Like a lot of companies, energy giant Chevron sometimes struggles to find well-rounded data scientists. So last year, the company held a problem-solving contest to identify potential analysts hidden among its 64,000-plus employees.
Chevron promoted the contest to about 350 employees who had expressed an interest in analytics. It held an introductory teleconference explaining the contest, which asked entrants to predict things such as the amount of oil a reservoir would yield or the cost of oil at a certain time.
Among the winners of that contest, now an annual company event, was a woman who had a background in statistics but was working in a supplier management position. She’s since become “an analytics rock star,” says Margery Connor, head of Chevron’s Center of Excellence for Advanced Analytics. “We might never have identified her without this contest.”
Over the years, Chevron, based in San Ramon, Calif., has turned itself into a data-driven business, prioritizing analytics and operations research throughout the organization.
Being data-driven means drawing conclusions based on evidence.
In April, the Institute for Operations Research and the Management Sciences, an association of analytics professionals, recognized Chevron with its annual INFORMS Prize. The organization specifically praised the way Chevron’s data-focused approach helps it reduce material costs, recover resources, and operate more safely and reliably.
Businesses large and small are increasingly launching analytics programs of their own, often with similar goals. Over the past year, there’s been a 125 percent rise in the number of organizations that have deployed or implemented analytics projects, according to IDG Enterprise. Many organizations surveyed said they expect analytics projects to surface strategy-defining insights into customer behavior, sales patterns, or product quality.
Delivering on that promise means finding, hiring, and developing talented data scientists. But that’s just the beginning. A culture driven by data has to extend beyond a specialized group employees trained in analytics. It involves the decision-making style of the whole organization, in every function and line of business.
“Being data-driven means drawing conclusions based on the evidence, not on the opinion of the highest-paid person in the room,” says Kirk Borne, principal data scientist at technology consultancy Booz Allen Hamilton. To build a culture that routinely makes data-centered commitments, he says, a company’s employees must make decisions based on all available and pertinent data rather than on preconceived notions.
Most people see a lot of data in their daily jobs.
Detecting Data-Driven Candidates
The analytics discipline has been around for decades, but in the context of big data it’s a relatively new field. There aren’t a lot of programs turning out job-ready candidates, andmidcareer professionals don’t always come with the necessary technical training.
“Sourcing candidates is really much more challenging,” says Alexis Fink, talent intelligence and analytics leader at Intel. “You can’t just source by a university.”
The good news is that you don’t have to limit yourself to finding fully-trained candidates. And there are likely scores of individuals scattered across your organization who, with good training and the right tools, can help transform your company into one driven by data.
Fink says strong analytics candidates need more than math and programming skills to succeed, however. Good ones approach data with an open mind, Fink adds.
“Most people use data the way a drunk uses a light post,” Fink says, “for support rather than illumination.” Rather than selectively seek data to uphold an existing belief, a datadriven professional will start with a question and use scientific methods to find data that reveal the right answer.