Guest blog post by Mark Doms, Under Secretary for Economic Affairs
“Better Data for Better Decisions” is my mantra as I crisscross the country talking to people about making the data we collect easier to find, understand and use. Making government data more accessible or “open” to improve government, business and community decisions is a major initiative in the Commerce Department’s “Open for Business Agenda.” The open data initiative has the potential to fuel new businesses, create new jobs and help us make better policy decisions.
One of our best data sources is the U.S. Census Bureau’s American Community Survey (ACS). The ACS is truly a unique, national treasure, producing a wealth of data on which our country relies to make important decisions. The ACS is used to inform disbursement of over $400 billion a year in Federal funds. State and local decision makers rely on the ACS information to guide tough choices about competing funding priorities, such as locating hospitals, funding programs for children, building roads and transportation systems, targeting first responders, supporting veterans, locating schools, and promoting economic development. In short, our community leaders use ACS data to analyze how the needs of our neighborhoods are evolving. And, our business users rely on ACS data to make key marketing, location and financial decisions to serve customers and create jobs.
The value of the ACS is immense. It makes our businesses more competitive, our governments smarter, and our citizens more informed.
This value comes from the fact that the ACS captures so much information so comprehensively. But, this also means that the value of the ACS depends critically on the people responding to the survey, known as the respondents. I met recently with members of the ACS Data Users Group, an organization dedicated to sharing innovations and best practices for ACS data use, to discuss how to get the best quality data with the least amount of respondent burden. This is of paramount importance. A survey seen as too lengthy, burdensome and intrusive will produce lower response rates and could undermine both the quality of the data and value of the survey. But reducing the length of the survey could reduce the amount of information available for decision-making.