January 31, 2018
By: Nico Thomas, Steve Campbell
There’s an apocryphal conversation between Hemingway and Fitzgerald where Hemingway observes that the difference between the rich and others is that they have more money. The accurate account is that Hemingway was talking with literary critic, Mary Colum. When Hemingway mentioned that, “I am getting to know the rich,” it was Colum who responded, “The only difference between the rich and other people is that the rich have more money.”
While this may be useful for small talk at your next cocktail party, why is it relevant in a manufacturing blog? Is there an analogous conversation for rural manufacturing? If we said, “We are getting to know rural manufacturing,” would the witty, but correct, response be, “The only difference between rural and other manufacturing is that you can see more trees at lunch”?
Luckily for us, there is a wealth of data on urban and rural communities in America, which helps us move the conversation from anecdotal to factual. One such piece of data is a report published by the USDA Economic Research Service, entitled “Rural America At A Glance: 2016 Edition”. This report analyzes the social and economic differences between urban and rural America, highlighting key differences such as urban and rural communities having differing population levels, costs of living, employment levels, median earnings, industrial compositions, and industrial dependencies among others. The information presented in the report is useful, and we recommend giving the study a look. The one piece of information in the USDA report that really stood out to us (for obvious reasons) was rural America’s dependence on manufacturing.
Impacts of Manufacturing on Rural Communities
When there are downturns in manufacturing the economic impacts disproportionately affect rural communities. Nearly 350 – 348 to be exact, or 17.8%, of rural counties in America are manufacturing dependent, and 70% of all manufacturing dependent counties are non-metro (rural). Those manufacturing dependent counties make up 22.5% of the rural population in America. And although the earnings gap between urban and rural manufacturers is large, median earnings for manufacturing is still the second largest in rural counties. These numbers are significant and highlight the importance of manufacturing to rural America. The better we understand rural communities and the industries they rely on, the more we can do to support those industries.
MEP National Network Supports Rural Manufacturers
The MEP National Network is in a unique position to both study and support rural manufacturing communities. The Network works with manufacturing companies in their local communities to enhance their competitiveness and reinforce their sustainability. As a result of these interactions, MEP Centers get feedback and data directly from companies, which informs our understanding of the industry and the communities in which they operate. This data was the foundation for a recent analysis of MEP Center’s rural clients done by the Manufacturing Research and Program Evaluation (MRPE) group of NIST MEP.
The rural client analysis leveraged unique survey data from Center clients to examine the extent to which the program reaches rural manufacturers and what those interactions tell us. From this analysis, we were able to examine characteristics of rural manufacturers in terms of industry, size, challenges, and reasons for engaging with MEP Centers. The analysis also examined the extent to which rural manufacturers have outcomes similar to urban manufacturers. The results from this analysis were telling.
And the Survey Says
There were significant correlations when looking at rural firms and some of the indicators which MEP Centers collect from their clients. The characteristic correlations are below.
In the client survey, manufacturers are asked “As you look forward over the next 3 years, what do you see as your company’s three most important strategic challenges?” We found that:
the more rural, the more likely cost reduction and employee recruitment were challenges
the more rural, the less likely growth opportunities and financing were challenges
The survey also asks the client “What were the two most important factors for your firm choosing to work with the Center X?” We found that:
the more rural, the more likely specific services and providers not nearby was an important factor
the more rural, the less likely fair and unbiased advice was a factor
Other characteristic correlations include:
the more rural, the less likely the establishment was woman-owned or minority-owned
the more rural, the less likely the industry was in other manufacturing (e.g. NAICS 54)
So yes, rural manufacturers are different demographically, highlight different challenges, and have different factors and needs when choosing to work with a local MEP Center. But do they deliver different impacts? A multivariate statistical analysis for impacts over the last five years found that rural manufacturers were less likely to indicate “yes” for one of the following impacts:
-new or retained jobs
-new or retained sales
-cost savings
-additional investment
However, when assessing the magnitude of the impact and not just the existence of an impact, rural manufacturers delivered statistically the same level of impact and even higher amounts of additional investment. They might say “yes” less frequently, but they deliver equal or higher impact amounts. This is likely due to rural manufacturers being slightly larger on average compared to urban manufacturers.
Leveraging Data to Enhance Services
Rural manufacturers are, in fact, different. They don’t just have more nearby trees! The next question involves using this information.
The MRPE group is aiming to leverage this data to enhance the Network’s service to and positive impact in the rural communities. A one size fits all approach does not work when trying to service unique companies and communities, and the more we can uncover this dynamic through data, the better we can inform our activities. This is not where our research ends, and we hope to use more community specific data to not only gain a greater understanding of the intricacies that make up the U.S. economy, but to also positively impact our economy.
