Employee Compensation and Job Satisfaction on Dairy Farms in the Northeast
Fogleman, Sarah L.; Milligan, Robert A.; Maloney, Thomas R.; Knoblauch, Wayne A.
As economies of size become increasingly important in production agriculture, farm sizes continually increase. For the farm members of the Northeast Dairy Producers Association (NEDPA), this results in larger herds, more acres of crop production, and more full-time, non-owner employees. The NEDPA membership realizes the important roles these individuals play in their businesses and are devoted to the study of successful human resource management practices. This research quantifies and illustrates the internal pay structure and enumerates the current employee satisfaction levels present on these farms for different subsets of employees. To enumerate the study, the NEDPA membership was divided into two groups. The first group, consisting of farms with herds smaller than 500 cows and greater than 1500 cows participated in the internal pay portion of the study where a researcher conducted personal interviews with the farm owner or manager and gathered detailed compensation information for each full-time, non-family employee. A second, more homogeneous group of farms, those with herd sizes ranging from 500 to 1500 cows, participated in both the internal pay study described above and the employee satisfaction study. On these farms, the owner or manager provided detailed compensation information about the employees and then the employees themselves were interviewed to assess their job satisfaction levels. In those cases where some employees were unavailable, another employee was asked to administer the survey to their coworkers and return the completed survey to us. We also gathered general managerial and production data at both groups of farms. Employers classified each employee as one of five competency levels based on supervisory capacity, level of decision-making authority, and skill level. These classifications determined the internal pay structure on these farms. A natural hierarchy related to tenure and education is evident as the members of each competency level become more experienced and educated from one band to the next. Total compensation values also increase with higher competencies. Mean compensation values and standard deviations for each level provide benchmark bands, indicating ranges of compensation values and illustrating the total compensation for 65 percent ofthe employees within each competency level. ii The internal pay data is also used in two regression analyses where total compensation and annual cash wage are the different dependent variables. The explanatory variables consist of farm and employee characteristics. The annual wage model has a slightly stronger R-squared value and coefficients that are more consistent with economic theory and a priori information but both models illustrate several interesting factors consistent with their respective dependent variables. Total Employee Satisfaction was measured through four core dimensions: autonomy, variety, feedback, and task identity. While the Total Satisfaction scores were fairly strong, the most interesting result is that Feedback is the core dimension in which employees are least satisfied. This result was supported by correlating the satisfaction components with variables such as compensation, experience, and demographic factors. These statistics indicate that feedback is not associated with wages or other factors but more likely with the amount and quality of communication an employee has with the farm owners or managers. Many employers utilize some non-traditional compensation techniques. Qualitative observations showed that employees enjoy these non-cash benefits but frequently underestimate their values. This is a problem for producers as they compete with seemingly higher wages from other area employers. This concern can be alleviated, again, by good communication between employers and employees about all aspects ofthe job, including compensation values.
Charles H. Dyson School of Applied Economics and Management, Cornell University