Monsanto Predicting Weather: Crazy or Crazily Smart?

Farming in face of climate change? Monsanto bought a weather predicting technology to manage supply chain risks.

How is Monsanto impacted?

Monsanto is a Missouri-based agricultural biotechnology company that produces genetically engineered seeds. It has a 18 month supply chain cycle, which means that in Q1 of Year 1, the company needs to plan for the customer seed demand in Q3 of Year 2 (taking into account the time to grow and harvest the seeds for selling). Because of this long supply chain process, demand forecasting is critical to its planning and risk management processes. [1]

Weather is one of the biggest drivers of demand forecast accuracy, in addition to acres and seeding rate. More than 70% of a farmer’s decisions are influenced by weather. [2] For example, if the growing season encounters drought, it’d in Monsanto’s interest to drastically increase seed planting in anticipation of supply shortages. Climate change in the recent years has severely impacted the company’s ability to predict demand accurately, which translates into increases in cost. With the growing competitive pressure in the agricultural inputs business, customers are becoming less willing to accept costs that result from inadequate supply chain management. [1] As such, Monsanto has taken active steps to respond to both the rapidly changing market conditions and the growing supply chain risk that comes along with climate change.

What is Monsanto doing?

In 2013, Monsanto spent $1Billion to acquire Climate Corporation, a company that uses machine learning to predict weather and other elements driving demand of agribusiness. Since its launch in 2006, Climate Corp built a data-driven platform that combines weather and yield data to predict the impact of weather on crop yield predictions. When Monsanto first looked into this acquisition, skeptics expressed concerns about the viability of weather prediction. However, Monsanto saw a future wracked by climate change and took an early action to manage future supply chain risks. In the recent years, increasing number of agricultural companies are taking similar steps to better leverage big data (including weather prediction technology) to manage supply chain risks affected by climate change. [3]

The Climate Corp acquisition marks one of Monsanto’s steps into big data analytics. To improve its supply chain management in the medium term, Monsanto continued to introduce a series of big data tools (e.g., SmartForecasts Enterprise) to improve demand forecasting and inventory optimization. [4]

What else should Monsanto consider?

While the acquisition of data analytics tools is a smart move, tools alone are insufficient. Monsanto needs to adjust its culture and organizational structure to ensure its managements can appropriately use these tools in decision making. In fact, cultural inertia can be one of the biggest roadblocks to operations improvement via big data. [5]

First, executives who are used to relying on business judgement in decision making may embrace the tools on the surface but stubbornly resist using big data in real decision making. Second, management and working teams may have this belief that predictive platforms needs to be 100% or they cannot be trusted. As we saw in IBM Watson case, the standard for errors is a lot higher for machines than humans. Lastly, if predictive analytics tools (e.g., Climate Corp, SmartForecasts) were to be used to improve supply chain, organizational structure needs to be considered to integrate analytics and traditional supply chain departments. In sum, Monsanto cannot neglect the amount of change management required to ensure that its acquired predictive tools are truly used and embraced by its management / working teams. [6]

What are the ethics of Monsanto’s big data usage?

Monsanto’s move into big data undoubtedly improves its supply chain efficiency by allowing the company to better predict and track its customers’ demands. However, it also creates a power asymmetry between this large agribusiness and its customers (the farmers). Monsanto’s ability to amass huge quantities of data to generate insights creates informational advantage over farmers and allows it to gain more negotiation power over them. [7] For example, not only does Monsanto plan to use the weather predictive tool for internal supply chain management, it also plans to commercialize the technology by selling to farmers to enable them to grow crops in changing climate. This then allows Monsanto to collect a massive amount of data from its farmers. [8]

How can we ensure that data is used equitably (e.g., not as a way for Monsanto to squeeze profits out of farmers)? What are the ethics of big data commercialization by large conglomerates? If Monsanto were to sell the weather predictive technology to its farmers, should it exploit farmers’ maximum willingness to pay? Or leave it free and see it as a way to fulfill corporate social responsibility? These ethics-related questions apply to many large conglomerates moving into big data but they are particularly interesting for Monsanto because over the years it has already weathered a large amount of negative publicity for its GMO products.

 

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[1] Stephen C. Graves et al, “Optimizing Monsanto’s Supply Chain Under Uncertain Demand“, Semantic Scholar (1997) https://pdfs.semanticscholar.org/9c35/5c0f080f60a361c477e5aa35b63cc1fda455.pdf

[2] Eugene S. Takle et al, “Climate Forecasts for Corn Producer Decision Making“, U.S. Department of Agriculture: Agricultural Research Service (2014) http://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=2416&context=usdaarsfacpub

[3] Megan Stubbs, “Big Data in U.S. Agriculture“, Congressional Research Service (2016)https://fas.org/sgp/crs/misc/R44331.pdf

[4] John Comando, “Monsanto Selects Smart Software’s SmartForecasts to Improve Forecasting Process“, BusinessWire (2004) http://www.businesswire.com/news/home/20040225005095/en/Monsanto-Selects-Smart-Softwares-SmartForecasts-Improve-Forecasting

