Abstract
Optimization is a driving force behind engineers’ pursuit of improvement. One desired outcome of optimizing a system is improved efficiency through better performance at a lower cost. In vineyards, actionable data from a low-cost system can improve the ability to manage crops in a way that best improves their performance. In baseball, “datafication” has engulfed many critical aspects of the game – from tracking every step of a player to analyzing the success of managers and the front office. Vineyards and baseball are fundamentally different operations – one centered around growing grapes and the other focused on talent management of athletes. My theses differ in their approach of looking at how utilizing data has affected baseball in the past and how utilizing data can affect the management of vineyards in the future. However, my theses are related by looking at how harnessing the power of data can optimize a system by maximizing the cost-efficiency of an operation. Moneyball has well-documented effects on the approach to baseball both on and off the field at both the player and management levels, while vineyards currently rely on limited data to make key decisions. My approach to my theses is related through an analysis of how management can use data to optimize key decisions.
As mentioned, many vineyard managers currently rely on limited data and their past experiences in the field to make key decisions about frost prediction, pest and disease prediction, and irrigation optimization. Considering that soil conditions and microclimates vary significantly within a single vineyard, this lack of data prevents them from precisely managing their vines. The technical thesis focuses on developing an effective and cost-efficient monitoring system that collects spatially-granular data within a vineyard. By engaging stakeholders in iterative prototype development, our team discovered that high-density networks of Long Range (LoRa) wireless communication technology could cost-effectively provide vineyard managers with the appropriate data to improve their key decisions and optimize the management of a vineyard.
The STS thesis analyzes the revolutionizing effects of Moneyball on player salaries, in-game and off-field approach to baseball, and organizational management with the Actor-Network Theory framework. By reviewing literature, testimonies, and data, I set out to understand how Moneyball, the data- and statistically-driven approach to baseball adopted by the Oakland Athletics in 2002, transformed the game of baseball as an effect of the relationships and tensions between actants and communities. I discovered the profound effects Moneyball had on the relationships between players and management and the negotiation between the baseball and data communities. Moneyball analytics and the translation of these tools from one team to another could help propagate the notion that analytics is not just helpful, but completely viable given both the ease of access to baseball’s wealth of data and the ease of adoption of the analytical tools.
Acknowledgments
This work would not have been possible without my family, professors, and friends Ben Carper and Tyler Sudbrink. I am beyond grateful for their support, inspiration, and guidance throughout my academic career.
