The Importance of Good Data Collection 

by Abe Lee

I love statistics. Wait. I'm not that nerdy. Let me clarify – I love the impact good statistics can have. Whether it's on policy or evidence-based practice, good data collected well from a large pool and analyzed with care can do amazing things. At least that is the assumption. But this week's blog post won't go into the details of the power of good data analysis based on good data collection. I want to focus rather on the truth that good data analysis needs good data collection.

A recent post by Mathematica Policy Research emphasized the effectiveness of small community-based programs in addressing adverse childhood experiences (ACEs) in young persons and adults. For example, a "Positive Social Norms" campaign (short duration media campaign) decreased alcohol use among youth by 10%. Looking at a report like this – focused on policy & practice implications based on evidence garnered from good data collection – made me think about one aspect of service delivery. While attending George Warren Brown (GWB) School of Social Work at Washington University, my master's thesis evaluated the effectiveness of using a local public school in a low-income neighborhood as a hub of social welfare services (a "no wrong door model") in the early 90's. The hardest part of the entire project wasn't formulating the hypothesis or writing up the questions or getting a random model sampling… it was getting responses. The constant struggle of any research is getting enough responses to make any study valid.

I'll tell you that technology has made that process SO much easier. Google Forms and Survey Monkey are my two "go to" services when it comes to conducting surveys today. They are extremely easy to configure, excellent to look at on a mobile device, easy to propagate through multiple methods (e.g. SMS, email, social media, etc.), and Survey Monkey even has an app to manage and execute the surveys. It allows me to get to the data I've collected on the cloud and extract it as necessary into statistical analysis tools as required.

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Though it is true that when you get a large enough sample size, the law of diminishing returns has proven that you don't need as many responses, but you still need to get a minimum number of responses. And for not-for-profit (NFP) organizations, public entities… any organization that is attempting to focus its available resources and funds on effective programs and proven treatments, surveys and data analysis are key.

#UsefulTech needs to focus on known areas of need. Financially frugal organizations need to funnel their existing funds as efficiently as possible, identifying proven programs. Surveys, using mobile tools to collect data that can be crunched, is one of the best ways to do just that. Providing a method to capture information from a client from within their self-service app… using notifications to ask "what do you think?"… pre-populating key demographics (or capture key demographics) via a survey tool in the self-service solution to get a better picture of the organization's client population. All these would ultimately be a benefit for both the client and the agency.

Many HHS agencies have already become deeply involved with good data collection, and analysis. These agencies have identified the biggest issues facing society, the people who need the most help, and some are even as far along the way as generating possible solutions. The next big step in the process is knowing where to begin a project. Mobility solution projects can be especially daunting as this is a technology that a lot of HHS agencies have not worked with before. Some agencies try to build their own in-house solutions (to their detriment), some look for vendors, and some stay in limbo. The question is; what stage is your HHS agency at, and how can you speed up the process?