Deere & Company is the Moline, Illinois, manufacturer of iconic John Deere farm tractors and other heavy machinery. It makes most of its US$26 billion annual revenue in the traditional way, by selling or leasing equipment to farms and construction firms.
Yet, this conservatively managed firm launched digital platform myjohndeere.com in 2013 to forge a direct connection with farmers. Originally established to give John Deere equipment owners access to spare parts and other company offerings, myjohndeere.com is providing the company with another rich source of potential income: big data.
For example, Deere has installed internet-enabled sensors on its tractors to record and transmit data on fuel consumption and other metrics useful to farmers. Deere also sells monitoring equipment called Field Connect, which collects additional data on soil moisture, temperature, wind speed and rainfall. The data from the sensors is then made available to farmers on the platform.
“We’ve never had that data before,” said Geoffrey G. Parker, a professor at the Thayer School of Engineering at Dartmouth College in Hanover, New Hampshire, who has studied the Deere platform and co-authored Platform Revolution: How Networked Markets Are Transforming the Economy and How to Make Them Work for You. “Think of the tractor like a Mars rover capturing data.”
The primary use of the farming data, Parker said, is to help individual farmers improve productivity on their farms. But the data also could be a valuable commodity in itself for agricultural companies, which could use the data to shape their investment strategy. “If Deere aggregated data across enough farms and sold the data stream, it would give a pretty good idea of what is going to happen in next year’s agricultural output, which puts one at a huge financial advantage,” Parker said.
“EVERY NEW SERVICE IS GOING TO GIVE YOU MORE DATA, AND THE MORE DATA THAT YOU HAVE WILL GIVE YOU A BETTER UNDERSTANDING OF WHAT’S ACTUALLY HAPPENING, ENABLING PEOPLE TO CREATE ENTIRELY NEW SERVICES.”MICHAEL BLITZ
MANAGING DIRECTOR, ACCENTURE TECHNOLOGY LABS
PROCESSED AND ANALYZED
As the Deere example suggests, decades-old firms with well-established business models now have the potential to use platforms not only as a showroom for their products and services, but as a source of detailed data on users. Collected via the Internet of Things (IoT) and analyzed by artificial intelligence (AI) algorithms, the data itself becomes a valuable source of business insights.
“The potential to share customer data with other parties is part of the advantage of platforms,” said Michael Biltz, managing director of Accenture Technology Labs in San Jose, California. “Companies realize pretty quickly that the data they are collecting has more value to other partners than it does to them.”
Biltz cites the example of health care companies that collect hospitals’ electronic medical records about diseases, as well as the tests conducted and pharmaceuticals used in treatment. While that data is potentially valuable to the hospital, it is even more valuable to drug companies doing research on the effects of different drugs, conducting clinical trials or trying to understand trends in health care.
“Every new service is going to give you more data, and the more data that you have will give you a better understanding of what’s actually happening, enabling people to create entirely new services,” Biltz said.
Sangeet Paul Choudary, co-author of Platform Revolution, who runs a platform consultancy in Singapore, cited the example of a large banking client which set up a real-estate platform to help homebuyers navigate the process of purchasing a home, comparing listings for houses with information about nearby schools and neighborhoods. The bank was able to use the data it collected from the website to target mortgage offers for those couples buying a home.
Choudary notes that the mining industry is also using digital platforms. Combining data from sensors on mine vehicles with prospecting data taken from specific mines, it then can share that data with other companies. “The idea is to look for clumps of data that you can open up to complement a set of competitors. That’s one way in which mining is moving toward multisided platforms,” he said, referring to platforms in which two or more groups of users and producers are brought together to interact.
Many companies may find the process of collecting data and then analyzing it to be more than the company can profitably handle. In such cases, data companies may step in to offer analysis services.
“With the increased ability to connect on platforms and the increased ability to analyze data, you’re going to see companies emerge that find the right business models to put these two things together to create value,” said Annabelle Gawer, co-director of the University of Surrey’s Centre for the Digital Economy at the Surrey Business School in Guildford, England.
Peter Evans, the principal for Innovation Enterprise Solutions at consultancy KPMG in greater Atlanta, said that digital platforms are in a particularly advantageous position to benefit from AI, sophisticated algorithms that not only analyze data but continuously improve their analysis by learning from what they analyze. Major Chinese platform firms, for example, are investing heavily in AI technology, particularly “machine learning” technology.
“Their business model is very geared toward collecting data and facilitating interaction,” Evans said. “Machine learning loves big data pools and the ability to go in and facilitate insights through behavior that you can further enhance. I’m seeing lots and lots of platforms gravitate toward artificial intelligence more quickly than other companies.” ◆