Companies that invest in and gain value from their data will have a distinct advantage over competitors, according to research from EY, and the gap between great and good will widen as emerging technologies which enable faster, easier data analysis continue to develop.
By turning information into intelligence, managers can create market advantages, manage risk, improve controls and, ultimately, enhance operational performance and boost earnings.
It is a sizzling hot topic that every aspiring business leader must consider. Those without the pre-requisite analytical skills sought by sectors like finance and consulting will be at a disadvantage, agrees Mark Kennedy, associate professor of strategy and director of the KPMG Centre for Business Analytics at Imperial College Business School.
“It’s no longer enough to know how to use [Microsoft] Excel very well,” he says.
Big data has created fresh business models like those of Salesforce or SAP and even entire new industries, but it has bombarded its way into virtually every sector, from healthcare and hedge funds to banking and brewing.
“Data and analytics have become part of the fabric of how we do business. It’s almost instrumental,” says Matthew Guest, head of Deloitte’s digital strategy practice for EMEA.
While the ability to capture and store vast amounts of data has grown at a rate of knots, the use of technology to analyze entire data sets has been slower to take root, and there continues to be a worrying skills shortage across sectors.
“Increasingly, we see client[s] make more data-driven decisions and putting analytics at the heart of their businesses,” says Gregor McHardy, managing director and technology consulting lead for Accenture UK and Ireland. “So our teams are increasingly bringing data and analytics skills into project analysis and execution.”
Managers must hone new tools to analyze and visualize information, and also better their ability to communicate with data scientists, says Theos Evgeniou, professor of decision sciences and technology management at INSEAD, the business school, and director of its analytics center, elab.
Yet this represents a challenge for educational institutes: “Education is no longer about old versus new skills, but old and new skills; both traditional management skills and data science,” he says.
Business schools like USC Marshall and McCombs have developed specialist degrees focused on business data and top MBA programs, from Wharton’s in the US to HEC Paris’s, have edged analytics into their curricula. Their outrageous popularity has helped address the talent gap while opening up a new market of students. “Definitely the demand is there. We could roll out another class if we wanted to,” says Yehuda Bassok, chair of the Department of Data Sciences at USC Marshall.
But, “we are not trying to train our students to become data scientists”, he adds — students learn to use data science to solve management conundrums.
By crunching data, trained talent can bring huge value to their organizations. McKinsey & Company estimates that big data could create $300 billion in value in healthcare alone each year; clever use of location data across industries could capture $600 billion in consumer surplus. Conversely, poor data management can cost up to 35% of a business’s operating revenue, according to research from A.T Kearney.
“Companies are generating new products and services based on new analytical capabilities that help them gain competitive advantage, engage with customers, and differentiate,” says Juan José Casado Quintero, academic director of the Master in Business Analytics & Big Data at IE Business School.
Companies with business models that successfully leverage client data are leaders of their industries, he says, such as Google, Amazon, Facebook, Twitter and LinkedIn.
While most companies are ecstatic about harnessing the power of information, the challenges stacked against them are steep. More than 95% of respondents to a KPMG survey admitted that untapped benefits of data remain on the table.
Experts say shifting to a data-driven culture, making data available across organizations, and embedding data scientists within companies are key problems.
“Unlocking the potential of analytics takes more than just hiring data scientists or building assets,” says Roy Lee, assistant dean of global programs at NYU Stern, which runs an MS in Business Analytics.
“Organizations have to challenge long-standing processes and oftentimes strong-willed personalities to initiate a shift,” he says.
The challenges have done nothing to dampen demand for analytics talent, however, which remains rampant, according to McKinsey, whose report says 1.5 million more managers and analysts will be required by 2018.
“Demand is strong because companies are still learning how to leverage their data,” says NYU Stern’s Roy.
They are collecting the data but struggling to effectively analyze it: “We can’t develop experts in business analytics fast enough,” he says.
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