Farmers make an average of 40 growing decisions each season – from what to plant when and with what seeds, to when and how much to irrigate, to when to harvest.
Taking the guesswork out of those questions – offering answers based on reliable models and scientific research – becomes an invaluable service.
“As an agriculture company that develops products and tools that allow farmers to efficiently grow crops while decreasing energy, water, and land use, Monsanto not only can – but should – use our scientific research to answer our partners’ questions,” said Monsanto CIO Jim Swanson. "In fact, we need to be able to efficiently answer questions about all aspects of our business. And that’s why data science is core to our mission.”
Swanson cited Monsanto’s Transportation Management System (TMS) as an example of how data science supports the business. TMS is an end-to-end logistics solution that combines real-time monitoring, process automation, analytics-based decision making and standardization to consolidate transportation routes in Brazil, Europe, North America, Latin America, and Asia. By optimizing efficiency, TMS maximizes truck utilization and reduces the amount of lost product, while also improving the customer experience by providing proactive notifications and delivery status updates. TMS is on track to deliver annual savings and cost avoidance of nearly $14 million, while simultaneously reducing 300,000 miles and 350 MT of CO2.
Swanson noted that TMS is enabled not just by data, but by an organization that has embraced a digital transformation.
The Transformational Beginning
Monsanto started its progression from an agricultural biotechnology firm to a data science-driven organization more than a decade ago, with the pace of the transformation rapidly increasing over the last four years. The change has impacted all components of the business from how Monsanto develops products, to implements processes, to how it serves its customers.
Swanson acknowledged that getting to the point where data science drives business decisions took a huge culture change across the organization.
The shift began at the senior level.
“About four years ago, Hugh Grant (Monsanto’s former CEO) and other senior leaders started acknowledging both internally and externally that data science is not just enabling the business, it is a central part of agriculture,” said Naveen Singla, Monsanto’s Data Science Center of Excellence Lead. “Our senior leaders stressed that data science is not just a curiosity, it is a mainstay of our products.”
A first step in the digital transformation was to shift the workforce to be more data driven. Over the past two years, the data science community at Monsanto has grown from about 200 to more than 500 people. But these are not all new hires, or even traditional data scientists. Singla notes that Monsanto found training existing employees in data science methodology allowed employees to transition into new roles that still utilized their skills and domain knowledge.
“If we had simply hired a data engineer or statistician, it might have taken that person six months to a year to understand the business,” Singla said. “Instead, we have biologists, process chemists, etc. who have learned data science methodology and are now doing data science or managing data science teams in those respective areas.”
The second step is what Swanson likes to call “data democratization.”
“Data democratization was a call to action from our executive leadership to recognize that the data we use is not an individual person’s data, or even a department’s data,” Swanson said. “The data is the company’s data.”
Monsanto leaders recognized that data must be available for all to use. They tore down data silos and promoted sharing across the company. They organized data around five salient categories: products, locations, customers, company information (typically Finance- and HR-related data) and IoT data. By connecting data in these five buckets, it became easier to both extract and connect data across Monsanto.
Shared data is at the heart of Monsanto’s smarter supply chain, which uses data science to optimize seed production. By incorporating a variety of factors, such as customer demand variability, supply forecast, crop placement, and environmental variations, Monsanto has created a standardized, automated, and robust field production forecast that covers the entire season – from pre-planting to harvest. Monsanto benefits from improved optimization while customers benefit from Monsanto’s ability to provide improved planting decisions and supply planning.
Data Science Center of Excellence
Another key step in Monsanto’s data-driven transformation was to connect data scientists across the company. When the first data scientists at Monsanto were hired more than a decade ago, it was for work within specific groups, such as biotechnology or breeding. At that time, the data science efforts were disconnected, and the few data scientists in the organization were unaware of each other and the work being done. As Monsanto realized value from early data science successes, the number and groups of data scientists grew dramatically and Monsanto took several important steps to break down the silos and unify data science across the company.
One of these steps towards this unifying strategy was the creation of the Data Science Center of Excellence (DSCoE), which Singla leads. Through the DSCoE, data scientists work closely as they develop on a single platform. “In addition to increasing awareness of one another’s work,” Singla said, “the close collaboration through the DSCoE has increased the rigor of the work while accelerating its pace."
