Going Beyond Code
Today’s data scientists must be more than mathematicians — they need to understand business needs to provide supply management teams and companies with a competitive advantage.
By Sue Doerfler
As supply management organizations strive to meet customers’ needs and respond quickly to disruption while increasing the bottom line, the role of the data scientist is beginning to take on greater importance.
Technology is shaping the roles of the future, says Karin Visser, senior director, intellectual property development at global management consulting firm Korn Ferry in Amsterdam, Netherlands. “In a lot of organizations, jobs are tied to working on data, data analysis, predictions, artificial intelligence (AI), machine learning and the like,” she says. “We see it in all kinds of businesses. Everything an organization collects — from its clients, suppliers or logistics — can be looked at and learned from. And more business can be made from it.”
In its 2018 Future of Jobs Survey, the World Economic Forum states that through 2022, there will be increasing demand for data analysts and scientists — across all geographies as well as in numerous sectors — due to the accelerating need for specialist roles pertaining to understanding and leveraging emerging technologies. Additionally, more data is available than ever before — and it’s projected to exponentially grow, says Michael Prokle, Ph.D., lecturer at Northeastern University’s College of Professional Studies in Boston and senior data scientist at Fortune Brands Global Plumbing Group. “With more data available, companies are asking what they can do with it,” he says. “For companies, data is the differentiator.”
But having data is not enough. It needs to be analyzed and translated to address business needs. And for organizations to optimize and become more transparent, agile and efficient — and to distinguish themselves from the competition — they must use data to create predictive modeling and new processes. That’s where the data scientist comes in.
“Data scientists are able to take what we humans use as cognitive, everyday capabilities and translate that into the data elements needed to create more cognitive, predictive AI-type solutions,” says Marco Romano, procurement data and analytics officer at IBM in Portsmouth, England.