Recognizing and Responding to Multiple User Needs

Among the users of data on business formation and dynamics are federal agencies, researchers, and businesses themselves. One way to increase the probability that final data products will meet demands is to involve users in survey design and data collection strategies from the start. Ideally, statistical agencies should facilitate front-end collaboration with the academic and business communities and not rely solely on postsurvey follow-up. Considering user needs up front should increase the relevance of final data products.

Of course, users’ data needs vary enormously. Even among the statistical agencies, whose missions are well documented, this is the case. For example, construction of local-level employment statistics relies more heavily on data for young and small firms than does production of the national economic accounts. Certain organizations—perhaps most notably the Small Business Administration, charged to “aid, counsel, assist and protect the interests of small business concerns”—are focused almost entirely on such data. Another example is the Census Bureau’s Economic Planning and Coordination Division (EPCD), which is charged with, among other things, editing and publishing the Census Bureau’s nonemployer statistics. They have a number of information needs that could be addressed by a regular survey of nonemployer entities. One example of an information gap that has been problematic for EPCD over the years is the extent to which employee leasing or other nontraditional employment arrangements are utilized by nonemployer entities with very large receipts.

Beyond the agencies, mayors, other local government leaders, and chambers of commerce need information for their cities and surrounding metropolitan areas, while governors need information for their states and counties. Urban and regional planners and congressional representatives require business data aggregated to areas of different sizes. Local business owners take advantage of information about their competition at the local, even neighborhood, level for purposes of planning various aspects of their operations. Ideally, data should be collected and made accessible in a way that helps business owners answer a broad array of operational questions: Where are my customers and potential customers located? Where is the competition located? Where do my employees and potential employees live? Where should I locate my stores, offices, and plants? How much should I produce? How much should I order? How much should I hold in inventory? How should I set my prices? What is the best way to promote my products and services? How much should I pay my employees?

Researchers, policy makers, and businesses use information, disaggregated to various levels of granularity, to plan and set goals for economic growth, to track progress against goals, to identify pockets of underper-

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