Progress report for LNC22-467
Project Information
Title. Financial Feasibility and Environmental Implications of Adopting Automatic Milking Systems by Dairy Farms in Wisconsin and Minnesota
Problem. In recent years, dairy farmers experienced substantial market volatility, hiring challenges and rising labor cost. These factors, and the substantial time that farmers must dedicate to their dairy operations are forcing an exodus from this industry. Automatic milking systems (AMS) offer a potential solution to these issues. This technology also decreases the reliance on labor while improving animal welfare and resource management. However, AMS requires a significant investment, and its net economic benefits depend on several aspects including daily milk production, herd size, and infrastructure needed to accommodate the milking robot in the barn. As a result, small farms are constrained financially to adopt this technology.
Goal. This project will assess the financial sustainability and environmental implications of AMS adoption in Wisconsin and Minnesota dairy farms. Three farm typologies are considered: traditional non-adopters (particularly small-sized operations), farms transitioning to AMS and established AMS adopters. The project’s aims are:
- Identify and quantify demographic, economic, and environmental attributes that influence dairy farmers’ decisions to adopt or transition into AMS.
- Evaluate changes in labor skills profile required among AMS adopting farms and explore labor-hiring challenges and alternatives for dairy farms with traditional labor-intensive milking production.
- Assess the overall feasibility of AMS technology by analyzing financial and operating management practices required to adopt AMS and determining specific sets of business strategies that optimize farm profitability for each of the three farm typologies.
Methods. This project will employ several analytical methods. An extensive producers’ survey will be conducted in both states. Supplementary qualitative evidence will be compiled from focus group discussions, case studies and a choice experiment (measuring farmers’ monetary valuation of AMS attributes). Moreover, analyses will extend to a comprehensive financial assessment of AMS adoption and non-adoption decisions, and a benefit-cost analysis to evaluate the financial feasibility of implementing AMS. Participating farmers will provide valuable inputs as members of our advisory committee and focus groups, and in the validation of project results.
Outcomes
- Learning outcomes. Dairy farmers will learn about the financial feasibility and environmental implications of adopting AMS. Smaller farms will also gain a clearer grasp of labor savings and key factors to consider when deciding to install robotic milking.
- Action outcomes. Dairy farmers will use financial decision benchmarks to determine the feasibility of implementing AMS depending on their farm characteristics and milk production.
The project’s goal is to exhaustively study the feasibility of AMS in Wisconsin and Minnesota from the financial and sustainability perspective. The outcomes expected from our study are:
- Learning outcomes. Dairy farmers will learn about the financial feasibility and environmental implications of adopting AMS. Smaller farms will also gain a clearer grasp of labor savings and key factors to consider when deciding to install robotic milking.
- Action outcomes. Dairy farmers will use financial decision benchmarks to determine the feasibility of implementing automatic milking systems depending on their farm characteristics and milk production
Dairy farming is an increasingly risky enterprise, driven by recent market volatility and labor hiring challenges. This project investigates whether robotic milking adoption decisions allow reallocation of owners’ working hours towards strategic decision-making tasks due to realized labor specialization and efficiency gains. Improved farm management and the ability to expand operations without hiring additional labor can enhance the quality of life of farmers and workers while helping enhance the sustainability of the nation’s milk supply.
This project employs benefit-cost and financial feasibility analytical techniques to determine whether economic returns generated from implementing an automated milking system exceed associated costs. This study aims to identify key strategies for a successful implementation of robotic technology, considering differences in farm size, type of barn, management practices, farm’s reliance on labor, among other factors. Results of these analyses will determine whether robotic milking leads to long-term improvements in farm profitability and financial resilience.
Cooperators
Research
Aims of the study
This multi-institutional project is designed to explore the financial sustainability and environmental implications of automatic milking systems in Wisconsin and Minnesota dairy farms. Specifically, we will look at three farm typologies: traditional non-adopters (particularly small-sized operations), farms transitioning to AMS and established AMS adopters. We propose three aims:
- Identify and quantify demographic, economic, and environmental attributes that influence dairy farmers’ decisions to adopt or transition into automated milking systems.
