A research opportunity presented itself when my management professor reached out to a couple of students, including me, about an agriculture survey that needed help analyzing data. This agriculture survey was sent out to southern Minnesota farming businesses about the past year. This survey was working with survey responses and focus group work in collaboration with Greater Mankato Growth’s GreenSeam. I didn’t know anything about agriculture, and initially, I didn’t necessarily feel very interested in the topic, but I wanted to get more experience in analyzing data and trying new things. The central research question I aimed to answer was: How has rising costs and economic drivers specifically shifted business performance for Southern Minnesota agriculture in the past year? By focusing on this question, I was able to turn a topic that I only knew a little bit about into a project that challenged me to face my fears, develop professional skills, and gain hands-on experience in how to effectively analyze and interpret real-world data.

            I set up a meeting with my professor to talk it through. First, I had to complete the Collaborative Institutional Training Initiative Program, which provides the training needed to ensure that all investigators and research study personnel who collect, access, and analyze data can do so legally. I would have to analyze a set of questions, research what the data means, make a PowerPoint presentation, and then present it to a crowd of about 50. In order to select a group of questions, I was given the entire survey and selected data that was looking a quantitative data and the business’s performance. I was excited! It was nothing I had done before, and what scared me most was public speaking. I am not very comfortable presenting to a crowd of people that I don’t know, but that was what was required, so I had to face my fear.

            I completed the certificate for the CITI training, which was a lot of modules and videos about the rights and wrongs of research. I learned about ethical research practices and the foundations of research, which involved human subjects, animals, and sensitive data. I also learned about the responsible conduct of research, which included integrity in data collection, analysis, reporting, and production. I acquired the best skills for managing and securing research data to ensure accuracy, confidentiality, and integrity. Overall, this process helped me prepare for my project because it equipped me with the knowledge to carry out my analysis with morality and professionalism. I felt confident in summarizing the data because I knew the proper criteria. This knowledge was essential as I began my two-month analysis phase, where I aimed to answer my core research question: How have rising costs and economic drivers specifically shifted business performance for Southern Minnesota agriculture in the past year? Using Excel, I began summarizing the quantitative data into clustered columns and bar graphs. This was definitely a process of trial and error. A big success that I had was using data visualization to show the contrast between large and small businesses, as well as the impact of rising costs. However, a technical failure I encountered was overcomplicating my initial charts. Some of the variables, like projecting performance and describing performance, were too similar to compare on one chart. I had weekly meetings with my professor to cover any questions I had and to make sure that I was on track. With some of my setbacks, my professor helped me realize effective research requires intense focus on the kinds of variables to use and the most impactful indicators, like performance metrics: high growth and sharp decline. I was nervous throughout doing this because I was unsure if I was making the right inferences about the agriculture industry, but with the reassurance from my professor, I felt a lot better.

            The most challenging but interesting part was to go through the short answer questions. For example, there were over 200 responses to one question, and I had to figure out what the overall themes were and summarize the data. I used Word Counter to input the responses, which made the most common words larger. This helped me identify what themes were most prominent and helped me narrow it down. It also created a challenge because, just because the words were larger, I didn’t know what they symbolized. So, although it created a success in speed, it was a failure in context. While the tool showed that words were like “costs”, “increase” and “labor” were frequent, I didn’t understand the reason behind them. To fix this, I manually coded the data by copying the short answers to a document and searching the most common words that I had found in Word Counter. I read every answer with the “searched” word. I then identified the theme I could create. Throughout this process, I identified three themes. The first theme was the “margin squeeze” that many businesses were facing because of the rising input costs. The second theme was the difficulty of navigating new labor laws. In the survey question, “How do the following economic drivers affect your business’s ability to grow, 10 being most impactful and 0 no affect?”, there were many “Other:” responses that said government regulations were a major reason. The last theme that I discovered was the institutional barriers to growth. Policy, laws, and regulations were ranked a higher threat to businesses’ growth than even inflation. It was important that I included and addressed almost every response. Even if they aren’t as frequent, all data is important. The businesses that responded to the survey were large businesses or smaller, so they had different opinions. I was successful after repeating this process for all short-answer questions. I liked doing this because I was learning more about how rising costs were affecting these contrasting businesses, and some answers were very opposite. I also had the chance to learn more about Excel because I understood which graphs portray the data selection the best. I would research what the best graphs are for displaying certain types of data because I hadn’t worked in depth with Excel in my other classes. I found that using stacked bars was best to show how different economic drivers contributed to the margin squeeze. I also used bar graphs for ranking regional conditions.

            I had finished my PowerPoint, and I met with my professor. This is where I faced a setback. We made a lot of changes. I felt embarrassed that I didn’t do some things the right way. But this was a learning experience. I had too many words on the slides, and some graphs included data that didn’t need to be in there. I learned that the simpler the graph, the easier it is for the audience to understand the data. Even though it made sense to me, the audience would be confused. We rehearsed the presentation about once a week for 3 weeks, and the nerves were starting to kick in. I was grateful my professor would be up on stage with me, and it made me feel a lot better.

            The day came when I had to present, and I just felt relaxed. I wasn’t frantic and I had confidence in myself. I arrived at the venue, and it seemed like a large crowd, which started to scare me a little. The people who were coming to the presentation were business farmers who filled out the survey, town mayors, people on the Minnesota Department of Agriculture board, professors, and researchers. It was an audience of about 40. The goal of this study was aimed at discovering how agriculture has improved or receded over the past year. It compared the data with 2023. Businesses that were attending were curious about how inflation, laws, and taxes were affecting their businesses. I was sitting at a circle table up front, and my professor spoke first. She introduced the data and what the survey was all about for 30 minutes and then it was my time. She introduced me and there was a small applause as I walked to the stage. I talked for about 15 minutes about business performance in 2023, predicted future performance in 2024, and the impact of economic drivers on businesses and regional conditions, and lastly examples of the impact of rising costs that businesses are facing. I used my slideshow to show the graphs I prepared. It was important for me first understand the “why” and purpose to this research. Once I understood how this information affected the crowd (inflation, law, taxes), I knew how important my presentation was. It made me present with care and curiosity. Understanding this information empowers the audience to make more informed decisions, allocate resources effectively, and respond strategically to changing market conditions. This would be very useful to the businesses in the audience to improve their business performance, economic stability, and sustainable growth. The presentation went very smoothly, and the audience was receptive to my data. It wasn’t open for the audience to ask questions until the very end of the presentation which in total was about 3 hours long. Although I felt I talked a little fast, I had people come up to me after the entire presentation congratulating me and saying I did very well.

          I enjoyed this experience because it challenged me to learn something new and face my fear of public speaking. As a finance major, this project adds to my knowledge of how to organize data most efficiently. I will be able to apply this learned experience in future encounters with financial data. I took away the knowledge from my CITI training which I can use in my next project. I know how to manage data with security, understand ethical principles, and I know how to address the responsible conduct of research. What I learned about myself was work habits and discipline. To complete this effectively I needed to work on it every week. I can tend to procrastinate but with weekly meetings with my professor, there was no choice but to make sure I worked on it every week. I also learned about my interests. I never knew much about agriculture, but I learned that it was so much more than just farming. It is about supply chain management, distribution and logistics, and labor laws. I am planning on attending law school and learning about agribusinesses sparked an interest that maybe I would want to go into agriculture law. With this experience, I know so much more about research and how to convey data to a crowd. I can use this experience in future settings because I found ways to innovate and be creative, manage, analyze and interpret data.  It increased my communication skills and networking opportunities for future professional settings. For my next research opportunity, I will be able to know how to explain data in the most efficient way!