Progress 10/01/11 to 09/30/14
Outputs
Target Audience: The target audience is small- and mid- scale, diversified fruit, vegetable, and fresh cut flower farms. In each year of the project, we targeted different regions of the state. Farms with at least 3 and no more than 6 active marketing channels (by category) were preferred. Additionally, we sought farms with 12 or fewer workers, including owners. Farms that fit this description tend to have between 2 and 35 acres in production and grow 35 different crops. These farms also tend to focus on direct marketing channels, and are usually involved in more than one farmers' market. If the farm participates in multiple farmers' markets, we are able to track each market separately so the best and poorest performing markets can be identified. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided? We reached approximately 235 agriculture service providers through presentations in NY and other states. Additionally, we reached nearly 1,000 farms in MA, VT, and NY through presentations at conferences and workshops. This work has led to a strong interest from agricultural service providers in New England and the Pacific Northwest to conduct MCAT in their states in 2014 and 2015. Our speaking opportunities certainly got agricultural service providers and farms thinking about marketing channel assessment and the opportunity to improve the efficiency of marking labor on their farms. The primary message of the presentations delivered is that the main factors of marketing channel performance can be measured on each individual farm and help clarify which channels are top performers for that farm and which ones can be considered for reduced participation or elimination. The presentation puts the factors of labor requirements, profitability, and volume of product sold, risk, and lifestyle preferences (compatibility) into perspective for farmers as they think about their marketing channel participation portfolio. How have the results been disseminated to communities of interest? Each farm that completes the MCAT data collection process for one week receives a detailed report, showing their data displayed a number of different ways and with personalized interpretation. The report illustrates the relatively strong and weak marketing channels and suggests changes. It summarizes the data collected from each farm in ways that make it easy for the farm to compare channels against each other, but also to see their farm's baseline data. The old agricultural economists' adage that "you can't change what you can't measure" is true. This report reveals measurements of farms marketing labor and earnings so farms can begin to adjust their overall marketing in favor of profitability, financial sustainability, and personal enjoyment and satisfaction. This outcome, the report, is the most valuable part of this project because it has a direct impact on farm sustainability and was not possible without the project. In their reports, farms learn how their marketing labor is divided between the four major steps of marketing as well as among the channels. This data is displayed as a percent of the total as well as in hours. From this, farms can learn if too much labor has been assigned to a particular activity or marketing channel and take steps to adjust it. In the report's "Labor Hours per Marketing Activity" graphic farms can see their labor divided by task. This has primarily led to two suggestions to farms; to improve the efficiency of their "wash and pack" stations and to consider ways to reduce overall sales time. The report also displays a summary of hours devoted to marketing on each day of the week, by employee, as well as the labor costs of each channel. One really useful and important graph on the report compares the percent of total labor that each channel utilizes next to one with the percent of total gross sales for each channel. The comparison of the two, side by side, makes it very clear to farms which channels are "pulling their weight" on the farm and which are not. We use this set of graphs as a "first glance" to reveal how the farm's marketing is going because it reveals the interaction of labor and sales information. It also, along with the other data from the farm, reveals how farm marketing can be improved. Farms without an MCAT report must make marketing decisions without channel-specific data. The MCAT project provides clear information and conclusions about a farm's marketing and gives them a great advantage in decision-making and overall viability. Farms are also given the rates at which they gross and profit with each channel. Gross sales per hour of marketing labor and profit per hour of labor are both displayed for the farm. Using this, farms have a baseline and an average for all channels they utilize. This can lead a farm to make adjustments such as raising prices in a particular channel or finding a way to cut labor. Displaying these rates also helps clarify a channels' performance better than absolute quantities, such as gross sales, because a channel can produce a great earning rate even if only at a small volume. Using the two sets of data together, it becomes easy for a farmer to imagine how to expand the channels with good rates. For example, if the "restaurant" channel was a low-grossing channel but performed at a high rate of profit per hour, it would be a great candidate for expansion. In this example, how can the restaurant channel be expanded? There are a few ways: 1) the farm can try to get the restaurant customers to place larger orders for each delivery by offering them additional items already grown 2) the farm can work to find additional restaurants that are likely to perform similar to the existing restaurant(s) 3) the farm can increase prices or introduce order minimums to improve the profit per hour rate. The suggestion we offer is directed by conversations with the farmers and are in the summary of each report. Of the three ideas for expanding the restaurant channel used in this example, the complimentary data and conversations will provide guidance as to how the farms should proceed. The MCAT benchmark performance paper was also published as an Extension Bulletin in the Charles H. Dyson School of Applied Economics and Management. The publication (which will be updated when all of the 2014 data is entered) provides benchmark performance estimates that producers can use to gauge their own performance in similar channels. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
