Getting Smart With Big Data

How smaller companies are becoming increasingly sophisticated about analyzing multiple forms of data.

May 10 2013 by William J. Holstein

IBM’s Advice to Mid-Sized Company CEOs

Ed Abrams, IBM’s vice president for the midmarket and the company’s top official concentrating on small and medium-sized companies, offers these tips on how to proceed with analytical projects.

“Your first step is identifying areas of future growth. Where is the opportunity going to come from? Then, work with IBM and business partners and your Information Technology staff to unlock the insights that are in the information you are already collecting. Chances are, you have a ton of information and you don’t know you’re collecting it, say, from mobile systems being used by the sales force.

“Working with our partners is the way most CEOs in this segment want to work. They want to work with someone local, who knows them and knows their business. They don’t want to get lost in a big company. Our resellers have real expertise in that regard.

“How do you put it together in a way that makes sense for you? The smart answer is to start small and grow. Take pieces of the information you have at your disposal to start this process. What often makes these analytic projects difficult is that a CEO will try to solve for everything at once. Our advice is, start with an aspect of business. Build, learn, develop and identify the things that work for you; then build off of that. Don’t go in and say, “I’m going to build a giant data analytic group within my organization.” Start with simple dashboards that give you insight into what you’ve already got.”

Desert Mountain Uses Data Analytics to Keep Golf Courses Green

The Desert Mountain golf club has a unique set of challenges. As the largest private club in the U.S., it boasts six 18-hole courses designed by Jack Nicklaus and needs 1.2 million gallons of water each night to keep the courses in tip-top condition. But the club is located on 8,000 acres in Scottsdale, Arizona, where water and the electricity needed to distribute it are in scarce supply and therefore very expensive.

Desert Mountain, with $63 million in annual sales, turned to technology to help address the challenge. It bought IBM Intelligent Operations Center software for $150,000 that allows it to analyze data from individual sensors located on all six courses about levels of humidity in the soil. The system is still being rolled out, but each course has as many as 1,000 sensors because different species of grass and other plants require different levels of moisture to survive and thrive. On 10-minute intervals, the sensors transmit their findings wirelessly to the club’s operations center, and employees also transmit findings from hand-held devices as they survey the courses and its lakes.

The system crunches both the structured and unstructured data—such as weather forecasts—and helps managers make decisions about which individual sprinkler heads on which courses need how much water each night. The water is recycled waste-water purchased from the city of Scottsdale. It is dispersed at night because that is when electricity is cheapest. Altogether, Chief Operating Officer Robert Jones estimates that the total cost of equipping each course with this system is about $250,000, including elements like the advanced sprinkler systems, sensors and wireless transmission gear.

But over the course of a mere three years, Jones reckons that the investment will pay off. “It represents millions and millions of dollars if we can control the amount of water we use,” he says. Because the club uses more than 1 billion gallons each year, even a 10 percent improvement in water usage will make the investment pay off in that three-year time frame. “Our water doesn’t go on unless our system tells us that the ground has reached a certain temperature of dryness stage and the turf needs it,” Jones explains. “Then it tells us how much water we need to buy.”

Desert Mountain relied on a local computer systems integrator, Element Blue, to put all the elements of the state-of-the-art system together. Like many small and medium-sized companies, it did not deal with IBM directly. But IBM’s analytics was the right solution because it could accommodate the data from other companies’ sensors and devices and translate it into one common “language.” Jones is confident that the net result is the most efficient use of water. “What used to be somebody’s guess or a Scientific Wild-Assed Guess (SWAG) has now turned into a very sophisticated decision based on what’s the best way to get the water out there,” he says. “It’s new technology managing old stuff.”


  • Small and medium-sized companies can buy sophisticated analytic tools for very little money
  • SMEs often can absorb and exploit these technologies faster and better than larger organizations
  • The rate of ROI in these technologies is high when implemented correctly