share data, we needed to give them a really good reason to do so. And we think we found it by helping them meet their most pressing needs.

Safe Night is a mobile service (currently in development) that will allow DV agencies to crowdsource funding for emergency shelter in local hotels when they don’t have space available for a client. Rather than turning the client away, the agencies could use Safe Night to send a message out to their supporters requesting a donation to put the client (and any children she might have with her) in a hotel room for the night. In the process, the agency would be required to log data on the clients they are trying to place, including the number of individuals and the reason they were denied a space in the shelter in the first place. Safe Night will serve as a repository for this data, and TechSoup will use the data to work with the DV sector to analyze and improve the services that the agencies provide, making sure that clients’ needs are met, and the agencies’ resources are used efficiently and effectively.

Safe Night is being built upon the premise that really useful services or applications are the key to the social sector’s adoption of better data collection and sharing practices. Take Flickr, for example. Flickr is a massive repository of data. It contains human-supplied data on images (all those tags) and machine-supplied data on the location, date the image was shot, and the type of camera used. But no one uses Flickr because they want to contribute data. They use it because it makes photo sharing easy. In the process, they have created an incredibly large and useful global dataset.

Is the lure of being able to serve clients even when they don’t have the systemic resources (those received through government and foundation funding) to meet their pressing needs enough to make DV agencies collect and share data on those clients?

It remains to be seen. If Safe Night is successful, it will provide a valuable lesson: the best way to incentivize social sector data sharing is to give organizations services that are so useful, the data is an afterthought.

Marnie Webb, CEO of Caravan, a division of TechSoup Global, contributed to this post. Safe Night is a project of Caravan.

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5 Comments

  1. avatar
    Nikon Rasumov
    March 27, 2013

    Very cool project! Are there numbers available already to see how well this worked, or is it too early to tell? I also like the personalized approach by matching individual grantees to donors – a bit like watsi.org.

  2. avatar
    David Bank
    March 27, 2013

    This is a terrific post and project and a great example of the way attractive and useful apps can ‘pull’ in new data more quickly and cost-effectively than brute-force scraping or constant nagging!

  3. avatar
    Sheetal Singh
    March 29, 2013

    Thanks Niko! Safe NIght is still in development, so too soon to tell. But we will definitely be reporting out once we have some numbers to share.

  4. avatar
    George McCully
    April 04, 2013

    Sheetal’s excellent report highlights the value of establishing a systematic, rigorously defined, taxonomy of fields of philanthropy, as a sine qua non for users’ finding complete lists of all the organizations working in any given field, in a designated region. If all the organizations in a field know who the others are, there will be a strong conducive pressure to pool resources and collaborate for superior service delivery. The chaotic and fragmented state of field data today impedes collaboration.

  5. avatar
    April 17, 2013

    [...] Horin, Founder (Data Points and Data Agents) and Sheetal Singh, Senior Director of Global Media (Making Data An Afterthought). Now, on to [...]

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