- Evaluate changes in labor skills profile required among AMS adopting farms and explore labor-hiring challenges and alternatives for dairy farms with traditional labor-intensive milking production.
- Assess the overall feasibility of AMS technology by analyzing financial and operating management practices required to adopt AMS and determining specific sets of business strategies that optimize farm profitability for each of the three farm typologies.
We will use a holistic approach to fulfill the aims by following six methods of analysis (in chronological order – as described in Figure_1):
Pilot Survey – Stage Completed
The aims of this project were developed based on the outcomes of our preliminary study launched in early Spring 2022. This pilot survey was conducted by the Survey Research Center (SRC) at the University of Wisconsin – River Falls (Co-PI Burney is the Director of the SRC). Five hundred Wisconsin dairy farmers were randomly selected and received the survey through mail. The high response (36.4%) obtained in this preliminary study provides evidence of the interest of dairy farmers to learn about robotic milking and the importance of the project. Farmers emphasized in their responses the need for optimizing resources and decrease dependence on labor to keep small farmers in business. Likewise, 37 out of the 182 survey respondents provided their contact information for a subsequent follow-up interview. From this list, we will select twenty-five farmers that will participate in our focus group.
Advisory Group
An advisory group of five dairy farmers from Minnesota and Wisconsin will provide input throughout the project, meeting twice per year to revise and validate all outcomes of the study. The five dairy farmers have been already identified and their letters of support are attached. Advisory Group meetings will be scheduled for a 5-hour duration and will be used to solicit feedback and guidance from farmers on the research team’s progress to date.
I. Exploratory study
For aims 1 and 2, we will conduct an exploratory study to gauge farmer perceptions of robotic milking and challenges they may face in adopting such technology. A survey will be mailed to 9,100 dairy farmers across Minnesota and Wisconsin, including farmers that have adopted robotic milking and those who have not. The survey will also gather information on methods of production and on the demographic profile of the dairy farmer. The survey will be conducted by the Survey Research Center (SRC), which also conducted the pilot survey. As aforementioned, Dr. Burney (Co-PI) is the Director of the SRC.
The SRC is a not-for-profit department that provides cost-effective survey services to academics, local governments, chambers of commerce, food co-operatives, and other clients in the public sector and in the agriculture industry. The SRC has conducted several surveys of dairy farmers in Wisconsin over the past 10 years and has a proven record of achieving strong response rates.
The SRC, in collaboration with the research team, will develop the survey that will be distributed to owners/managers in both states through mail. Recipients will have to option to complete the survey online through a URL and QR code provided in the cover letter. To maximize the response rate, the SRC will send one postcard reminder three weeks after the initial mailing of the survey and will send a second copy of the survey two to three weeks after the postcard reminder. Based on historical experience and literature on survey methodology, this method is likely to boost the survey response rate. Data collection will be conducted over an 8-week period. The SRC will clean and compile all responses received and provide the authors with the data in CSV format. The SRC will conduct all tasks associated with survey preparation and mailing.
Farmers will also be invited to voluntarily provide contact information if they would be open to follow-up questions or if they would like to be more directly involved in the project. This information will also be used to recruit farmers to obtain feedback on various other aspects of the research. Farmers who complete the survey will be entered into a random draw to win one of ten-five $50 Visa cash vouchers.
II. Choice-experiment
To accomplish aim 1, we will also employ a hypothetical Choice Experiment (CE) with dairy farmers who are familiar with AMS. Using a CE, we will quantify the farmers economic value of different attributes of AMS – highlighted by the exploratory study and literature: such as improvement in farmers quality of life, reduction in time and effort devoted to manage employees, environmental benefits (e.g. efficient water use) (Jacobs & Siegford, 2012; Schulte & Tranel, 2013), yield improvements, decreased reliance on manual labor, labor-cost savings (Tejeda et al., 2020; Tranel, 2017), improved animal welfare and reduction in disease frequency, among other aspects.
CEs have been used widely in different fields, including in agricultural economics. While there are few applications of CEs in the dairy sector to elicit farmers’ preferences and opinions on technology adoption, including on-farm raw milk concentration plants and working conditions (Lips & Gazzarin, 2008; Weissgerber & Hess, 2022), to our knowledge, this is the first time a CE is applied to understand dairy farmers’ preferences related to AMS.