Improved scale and speed are apparent in Monsanto’s corn R&D pipeline. Using more than a decade of data, Monsanto researchers are using a machine learning-based product to help accurately predict how thousands of seeds will perform their first year in the field. This enables them to evaluate approximately five times more corn varieties than in the past, saving hundreds of hours of research time.
One of the ways to improve the connection of data scientists to each other and the business was to increase the digital literacy of the entire organization. Monsanto partnered with Coursera and DataCamp to develop a learning platform that could help improve the digital acumen of all employees. Through the learning platform, employees are encouraged to explore online programs in R and Python, as well as others.
In addition, Monsanto encourages employees through regular internal events. Singla said that during one of last year’s hackathons, where groups focused on a molecular breeding problem, people NOT related to the work came up with the idea that now has been adopted in the lab.
“Monsanto reaps immeasurable value by exposing people to new technologies to solve problems,” said Singla. “Combining diverse backgrounds and thinking in our models often allow us very creative outcomes.”
The “Notion of Experimentation” is the final step of Monsanto’s digital transformation. About three years ago, Swanson’s IT organization adopted an agile approach to software development. The agile approach incorporates iteration, feedback, and continuous improvement. That same mindset also is true for how data science is incorporated into business decisions.
“We continually bring experimentation into the process,” Singla explained. “We listen to and learn from our customers – whether it is our colleagues within the organization or the farmers in the field. Based on what we learn from them, we redefine.”
Utilizing a wealth of new data opportunities to improve the customer experience is a tenet of Climate’s FieldViewTM platform. Farmers – whether by hand or electronically – log data. Climate’s tools allow farmers to optimize their data, uncovering new insights that support a successful harvest. Decisions are no longer based on field-by-field assessments; instead they are moving toward foot-by-foot data collection and analysis.
A Transformational Journey
While both Swanson and Singla are pleased with the progress Monsanto has made, they both remain passionate about the impact data science will continue to have. Swanson cited a rapidly growing world population, combined with the challenges of climate change, for the continued push to leverage data science in agriculture.
Singla shared how Climate is using artificial intelligence to diagnose corn diseases in the field. The machine learning model is diagnosing nine key corn diseases – with a very high probability of success – using more than 50,00 disease and stress images. With this capability, a farmer could take a photo of a crop, receive a disease diagnosis, and take action before the disease impacts yield.
“Using predictive modeling and analytics has allowed Monsanto to extend our research further and faster,” Swanson said. “From predicting consumers’ preferences in product flavors to working with climatologists to model how the evolving climate impacts farming, we want to invest now in the products farmers will need 10 or 20 or 30 years from now.”
About the Authors
Jim Swanson James (Jim) Swanson is Chief Information Officer for Monsanto, a leading sustainable agriculture company focused on helping farmers grow better harvests while conserving natural resources, such as water and energy. Jim leads a global team of over 1,000 information technology employees for the company’s operations, which span about 60 countries. Jim is responsible for enabling Monsanto’s digital transformation to an information-based company and delivering IT capabilities across all of Monsanto’s global business. The Information Technology organization has been recognized externally for contributions to Monsanto’s business through data science and digital transformation as well as supporting the development of emerging IT talent.
Prior to joining Monsanto, Jim held executive and scientific roles at Merck, Johnson & Johnson and SmithKline Beecham. He holds a Bachelor’s degree in Bioscience and Biotechnology and a Master’s degree in computer science, both from Drexel University in Philadelphia.
Naveen Singla Naveen Singla is the Data Science Center of Excellence Lead and Director of Analytics at Monsanto, working with talented and inquisitive people to transform the world’s oldest profession: agriculture. He has more than 10 years of experience finding meaning in data for applications in the areas of agriculture, biometrics, and high-frequency stock trading. During his tenure at Monsanto, he has helped grow the value realized from data science to establish a data-driven mindset by developing strategies, influencing leaders, and implementing solutions all towards the goal of improving food security. In 2018, Naveen was awarded the Ones to Watch award from the CIO and the CIO Executive Council.
During his Bachelor’s study in Electrical Engineering at the Indian Institute of Technology (IIT) in Delhi, India, he was inspired by Claude Shannon’s ideas on transmitting information on noisy channels. He completed his PhD at Washington University in St. Louis in the same field.