Looking Forward: Data Collection and Releases

This is final part of a blog series where Kauffman Foundation Research Director E.J. Reedy interviews Ron Jarmin, Assistant Director of Research and Methodology at the U.S. Census Bureau, to learn more about how Census is continuing to create new, innovative data resources and about some of its work as a partner with the newly created Institute for Research on Innovation and Science at the University of Michigan.

Read part one on Institute for Research on Innovation and Science.

Read part two on Finding More Timely Economic Statistics. 

Read part three on Big Data and National Statistical Agencies.

Part 4: Looking Forward: Data Collection and Releases

Q (Reedy):            Any other ideas, anything you think should be done or could be done to encourage more timely data collection and releases more broadly? Or foster that kind of nascent community within the statistical infrastructure that’s incorporating new data use techniques?

A (Jarmin):             The research agenda that we’ve laid out kind of has four broad areas that need to be tackled and I think people need to recognize that lots of things need to be done.

First and foremost, obviously, is methodological. And we kind of touched on that before. We can now easily mash up information from all these different sources. How do you know the quality of that information and the reliability of that information once you’re done? So I think we need some work on the methodology side. The second is computational. Obviously, we’re talking about much larger quantities of data, trying to process it much quicker. How do we do that and still maintain the security of the information? Third, and perhaps just as important, is we need to start figuring out some of the policy, privacy, legal ramifications of moving to a more big data statistical infrastructure. For example, the Census Bureau produces data on commuting patterns. You could use cell phone telemetry data to produce really good commuting pattern data, but I don’t think that the public is at a point where they would want cell phone telemetry data used for that purpose. There’s what’s possible given technology, and then there’s what people are comfortable with. And so what we have to be able to figure out, what’s the optimal place in that continuum where we can use the new data-rich world to construct timely and informative data products using methods that people are comfortable with. Fourth, and this is related to maybe all of these other things, is that you’re going to have to be able to convince users that these sort of new data products that are produced in new ways are informative and trustworthy. Data users can be very conservative folks, and they’re going to want the data the way they used to get it, even though they complained about that data being inadequate. But if you give them something different, how do we help them understand it so they feel confident using it for decision-making? So these are all huge challenges that I think anyone working in economic or social measurement over the next couple of decades is going to have to struggle with regarding how to adopt new methods and new sources of information to provide better information to public and decision-makers.

Q:            And I have to believe that probably one of the leading places to start is going to actually be the information that’s focused more on businesses? Do you feel that’s accurate?

A:             That is a strategy we’re employing right now for a number of reasons. I think there are fewer issues on the privacy policy front, but I think we also hope that businesses will be more of a partner with us as we’re doing this. So this is one of the aspects of the IRIS-IMI project that we really are trying to learn from, and so we want the people that provide us the data, whether it be businesses or individuals, to see the value that they get from participating in our data collection activities. And so, like in the IRIS-IMI project, we’re providing value-added products back to the universities that they appreciate, and it encourages them to be more willing to participate. We hope to do the same thing with businesses, be able to provide benchmarking reports or something that the businesses would find value in that would encourage their participation. So very much we would be treating them as a partner, and I think that’s going to be easier to do on the business side than the household side. Businesses obviously have a profit motive and they want to grow their business. And I think if we can help provide them information that they can use in making their day-to-day business decisions that would encourage them to participate with us. It’s a little harder to think of what we would do on the household side in that type of scenario.

Q:            Do you think some of the initiatives that you are describing are best done just with the biggest companies and the biggest areas of the economy?

A:             I would argue that what we’re describing isn’t necessarily focused on big, established firms. I mean, obviously, there are things that we can do in terms of automation with big, established companies that we might not be able to do with smaller companies. But I think there are things we can do with smaller companies, as well. I think that we want to find ways of using more modern data-collection techniques and processes, and to measure the entire economy and not just the big firms. So we’re very much interested in collecting more information. So I think what we’ve done with business dynamics wasn’t that we collected more information, it’s just that we looked at it in new ways and were able to shed light on some issues. And I think as we move forward with this, if we’re able to collect more information, and process it and analyze it in different ways, that the number of other new insights that we might get from this will be very large. At least that’s my anticipation. I’d be surprised if it wasn’t. So I think we hope to learn a lot about the economy by modernizing the statistical infrastructure that we use to measure it. 

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e.j. reedy data maven

E. J. Reedy

As a director in Research and Policy, E.J. Reedy oversees the Ewing Marion Kauffman Foundation’s research initiatives related to education, human capital development, and data.

Since joining the Kauffman Foundation in 2003, Reedy has been significantly involved in the coordination of the Foundation’s entrepreneurship and innovation data-related initiatives, including the Kauffman Firm Survey, for which he served as a principal investigator, and the Foundation’s multi-year series of symposiums on data, as well as many web-related projects and initiatives. He is a globally recognized expert in entrepreneurship and innovation measurement and has consulted for a variety of agencies.