Table 1 describes the potential attributes to be presented to farmers related to AMS that will be evaluated. The number of CE decisions (tasks) and combination levels will be designed based on an efficient design.
Table 1. Attributes and levels of an AMS for CE
Attributes |
Levels |
Investments costs per cow |
min, mean, max |
Labor savings costs per cow |
min, mean, max |
Water use per cow |
x, y, z |
Please select which of the two alternative you prefer:
Attributes |
AMS A |
AMS B |
Investments costs per cow |
Min |
Mean |
Labor savings costs per cow |
Mean |
Max |
Water use per cow |
X |
Y |
I choose |
|
|
Exit questions: Following the CE and suggested by previous studies on technology adoption (Carter, 2016), questions investigating farmers’ risk behavior and sense of self-efficacy will be considered. This will allow understanding how these factors affect AMS adoption and farmers’ preferences for AMS attributes. Questions related to basic sociodemographic information will also be included at the end of the CE questionnaire.
Data analysis and target sample: Data from the CE will be collected through a survey and will be measured using advance economic modeling. We expect to mail the survey to 2,000 randomly selected dairy farmers (expecting a 15% response rate) to obtain 300 responses and have a representative sample size. Farmers who will participate in the exploratory study (previous to this experiment) and who are familiar with AMS will be invited to fill out a questionnaire with the CE questions as well as exit questions. The survey will take on average 15 minutes and will be self-administered.
III. Financial assessment
With input from the previous methods, a financial assessment will be used to qualitatively determine the impact of robotic milking on farm profitability, and thus fulfill aim 3. Data will be collected from farm financial statements such as the Farm Financial Management Database (FINBIN), the Agricultural Resource Management Survey (ARMS) and the Farm Business Financial Management application (FARMBENCH). The financial assessment will investigate the financial situation of dairy operations that already adopted the AMS technology compared to their counterparts (farms with non-robotic milking). The results will shed light on the differences in cost structure of both types of dairy farms. This will be particularly valuable for farmers contemplating switching to mechanization of the milking process.
IV. Case Study for Labor
For aim 2, we will also elaborate a case study that explores alternatives for traditional labor-intensive production for farmers who cannot afford robotic technology. We propose to test the hypothesis that domestic labor’s aversion to farm work can be tempered by the different work structure and conditions of dairy farms with AMS. We will employ case study techniques involving three farms identified as non-AMS adopters, employing traditional labor-intensive methods. These case studies will utilize the participating farmers’ production, cost, and other operating decision inputs (especially labor) under an economic-simulation framework. We want to investigate if the adoption of this technology can be enough to lure domestic workers and thus mitigate the hiring issues, especially in the light of a costlier H-2A foreign labor hiring alternative whose existing guidelines are incompatible with the needs of the dairy industry. Results of such analyses will become the basis of this study’s policy recommendations on labor needs for the industry.
VI. Benefit-Cost Analysis for AMS
We will develop case studies that investigates the situation of three selected dairy farms that have already adopted AMS using benefit-cost analysis to quantify the economic impact of adopting robotic milking. We will collect information regarding their experience obtaining loans to finance the AMS investment (i.e., equipment, infrastructure needed to support the milking robot, required changes to barn design), changes in management structure, training to adapt managers into the new technology, and the environmental considerations needed including manure and water management. The results will be calibrated using the data collected throughout the study and will be validated by the farm advisory committee. The outcome of this study will inform farmers of the long-term financial sustainability of AMS adoption compared to a traditional milking system. Likewise, a financial spreadsheet will be developed that can be used by dairy farmers with AMS or by dairy operations contemplating AMS adoption in order to evaluate the financial feasibility of AMS, the optimal use of resources, and the economic and environmental considerations needed in order to implement this technology.
Collaboration with the audience
As aforementioned the Background section, farmers will participate in the design and planning of the study as part of our advisory group. Dairy farmers will also express their opinions and perceptions in the exploratory survey and the choice experiment. Dairy farm managers will expand on their experience regarding labor challenges and their AMS adoption in our case studies. Farmers will also provide feedback in the extension outreach that will be hold in the upcoming webinars and two-day workshop during the fall of the second year (2024). We will also survey participants to evaluate if they have gained knowledge from our outreach activities (explained in the Evaluation Plan section).