The primary accomplishment, for this project is to advise farms how to optimize their marketing labor to reach income (sales) goals and enjoyment of their work. The reports and consultation we provided gave participating farms data-based guidance for those decisions. The Marketing Channel Assessment Tool's (MCAT) main impact on a farm is to provide guidance to either increase gross sales or cut labor. Farmers may be slow to react to the data they receive in their final reports, appropriately cautious to swerve their business in a new direction based on one week of data collection. Nevertheless, we are very satisfied with the farm level impacts that we have seen on farms. Farmers' comments demonstrate that both the process and results of this project guide their overall marketing management. The most common response by farms was to expand channels that were performing well, specifically CSA and wholesale. Another common response was to drop a farmers' market or other poor-performing channel. Some farms report that the project was useful for how they manage their business and track costs such as labor though they did not specifically plan to take action in their channel usage. We are confident that this project has worked to elevate the marketing of farms that have been involved with respect to labor efficiency, gross sales, and total labor demands. These factors directly impact farm profit and sustainability. Even when it may take a few years, or a change in conditions for farms to adopt changes, we know that the process and approach of MCAT impacts farms positively. In addition, preliminary benchmark performance estimates were completed utilizing data through the 2013 marketing season (the benchmarking will be updated in 2015 after including all of the 2014 data). Benchmarks were estimated for profit margin metric (profit/total sales) and sales per labor hour, for both aggregate and individual marketing channel classes (where sufficient data existed). In general, the benchmark estimates indicated that direct and wholesale channels can often compete on relatively even footing in terms of profitability and labor commitments per value of sales, but larger downside risk on wholesale channels may result if not properly managed. Given the variety of direct and wholesale channels evaluated, and distinct differences in their operation and management, we also examined particular channel performance metrics. In terms of profit margins for the direct marketing channels, CSA for our sample was the best overall performing channel. The median margin performance and sales per labor hour for farmers markets was considerably below that of CSAs. While certainly the most popular channel in our sample, of the individual direct channels considered, its performance on profit margin and sales per hour were the lowest. Under both metrics, farm stands performed in between the CSA and farmers market channel results. Less information was gleaned from the individual wholesale channel results, given their small sample sizes. However, from the small sample results, it appears that the restaurant channel results are superior to that in wholesale. Profit margins were considerably more variable for the grocery channel observations, and the median statistics were considerably larger for the restaurant channel than that of grocery. Higher volumes are likely available in grocery channels, albeit at reduced rates of profitability per unit. The relatively narrower distributions on profit margins and median values close to the 75% percentiles also provide some evidence of improved channel performance for restaurants, albeit based on very small sample. Additional wholesale channel observations to assess the robustness of these results are needed, but at least provide some preliminary benchmark estimates. Finally, we assessed differences in the allocation of labor amongst the various labor marketing activities (i.e., harvest, process and package, transport and distribution, and sales and bookkeeping) considering the top (75th percentile) and bottom (25th percentile) performing channel observations (based on the profit margin percentiles). Poorer performing wholesale channels allocated too little time for sales and bookkeeping, likely reflecting the time to properly establish and maintain buyer relationships, and too much time on particular harvesting activities. We found just the opposite for direct channels, whereby top performing channels allocated less time to sales and bookkeeping; likely due to the influence of profitable unmanned farm stands within the sample, relative to more time-intensive but less profitable farmers markets. Given differences in individual labor requirements by channels within each of these broader categories, it is difficult to discern much, other than to note that, on average, labor allocations amongst activities are more similar between direct and wholesale channels than is generally inferred. The higher allocation to transportation and distribution for wholesale channels is likely influenced by the opportunities for wholesaling in more distant (urban) markets. The MCAT project has been successful in identifying the need for proper data collection to assess marketing channel performance for producers. The tool has been implemented successfully in New York State and continues to be utilized to assist management decisions by small-scale fruit and vegetable producers. Benchmark performance metrics on profit margin (profit/total sales) and labor efficiency (sales/labor hour) were estimated, along with average labor allocations among labor marketing activities, differentiated by top and bottom performing channel observations. The generalizations of the results beyond the sample are limited given the relatively small sample size, for certain channels in particular. Expanding the sample size through additional MCAT evaluations will improve the robustness of our results and also allow us to assess differences in channel performance for differing geographic locations and/or farm and manager characteristics. A careful examination of these issues is a top priority for our continuing research.
