Spring 1992 // Volume 30 // Number 1 // Feature Articles // 1FEA6

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Database Information for Small Organizations

Abstract
Where are our best customers located? How has our town's population been changing? What new businesses can we attract to our downtown? How have some rural communities managed to revitalize their economies? What segments of our state's farm economy have been relatively strong? Does our region need more services for pregnant teenagers, homeless families, the impoverished elderly, or other at-risk groups? This article describes a demonstration program in which information to help answer such questions is provided through Extension. The information is based on secondary data-records and statistics already gathered into databases by organizations such as the Census Bureau and Dun & Bradstreet.


Peter J. DePaulo
Assistant Professor of Marketing
University of Missouri-St. Louis


Where are our best customers located? How has our town's population been changing? What new businesses can we attract to our downtown? How have some rural communities managed to revitalize their economies? What segments of our state's farm economy have been relatively strong? Does our region need more services for pregnant teenagers, homeless families, the impoverished elderly, or other at-risk groups?

Answers to questions like these are needed by small businesses, nonprofit service organizations, city planners, and local government officials. This article describes a demonstration program in which information to help answer such questions is provided through Extension. The information is based on secondary data-records and statistics already gathered into databases by organizations such as the Census Bureau and Dun & Bradstreet.

Utilization Gap

Secondary data can be obtained by anyone, often at low cost, from various suppliers: state data centers, private data companies, and other organizations that compile and sell information from computer databases. However, major databases are extremely voluminous and complex. Further, their usefulness for particular purposes may not be readily apparent.

For example, a data center's catalog may include "automobile registrations by year, make, and zipcode." Certain applications of this database, such as finding a location for a new automobile service center, may be obvious. Other applications are more subtle. For instance, automobile registration data can also indicate the relative affluence of various areas within a city, because more affluent areas have newer cars.

Large organizations have staffs of information specialists who can handle complex databases with finesse. However, small businesses, nonprofit organizations, and local governments may not have easy access to such expertise. One survey has shown that when small business managers seek marketplace information, they rely on word-of-mouth information from business associates rather than on database information.1 Although officials in small organizations often have a general idea that various information is available, they may not know where to get it and how to ask for it. If officials do acquire a relevant set of data, they may be unsure how to compile and interpret the numbers. Therefore, a utilization gap exists between the small organizations that can use database information and the technical organizations that can supply it.

From 1988 to 1990, the Center for Business and Industrial Studies (CBIS) at the University of Missouri-St. Louis, in conjunction with the UM-St. Louis Urban Information Center, conducted an information-services demonstration project. The project explored ways to bridge the utilization gap by helping small organizations benefit from public database information. The work was funded by the Urban Extension Project, a joint project of the East Central Region of University Extension and Continuing Education-Extension at UM-St. Louis.

Secondary information may be relevant to virtually any Extension initiative. Consider, for example, programs in the overlapping areas of family development, health and nutrition improvement, and youth at risk. Program developers could refer to county-level statistics on divorce rates, adult illiteracy, homeless families, impoverished elderly, teenage pregnancies, infant deaths, licensed day care facilities, hazardous chemical storage sites, and a variety of other variables. The UM-St. Louis Extension project dealt with small businesses and economic development, as illustrated below.

Demonstration Cases

Case #1: Washington County, Missouri. In addition to the economic problems typical of many rural areas, Washington County has suffered high unemployment after a large mine closed. Because retail sales in local stores had dropped so sharply, the county program director, the contact person for this case, wondered whether many residents might be "outshopping"-making purchases in urban areas outside Washington County.

From another university office, the county director had already acquired a set of data tables, with statistics such as "effective buying income" and "total retail sales." He realized these data were probably relevant to outshopping, but didn't know how the numbers were compiled or defined. We identified the data source as the Sales and Marketing Management (S&MM) magazine and found an issue explaining the statistics. We then conducted a library computer search, which uncovered a business journal article explaining how to use the S&MM data to study outshopping.2 Our analyses provided hard evidence that Washington, like other rural counties near metropolitan St. Louis, loses considerably more retail business to outshopping than rural counties not located near a large city.

The library computer search also found some interesting articles about outshopping in general and about small rural towns that have successfully turned their economies around. These articles suggested some new ideas for revitalization strategies. The county director is now working with Washington County officials to develop a systematic plan for dealing with economic problems.

