Big data can be a new tool of corporate competitiveness that offers vast business opportunities, but proper use and analysis of the massive volume of data will require new sets of skills and mind-sets on the part of management, said Phillip Leslie, an associate professor at UCLA Anderson School of Management.

Speaking at the May 31 symposium that gathered American business school scholars, Leslie noted that after companies in the United States invested heavily on building the capacity to process big data in recent years, the firms “are increasingly asking the question — all this data, all this infrastructure, all this spending, and now what do we do with it?”

“We are at a critical moment where companies need to figure out exactly how to utilize this data to address strategically important questions that will allow them to create and capture value,” he said.

Leslie said there are two categories of work involved in big data analytics.

In data-driven analytics, companies try to harvest the descriptive value of the data — and enhance their visibility into what is happening in their business, he said. “Companies in the U.S. today at least have better visibility into how their sales are performing, how their employees are performing, how their supply chain is performing than at any point in the past,” Leslie said.

Investments in the hardware, software and engineering talent for processing the massive data allow the companies “to know and understand — as near as possible in real time — what’s going on in their business, and with this real-time data reporting, the companies are able to react quickly,” he said. This is “providing whole new opportunities for companies to be able to analyze and think about how their business is performing,” he said.

On the other hand, more efforts still need to be made in terms of question-driven analytics — using the data to answer strategic questions, such as predicting customer behavior or future inventory levels, assessing the value of an advertising campaign, and so on, Leslie said.

This requires people to come up with the right questions, to know how to utilize the data or to carry out an experiment to answer the questions, he said. “These are skills that companies have not had much human capital in. This is a new and emerging skill set” that would be needed to “get maximum value” out of all the data collected, he said.

As one of the successful examples of question-driven data analytics, Leslie cited an experiment carried out by eBay, the major online marketplace, that sought to see how the money they spend on paid search listings are in fact impacting the flow of traffic to their website. While the marketing people at the firm insisted that the money they pay for the keywords is crucial to bringing people to their website, the results led the eBay data analysts to think that the paid search is not an effective use of the expenses, and management eventually decided to substantially cut the spending on the paid search links, he said.

While the case was seen by many as a huge victory of the power of data to overcome managerial bias, “it also points out not just the value of analysis but the challenges of making sure that management is capable of believing and reacting to that analysis,” Leslie said.

The recent trend in data analytics, he said, is that companies are shifting from purely monitoring activity using data analytics “to more sophisticated” uses of data. “It’s less about the work being done by engineers to build the software and hardware needed to gather and collect data. We’re moving now into a period where people who have a data mind-set, people who know how to study data, to ask questions and think statistically, are going to be more and more important when it comes to evaluating the data,” he said.

Companies need to have “data-driven decision makers,” and “it’s not just about hiring a few econometricians or statisticians to analyze the data,” Leslie said. “Throughout the organization you need to embrace the power of data to be able to ask and answer important questions.”

In the U.S., data analytics is becoming a core skill for corporate managers, he noted. “More and more people are now embracing the idea that in addition to being a strategic thinker and a leader, a modern manager must think in terms of data, must use data to evaluate issues, must know what it means to run an experiment and be able to assess and evaluate the quality of data, in order to be able to make effective decisions based on that kind of work,” he said.

A common complaint that’s heard at U.S. companies about data analytics today, Leslie said, is that businesspeople do not react to the report compiled by data analysts. The analysts complain that their work is being ignored, while the businesspeople complain that they don’t understand or don’t know whether to believe the work done by the analysts, he said.

The first step to resolving these problems, Leslie said, is to have the analysts provide clear, transparent and compelling presentations based on the data so that the businesspeople should be able to understand and react to the analysis.

The second challenge is to get managers to “have more of an open mind to the power of data” — to change the way managers think about data, get them to question their gut instinct and be more open-minded to using the data for decision making, he said.

And the third step, Leslie said, is for managers to do both of those things. “You need to be somebody who is business-minded who can understand data analytics, so that all of these capabilities are embedded in a single person.”