Publications
- Type:
Other
Status:
Submitted
Year Published:
2014
Citation:
Schmit, T.M. and M.N. LeRoux. 2014. Marketing Channel Assessment Tool (MCAT) Benchmark Performance Metrics. Extension Bulletin. Charles H. Dyson School of Applied Economics and Management.
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Progress 10/01/12 to 09/30/13
Outputs
Target Audience: The target audience is small- and mid- scale, diversified fruit, vegetable, and fresh cut flower farms. This year of the project we targeted farms in Western and Central New York State. Farms with at least 3 and no more than 6 active marketing channels (by category) were preferred. Additionally, we sought farms with 12 or fewer workers, including owners. Farms that fit this description tend to have between 2 and 35 acres in production and grow 35 different crops. These farms also tend to focus on direct marketing channels, and are usually involved in more than one farmers’ market. If the farm participates in multiple farmers’ markets, we are able to track each market separately so the best and poorest performing markets can be identified. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided? In 2013 we reached 135 agriculture service providers through presentations in NY and VT. Additionally, we reached nearly 200 farms in MA, VT, and NY through presentations at conferences and workshops. This work has led to a strong interest from ag. service providers in New England to conduct MCAT in their states in 2014. Public speaking also led to the successful recruitment of 1 farm that managed to complete data collection and 2 others that are potential for 2014. All of the speaking opportunities attracted ag service providers and farms into thinking about marketing channel assessments and the opportunity to improve the efficiency of marketing labor on their farms. The primary message of the presentations delivered is that the main factors of marketing channel performance can be measured on each individual farm and help clarify which channels are top performers for that farm and which ones can be considered for reduced participation or elimination. The presentation puts the factors of labor requirements, profitability, and volume of product sold, risk, and lifestyle preferences (compatibility) into perspective for farmers as they think about their marketing channel participation portfolio. How have the results been disseminated to communities of interest? Results have been provided to the individual farm participants. We have also presented at conferences and workshops to both farms and agriculture service providers on the methodology and benefits of Marketing Channel Assessment. What do you plan to do during the next reporting period to accomplish the goals? We plan to continue public presentations in NY and surrounding states, to recruit additional farms for the 2014 growing season, and to conduct data collection on farms. In addition, the data collected on all farms during this project will be analyzed to develop benchmark performance metrics (i.e., average, low, and high performance levels) by market channel in terms of output potential and labor requirements. Such metrics can be used by individual farms to compare their results relative to their peers and also by farms entering new channels to better understand channel marketing requirements. The results of the analysis will be published in a department extension bulletin and distributed widely.
Impacts
What was accomplished under these goals?
This year we developed and completed the format/template for farm-level data analysis results. We include recommendations for how each farm could improve its marketing, based on the data, and extend an invitation to contact us for additional consultation. The primary accomplishment, for this project is to advise farms how to optimize their marketing labor to reach income (sales) goals and enjoyment of their work. The reports and consultation we provided gave participating farms data-based guidance for those decisions.