[5] Murli Buluswar et al, “How companies are using big data and analytics“, McKinsey & Co (2016) https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/how-companies-are-using-big-data-and-analytics

[6] Randy Bean, “Why Cultural Change is Necessary for Big Data Adoption“, Forbes (2016) https://www.forbes.com/sites/ciocentral/2016/11/08/another-side-of-big-data-big-data-for-social-good-2/#690032c86628

[7] Isabelle M. Carbonnell, “The Ethics of Big Data in Big Agriculture“, Journal on Internet Regulation, Policy Review (2016) https://policyreview.info/articles/analysis/ethics-big-data-big-agriculture

[8] Dan Mitchell, “Why Monsanto Spent $1 Billion on Climate Data“, Modern Farmer (2013) https://modernfarmer.com/2013/10/monsanto-spent-1-billion-climate-data/

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6 thoughts on “Monsanto Predicting Weather: Crazy or Crazily Smart?

  1. Wonderful commentary and questions.

    In particular, the ethical considerations surrounding Monsanto’s use of big data parallels concerns in other industries, such as healthcare. At times, big data is hailed as the omnipotent solution to varied problems that the end-consumer (or patient) faces, but too often we see that this data drives further information asymmetry.

    For farmers, the value of ClimateCorp and SmartForecast come at a price that may be less than leaving farming altogether and shunting more food production to larger and larger agricultural firms whose growth is driven by land merging through acquisition. This only heightens the issue that monoculture crop production poses to US and international food scarcity. At this point, there may be no alternative other than relying on genetically-modified Monsanto crops to feed us out of human-driven climate change. While Climate Corp may help inventory optimization and supply chain management, it’s unclear whether it will truly benefit farmers’ crop yields.

  2. I really liked how you ended the article by posing very thoughtful questions on the rise of technology, big data and how it seems to fuel further big business to continue their almost monopoly of the sector. I propose this is where the public / non-profit sector can come in and pressure companies like Monsanto to share their data. One scenario could be for advocacy organizations to raise public awareness of the power they are holding through big data. With the rise of social media, hopefully this can amass enough people power to alert political leaders who will inevitably respond especially since agriculture is such an important and political business. In short, companies like Monsanto certainly need more accountability given its size, which can be further fueled through big data.

    From Monsanto’s perspective, I would also urge that on top of weather predictors whether they are investing into technology that provides more sustainable farming. If they are, that would be ideal, given that the rise of climate change is in partly due to big agribusiness and how they have disrupted natural cycles as well as many other factors of course. Hence, this use of new technology would be best if they can also see how to fundamentally change their farming ways to become more sustainability and environmentally friendly.

  3. Great post and interesting to learn how Monsanto is investing in and using machine learning to weather. The company seems it be preparing for climate change in a number of ways. First by creating seeds that are more resistant to harsher climates and now to making decisions around when and how much to plan based on big data analytic forecasts of weather. In the future, companies like Monsanto or farmers in general may consider using technology that enables them to manipulate the weather. Although quite effective, this technology as it works today, tends to be very bad for the environment. I wonder if Monsanto has anything in its R&D pipeline to manipulate weather for the agriculture business.

  4. Great read and very à-propos given the recent decision to postpone the Bayer-Monsanto merger. On top on the big data, this merger would significantly increase the asymmetry you mentioned, between large agribusinesses and their customers. To build on Ketty’s comment, it does seem like Monsanto is currently trying to find ways, through technologies, to limit the impact of climate change on its supply chain but I would like to see them launching initiatives to actually reduce their own impact. I am worried that this merger will shift the focus on financial and synergy matters and postpone/delay any sustainability efforts that they had launched or planned to launch.

  5. Amia – I am fascinated by this topic! I appreciate the questions that you raised near the end. My concern about Monsanto selling the predictive weather data to farmers, as you allude to, is that it the farmers will be no better off. I am not convinced that the predictive analytics will help increase farmer yields given that weather is likely hard to predict within a degree of accuracy that would translate into substantial yield gains. Furthermore, even if it does increase farmers’ yields, if Monsanto makes farmers pay for such information, I wonder if the earnings gains from increased yields would outweigh the costs for access to the data. I would say that this initiative would be ethically sound if it had the potential to save a farmers’ entire annual harvest from an extreme weather event, but it is not clear if the Climate Corp platform has that capability.

  6. The shift into big data seems like the perfect fit for Monsanto. These ethical questions are quite interesting given the context of Monsanto’s GMO products. Here, however, there seems to be less opportunity for the monopoly power and price-gouging that accompanied Monsanto’s seed products. With those products, a farmer has to buy Monsanto’s seeds and accompanying pesticide, and must do so every year. Weather information seems much less sticky: any farmer can take weather measurements and share the results of their crops. The shareability of this data means that Monsanto’s weather data advantage is less defensible. This makes big data more ethical, because it reduces the pressure on any individual farmer to share data with any individual company: farmers have the choice about which data provider they want to work with.

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