10 data analytics success stories: An inside look

Here’s how leading CIOs are successfully tapping data analytics and machine learning to achieve business goals.

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Lessons learned: New enterprises require a high-level commitment, though O’Brien admits some of his business peers were ready to throw in the towel at various points along the way. The business didn’t trust the technology for a process that was typically done by feel and guesswork. RRD set up a collaborative environment in which business and IT worked together to influence the outcome. “You will stumble, you will have challenges, but be patient,” O’Brien said.

Monsanto taps machine learning for optimal planting

Farmers are forever agonizing over which seeds to plant, how much, where and when. Seed giant Monsanto is on the case, using data science to make prescriptive recommendations for planting by leveraging mathematical and statistical models to plot the best times to plant male and female plants and where to plant them, ideally to maximize yield and reduce land utilization. Its machine learning algorithm churns through more than 90 billion data points in days, rather than weeks or months, says Adrian Cartier, director of global IT analytics at Monsanto. The business benefits? In 2016, Monsanto saved $6 million and reduced its supply chain footprint by 4 percent. “In North America, a 4 percent land utilization reduction equates to a lot of land not being used and a lot money saved,” Cartier says.

Lessons learned: The key for Monsanto was instilling a “cradle to grave” collaboration between IT and the supply chain business. "Their domain expertise from an agricultural and supply chain perspective, married with our domain expertise of mathematics and statistics created the value that we were able to deliver,” Cartier says, adding that he also sought out “change leaders and advocates” within the supply chain business to offset the healthy balance of naysayers.

For Pitt Ohio, predictive analytics delivers success

The freight industry is under fire from the “Amazon Impact,” says Scott Sullivan, CIO of Pitt Ohio. Pitt Ohio, a $700 million freight company, had gotten used to picking up freight and delivering it to customers the next day. But thanks to Amazon, customers are increasingly expecting same-day delivery. And they expect more information about their packages.

“Customers now want to know not only when it will be picked up but how it will be delivered so they can plan their workload,” Sullivan says. Using historical data, predictive analytics and algorithms that calculate a variety of freight weight, driving distance and other factors in real time, Pitt Ohio can estimate the time the driver will arrive at a delivery destination at a 99 percent accuracy rate. The company estimates that it has increased revenue through repeat orders (estimated at $50,000 per year) and reduced the risk of lost customers (estimated at $60,000 per year).

Lessons learned: Sullivan says it was a cross-departmental affair involving market research, sales operations and IT, all of whom checked and re-checked results to make sure they were accomplishing their objectives. “There’s a lot of data within your four walls — be innovative and look for challenging ways to use it,” Sullivan says.

Copyright © 2018 IDG Communications, Inc.

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