Publications
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Progress 10/01/11 to 09/30/12
Outputs
OUTPUTS: Since the project's initiation, activities have primarily concentrated on the recruitment of cooperating agriculture agents in target counties, and the recruitment of farmers to participate in data collection during the summer 2012 growing season. Cooperators and farmers were recruited through extensive speaking engagements through the winter months, as well as through in-person contacts and farm visits. Presentations were given at six farmer events and conferences in New York State (NYS), including the Direct Marketing Conference at the NYS Fruit and Vegetable Growers Expo and a recorded session for the NY Farmers' Market Federation's business planning webinar series. Additional outreach and presentations were initiated in the New England states. Additional speaking engagements and farm data collection in New England are being planned for the coming year as a result. For the first season of the study, geographic focus areas concentrated on counties in Eastern and Northern New York. Five cooperating agriculture agents were identified, where we worked collaboratively with them to identify farm candidates for participation during Summer 2012. Following initial outreach to 35 farms, 27 farms were identified as good candidates and nearly all of them were visited by project investigators, a student intern, and the cooperating local agent. While some farms subsequently dropped out of the data collection process, 20 farms were ultimately provided with study materials and data collection forms. At this stage, we are awaiting completed data materials from the participating farms to develop the individual farms marketing channel evaluation results. The results will be reported to the farms and the individual farm data will be entered into a database for eventual development of marketing channel performance benchmarks when sufficient farm-level data has been received. PARTICIPANTS: A goal was established to recruit 25 producers in New York State each year to participate in the farm visits, data collection, and marketing channel assessments. Farm owners and employees will be directly involved in the data collection by filling out labor logs at the farms and markets attended. Many more farmers and buyers participate in the farmer-to-farmer and farmer-to-buyer meetings also organized as part of this project. Farmers, extension educators, and agri-service providers were engaged through presentations at extension- and industry-related events and conferences. Matt LeRoux, project collaborator, coordinated producer recruitment, agriculture agent training, and marketing assessments. Monika Roth, project collaborator, assisted with buyer referrals, producer recruitment, and project outreach. Todd Schmit, project investigator, helped facilitate producer recruitment processes and developed a revised database structure for farm data entry and analysis. In addition to the project leaders, there were two main groups of participants for this phase of the project, the cooperating agriculture agents and the farmers who would conduct the data collection. Five Cornell Cooperative Extension agents cooperated with farmer recruitment, training, and participation. Following initial outreach to 35 farms, 27 farms were identified as good candidates, and 20 farms ultimately signed up for project participation and were provided with study materials and data collection forms. Data collected from the farms will be analyzed following the marketing season. TARGET AUDIENCES: Communication and networking with CCE associations was conducted to recruit farmer participants. An annual farmer recruitment goal of approximately 25 small and mid-scale fruit and vegetable farms throughout New York State to participate was established. Training and information sessions are organized each year to county-level CCE personnel interested in participating and recruiting local producers to participate. The target audience for the majority of our activities in the first year of the project were small- and mid- scale, diversified fruit, vegetable, and fresh cut flower farms in Eastern and Northern NY. Farms with at least 3 and no more than 6 active marketing channels (by category) were preferred. Additionally, we sought farms with 12 or fewer workers, including owners. Farms that fit this description tend to have between 2 and 35 acres in production and be growing 35 different crops. These farms also tend to focus on direct marketing channels, and are usually involved in more than one farmers' market. If the farm participates in multiple farmers' markets, we are able to track each market separately so the best and poorest performing markets can be identified. Farmer networking meetings were also held to discuss ways to improve marketing, profitability, and labor efficiency. Wholesale buyer and farmer meetings were organized to facilitate the establishment of new business relationships and entry into alternative market channels. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
The primary outcomes achieved thus far are that, through the agricultural agent and farmer recruiting activities, we have reached over 20 agricultural agents and over 100 farms. Communications with farmers has gotten them thinking more about the performance of their marketing channels and the opportunity to make a change based on data collected from their own farm. The primary message of the presentations delivered is that the main factors of marketing channel performance can be measured on each individual farm and help clarify which channels are top performers for that farm and which ones can be considered for reduced participation or elimination. The presentation puts the factors of labor requirements, profitability, volume of product sold, risk, and lifestyle preferences (compatibility) into perspective for farmers as they think about their marketing channel participation portfolio. In addition, farmer-to-farmer discussion groups are continuing to be held where marketing channel selection, new market opportunities, and record keeping for improved profitability are discussed. As a result of the discussions on channel performance and the participation of small-scale wholesale buyers in the discussions, at least one farm has entered wholesale for the first time and another has expanded their wholesale business. Both farms have completed the MCAT data collection and cited the ability to move large volumes of product at fair prices in a short amount of time as the reason they had expanded wholesale. Both farms report that they are really happy with the results of wholesaling and are making plans to expand wholesale in the coming year.
Publications
- LeRoux, M.N. and Schmit, T.M. 2012. Marketing Channel Assessment Tool (MCAT) Instruction Manual, Version 2.0.2.
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