I. Results of the exploratory study
Wisconsin is characterized by mostly small to medium-sized family farms, unlike other major dairy states like California and New York. In 2021, Wisconsin annual production reached 31.7 billion pounds of fluid milk, equivalent to 14% of the U.S. milk output. A tightening market for agricultural workers, supply chain bottlenecks, and price volatility have increased farm financial stress and expedited the exit of many small farms from the industry. Thus, automatic milking systems (AMS) are seen as an alternative to hired labor. AMS, or robotic milkers, use robotic arms to attach teat cups with the help of sensors for a “hands-free” milking operation. Depending on type, the AMS may use a sorting gate to control flow of cow traffic into the system. Cows are identified using ID tags and the AMS generates a wealth of data on milking frequency, quantity per teat, milk temperature, etc.
For aims 1 and 2, we conducted an exploratory survey to determining the motivations and barriers to adopting AMS, and the impact of AMS adoption on milk yields, cost of production, profitability, farm’s ability to withstand market volatility, use of agricultural workers, etc. The survey was distributed by the Survey Research Center at UW-River Falls in the winter of 2023 to a randomly selected sampling frame of 2,000 dairy farmers in Wisconsin. A total of 668 responses were received, for a robust response rate of over 33%. From the sample, 39 farmers already adopted AMS.
Descriptive results from the survey showed that over a 10-year period, dairy farms with AMS experienced significant greater improvements in yields, cost of production, profitability, reliance on agricultural workers, and owner’s time spent with family, relative to farms without AMS. In addition, contrary to popular belief, large dairy farms (500+ milking cows) were less likely to adopt AMS relative to medium-sized farms. One explanation for this result is that larger farms may find it easier to recruit and retain agricultural workers as they have greater ability to accommodate immigrant workers by providing better housing, navigating the immigration requirements, etc.
II. Choice-experiment (in progress)
To accomplish aim 1, we are currently conducting a Choice Experiment (CE) with dairy farmers in Spring 2024, especially those who have not adopted yet AMS. Using a CE, we will quantify the farmers economic value of different attributes of AMS. This effort is ongoing and envisioned to finish by mid-April of 2024.
Education
The outreach and workshop component of the study will be implemented in Fall 2024.
Project Activities
Educational & Outreach Activities
Participation Summary:
Three labor-related outreach articles/bulletins:
- Southern Ag Today submission: “The Costs and Benefits of Mechanization: A Look at the Dairy Sector”
- Southern Ag Today submission: “Reforming the H-2A Guest Farmworker Visa Program: Sectoral Coverage Expansion and Workers’ Path to Permanent Residency”
- Outreach Bulletin under Review: “Milking Production Practices and Trends from Farmer’s Perspective: A Tale from the Midwest”
Outreach Plans
-
- Poster/paper proposal to the annual conference (December) of the Georgia Farm Bureau and another commodity (dairy, cattlemen’s association, and the like) group in Georgia
Analyses of labor-related variables and formulating an econometric model to explore significant correlations between labor hiring decisions and several factors (structural, demographic, and financial/economic)
-
- Envisioned outputs: journal article, conference paper
Analyses of farmer valuations for milking automatization
-
- Envisioned outputs: conference paper to be presented in August at the AAEA annual meeting
The outreach workshop that will provide the results of the four stages of the research project is scheduled to be late September - Early October 2024 to farmers from Wisconsin and Minnesota.
Learning Outcomes
- Pending for Fall 2024
Project Outcomes
The outreach to farmers will be made in the last stage of this project - Fall 2024
While developing the case study (Stage 3 of the project), we interviewed two farmers in Minnesota in February 2024. Both provided anecdotal experiences regarding the implementation of Automated Milking Systems in their small farms. What we found interesting is that, both of them, expressed that they were able to stay in business mainly due to the adoption of AMS, because it was pretty difficult to find farm workers.
Information Products
- FEASIBILITY OF AUTOMATIC MILKING SYSTEMS IN THE MIDWEST (Conference/Presentation Material)