My story about Mondavi
My name is Chloe, and I study at the University of California, Davis majoring in Master of Business Analytics program. Since last year, I have been fortunate to work with three of my colleagues on the Mondavi Center practicum team. Mondavi Center is the main performing arts center in the Sacramento region that wants to be data-driven in making strategic and tactical decisions. For example, we finished some projects like Seating Allocation, Event Profitability Analysis, and so on. 2020 is not an ordinary year for all industries, especially for the performance industry, and we mainly communicate with them through Zoom. Even though everything was not easy and we went through some winding steps, this is a learning process. I appreciate this opportunity due to experiencing many memorable projects coordinated with real-life problems. In this blog, I want to share how my practicum has contributed to my perspective on an analytics career.
The application of data analysis is so extensive that we could solve a problem like seating allocation, analyze survey text results, predict performance revenue, and so on. Seating allocation is one of the great examples. The Mondavi Center had been closed for a year and plan to reopen next year. Since most of their customers are seniors, it’s also nice to have social distance when everything comes back to the new normal. Our goal is to optimize the seating allocation of the main performance hall, Jackson Hall, to provide the best visual experience with safety concerns in mind. For this goal, we analyzed previous historical data to find that most customers came with two people, and some customers came with three people. Then we place those parties individually on the seating chart based on this proportion. To demonstrate the visual hall seating chart, we used Tableau and Excel to establish our result. In the end, we figured out that this allocated 8% more seats than we normally thought. We could not only use tools to analyze data and optimize seating allocation but also analyze text survey results. Mondavi center collected surveys on three groups of customers to evaluates the opinions of Mondavi customers toward Mondavi’s identity. After running topic modeling and bag of words on the text data, we provided Venn diagrams showing the word clouds for different customer groups on similarities and differences. After working with Mondavi center, I realize that the application of data analysis can have large impacts and provide otherwise hidden insights into business decisions. I see the potential using business analytics to solve many kinds of problems.
With Mondavi Center Arts shareholders and my team of colleagues, communication is always the key to solving problems and moving the process forward. At the beginning of our weekly meeting with Mondavi’s team, we mainly communicate with Sarah, Assistant Director of Business Intelligence. She shared with us their recent updates and what we could help them with at the moment. When we required more information, she had to ask other departments and got back to us later. It was inefficient, and we didn’t know what output they would like from us. Once, we asked to attend their internal group meetings for more information about their current status. Sarah invited us to join their weekly internal meetings with the Programming team and Marketing team. In the meeting, they went over many projects and their preliminary thoughts on them. We could ask more questions and provide possible projects of what we could do to help them reopen. Speaking with a large group fastened our process of providing what they need the most. Frequent communication with customers is an important element to decide what we could help with Mondavi, and frequent communication within our team is also essential for us to process our original thought and to provide insightful results to Mondavi. Sometimes the solutions we have come up with don’t work out for reasons, so we should always communicate and find an alternative method to make sure we could deliver our insights on time. Effective communication with clients and team members will help move the project forward and deliver quality projects.
Working with a real-life company, I learned that we have to always consider biases and risks associated with collecting data and analyzing results. For our Organizational Identity Analysis, we sent out customer surveys to collect sentiments from our customers, and this is prone to response bias. The identity analysis aims to find out how Mondavi is perceived by different groups of customers. Each respondent answered the survey question “Mondavi Center is__” up to ten times. People who were willing to take the survey tend to think highly of Mondavi, and thus most of them gave positive responses. Additional, survey questions are too vague to have an accurate answer, so some of those results deviate from the main point. All biases reduced the quality of the analyzing result. We have to design a unique survey for a small group of survey participants to high-quality data. Besides data biased, we also have to think about potential risks as well. When we designed the prototype for Event Profitability Analysis, one of the biggest assumptions we made was that our models are build using the past five years of data on best-selling shows. Consumer behavior could be completely different after a year of lockdown. We understood the potential risks of shifting in customer behavior and presented them to shareholders when we delivered the final presentations. Before we start analyzing a project, we should acknowledge the quality of data and potential risks before concluding decisions.
Throughout a year of working with Mondavi, I gained a lot of valuable work experience, including working as a Data Analyst and communicating as a CRM. I earn more knowledge of working with shareholders, and I appreciate this chance provided by the UCD MSBA program. At the same time, I am fully confident about my future work as a data analyst.
