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Meet NASS Administrator Cynthia Clark

1 December 2011 3,420 views One Comment
Amstat News invited Cynthia Clark, director of the National Agricultural Statistics Service (NASS), to respond to the following questions so readers could learn more about her and the agency she leads. Look for other statistical agency head interviews in past and forthcoming issues.


Cynthia ClarkAn accomplished statistician, Cynthia Clark is highly respected for her expertise in survey research and development. Before joining NASS, she directed statistical research and survey methodology for the United Kingdom’s Office for National Statistics and the U.S. Census Bureau.


What have you enjoyed most about being head of NASS?

NASS is a great agency to lead. The agency has the best managers I have encountered in my career, in part because of its leadership training program and the career development opportunities available to NASS staff. Our staff is very customer-focused and has a “can do” attitude. It is very important for staff to be adaptive, responsive, dependable, and knowledgeable. It has been a great pleasure to work with the NASS staff.

I have thoroughly enjoyed the task of leading a statistical agency. I came to this position with experience in directing statistical and survey methodology research and managing survey programs in three organizations: the U.S. Census Bureau, NASS, and the UK Office for National Statistics. As part of the senior management of these agencies, I had observed all the functions of a national statistical office, but never bore the responsibility of integrating them. Through my experience in research, I became familiar with an extended range of statistical programs and the different issues each encountered. I also learned the following:

  • A statistical agency must rely on its data respondents
  • The agency’s data and publications must be carefully reviewed
  • It is important to communicate our methods and procedures to differently situated audiences
  • An agency must interact responsibly with its stakeholders
  • Effective data processing systems play a crucial role in our success
  • An effective and robust research program is essential
  • The pressing need for effective internal and external communication must be satisfied

I have thrived on the challenge of ensuring that these responsibilities are met.

Earlier in my career, I worked in agricultural statistics, but had not been involved in this sector during the past 12 years. Returning to the United States and agricultural statistics has been both daunting and exciting.

For the first time in my career experience, agriculture is at the center of many societal issues—feeding the world, ensuring a safe food supply, providing water for societal needs, promoting health and nutrition, caring for our environment, responding to climate change, maintaining an adequate supply of energy. I have found it stimulating to be involved in the effort to ensure that there is a statistically valid base for information and analysis relating to these issues. Because of NASS’s position in the research, economics, and education mission area within the U.S. Department of Agriculture (USDA), our agency is crucially involved in research and information efforts relating to all these issues.

What do you see as the biggest challenges for NASS, and have they changed significantly since you started this position?

Today’s biggest challenge for NASS is to stay relevant in a difficult budget environment. NASS took the equivalent of a 7% cut mid-year in fiscal year 2011 (FY11) and, based on the early House and Senate marks, we face shortfalls in FY12 as high as 12% for the agricultural estimating program—the largest component of the NASS budget—and the ramp-up of the Census of Agriculture. Operating under continuing resolutions with a high range of budget uncertainties makes it difficult to plan data collection activities that must take place early in the fiscal year. Such cuts are difficult for a government agency to take without eliminating programs and cutting the staff who administer those programs. The unprecedented current budget process has not allowed much stakeholder input into those decisions. Accordingly, we anticipate there will come to be numerous disappointed data users. In response to this process, NASS has identified what it considers its core programs, based on whether the program in question provides data for principal economic indicators, data that affects commodity markets, data necessary to implement USDA programs, and data publicly available from no other source.

Fast Facts
Reports to Under Secretary for Research Education and Economics in U.S. Department of Agriculture

Website: http://nass.usda.gov

FY11 Budget: $158.6 million

Staff Size: 1,050

In February 2009, NASS began a process to identify and implement five operational efficiencies in conjunction with an enhanced investment in research. The efficiencies we sought were designed to improve agricultural data quality, reduce cost of operations, create new NASS career opportunities, and position NASS to be the lead statistical data collection agency within USDA.

This supported the opening of a NASS National Operations Center (NOC) in St. Louis in October 2011. Statistical functions at the center include a 150-seat telephone calling unit, receipt of mail forms and associated digitization and data keying, development and maintenance of the NASS list frame, development and execution of interviewer training—both telephone and field—and receipt and processing in a laboratory of fruit (corn, wheat, soybeans, cotton) for objective measurement surveys.

To support the center, NASS initiated a large effort to redesign its operating systems to work in both a centralized and decentralized mode. It created a thin client network for all its offices such that all servers are now centralized and all desktop images are managed centrally. To facilitate complete digitization of its processes, NASS is implementing the use of Apple iPads with high-speed Wi-Fi for field data collection. The entire effort is being facilitated by newly installed videoconferencing equipment at each of the 46 NASS sites.