Case #2: Maplewood Chamber of Commerce. This suburban St. Louis client needed demographic information to help in strategic planning for its "main street" business district. We conducted this project in 1988, when the 1980 Census was largely outdated. Because the 1990 Census data won't be available until at least 1992, finding substitute sources of up-to-date demographics was essential. For example, to estimate the current populations of the neighborhoods around the business district, the Urban Information Center used a statistical extrapolation from county housing data. Also, to compare levels of affluence in various neighborhoods, we compiled vehicle registration data on the average ages of automobiles.

Some of the findings were relevant to Maplewood's efforts to attract new retailers to the business district. For example, data on changes in population and affluence since the 1980 Census showed that the Maplewood trade area compared favorably with other local business districts competing with Maplewood for new retailers.

Case #3: Leander Lubricants, Inc. Leander is a small manufacturer of specialty oils used in metalworking industries. The owner requested information to help locate potential customers in his prime trade area, the Midwest. We provided computer-generated maps with shading patterns enabling managers to see, at a glance, the areas containing high concentrations of metalworking firms that buy Leander's products. The maps could help plot efficient travel routes for sales representatives, allowing them to call on many customers while containing travel costs. The maps were compiled from a business database maintained by the Census Bureau.

From these demonstration cases, insights about the kinds of database information useful to small businesses and local governments were gained. Further, we learned how to organize and present the data in ways useful to such clients. In other words, it's not enough to get the right set of numbers; one must also turn the data into information.

Information Handbook for Extension Specialists

To help guide Extension specialists in providing information services to their clients, we've prepared a detailed handbook, entitled Information Services: How To Acquire Public Database Information and Make It Useful for Small Businesses and Government.3 Although intended to be self-explanatory, the handbook will also serve as the textbook for a new seminar that may become part of inservice training for Extension specialists in Missouri.

The trained Extension personnel should be able to handle most of the secondary data needs of their clients. That is, they should be able to locate relevant secondary data, work with database suppliers, acquire statistics compiled in useful forms, and interpret the information for their clients. Sometimes, however, the Extension personnel may need help with the more technical aspects of secondary data. To provide such help, we hope to acquire funding for a part-time information specialist with expertise in demographic statistics and business research. This technical specialist would help Extension field personnel and clients with information needs on request. We've conducted one seminar for Extension specialists involved in economic development; the participants felt they'd need such technical assistance occasionally.

When secondary data are compiled by a state data center or private data company, there are out-of-pocket costs to compensate the supplier for programming time, computer operations, and printouts. Such costs range from $50 to several hundred dollars, depending on the complexity of the request. While our grant covered these costs for the demonstration cases, in the future, clients will have to cover some or all of such costs. This poses a problem, since small organizations are unaccustomed to paying for a few pages of statistical tables and maps. Furthermore, the Extension specialist may spend considerable time working with the client to find relevant data, compile it, and derive strategic recommendations.

Conclusion

Several Extension educators maintain Extension should do more to aid small businesses.4 By training its staff in the use of secondary data, Extension can build its capacity to help small organizations gain the information edge. As one well-known writer who has studied business excellence observed, the most successful companies thrive on information.5

Although this project focused on small businesses, secondary data are relevant to virtually all Extension activities. Whether dealing with family issues, youth development, displaced workers, health problems, environmental quality, agricultural issues, or any other concerns, Extension personnel and their clients need to understand what the situation is now and how it has been changing. Secondary data, when converted to useful information, help provide that understanding. Moreover, encouraging the use of information can be viewed as the "core business" of Extension.6

Footnotes

1. J. Lynn Johnson and Ralph Kuehn, "The Small Business Owner/Manager's Search for External Information," Journal of Small Business Management, XXV (July 1987), 53-60.

2. Gary Brockway and W. Glynn Mangold, "The Sales Conversion Index: A Method for Analyzing Small Business Market Opportunities," Journal of Small Business Management, XXVI (April 1988), 38-48.

3. For information on ordering the handbook, contact University of Missouri-St. Louis, Center for Business and Industrial Studies, 8001 Natural Bridge Road, St. Louis, MO 63121-4999.

4. For example, William R. Bernhagen and Wesley T. Mott, "Small Business: An Opportunity for Extension," Journal of Extension, XXIV (Fall 1986), 8-10 and Thomas A. Henderson, "Should Business Be the 'Business' of Extension?" Journal of Extension, XXIV (Winter 1986), 23.

5. Robert H. Waterman, Jr., The Renewal Factor: How the Best Get and Keep the Competitive Edge (Toronto: Bantam Books, 1987).

6. Michael Quinn Patton, "Extension Excellence in the Information Age," Journal of Extension, XXIII (Summer 1985), 4-7.