The recent opening of the NOC has resulted in disproportionate staff loss from our 46 field offices, as well as movement of functions from headquarters. That loss, in conjunction with large budget reductions, has forced the agency to consider realigning both its field office and headquarters staff. A proposal under discussion would implement a regional field office structure while maintaining one to two staff members in each state to maintain our effective federal-state cooperative partnerships and connect with the states’ agricultural infrastructure and their farmers and ranchers. Because of the immediacy of the 2012 Census of Agriculture, this realignment—though now begun—might not be fully implemented until the conclusion of the census of agriculture data collection and review process.

Describe your top two or three priorities for NASS.

My vision for NASS is to maintain its stature as the leading agricultural agency in the world as it positions itself to become USDA’s premier statistical agency. The vision entails improving agricultural data quality while reducing operational costs and enhancing career opportunities for staff. The efficiencies mentioned above directly contribute to improving NASS data quality by standardizing the data collection process, reducing the number of sites performing a given function, and streamlining each process.

The complimentary research agenda has focused on improvements to data collection methodology, automated and selective editing of data, and the estimation process. Needed improvements in the field procedures used for enumerating operations within a sampled area segment in the June Area Survey (JAS) were identified in a research project that compared 2007 JAS data with 2007 Census of Agriculture data.
The Statistics Canada BANFF editing program has been used to develop selective editing procedures. Bayesian hierarchical models have been developed to incorporate farmer crop reports, objective measurement surveys, weather, and precipitation information for crop yield forecasts. Small-area estimation models and a new probability-based survey design will provide higher-quality county crop estimates for area planted and harvested and production. Time series models using state-space methods have been developed to forecast livestock production using survey information and slaughter data. All these research efforts will enable NASS to be more transparent in the forecasts and estimates it provides to data users.

The agency has enhanced staff career opportunities by creating new positions in headquarters, in the NOC, and (we expect) in a new regional structure. A regional structure will allow more specialization of functions, thus increasing the depth of an individual’s knowledge. Additionally, NASS has pursued a project management certificate program for its staff and has numerous certified project managers. We could use more survey methodologists than we currently have. We also have formalized a quality management function in NASS.

What do you see as the role for the broader statistical community in supporting NASS?

In the past, most staff members have spent their entire career at NASS, beginning with 5–10 years in state field offices. When employees come to Washington, their focus has generally been on their work at NASS. They have not participated much in activities of the broader statistical community. I have been encouraging broader participation—in WSS seminars, in JSM and other conferences, as liaisons with other statistical offices, and in facilitating contacts. These opportunities have been enlightening to staff and have brought new ideas into the organization. NASS has hosted the Morris Hanson lecture for many years, bringing other statisticians into our building. All these activities and opportunities increase our vision and enable us to add value to our products.

What do you see as the biggest accomplishment of the agency during your tenure?

NASS will soon be in the position to do its business in a very different way. It will be structured differently than it has been during the past 40 years, and the work product of the agency will be recognized as transparent and statistically sound. We have tried hard to preserve the positive components of a statistical organization that was close to its respondents, users, and customers. This will continue to be a goal as NASS moves toward conducting its work within a new and more efficient structure.

Our ongoing implementation of operational efficiencies (and improved research) enables NASS to operate using standard statistical processes with built-in quality assurance procedures and facilitate the incorporation of quality control checks. The technology implementations will ensure all data goes into a digital form within a much-reduced time frame. This will allow NASS to implement components of adaptive design into its data collection procedures, thereby reducing cost and minimizing response bias. Computerized editing procedures will reduce staff review and associated costs. Other cost savings are materializing in consequence of the fact that fewer staff members are needed to accomplish the objectives of agency programs. Our research agenda, with its focus on modeling, provides the foundation for NASS to be more transparent with its methods and produce quality measures for its data.

One of the initial goals of the transformation ongoing at NASS was to produce efficiencies that would permit the agency to enhance its data products and stay relevant to societal needs. Achievement of this goal may be inhibited in a budget-downsizing environment, but the ongoing transformation will, in any event, allow NASS to remain relevant without inflicting damage on its core programs.

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One Comment »

  • Dave W. said:

    Cynthia I knew and respected You as a NASS Division Director. As a NASS retiree my contacts with Production Agriculture tell me they must have reliable current production number. Census data is a valuable bench mark, but is of minimal value in producing and marketing commodities.