INSC research

Why Aren’t More Companies Capitalizing on Big Data?

Big data can transform the way supply chains work, yet most companies aren’t taking advantage of it. Professors Daniel Chen, David Preston and Morgan Swink researched companies to find out why.  

October 25,  2016

By Elaine Cole

Big data is changing how companies make decisions, serve customers, manage employees and create value. Companies using big data can’t say enough positive things about it, yet a recent PwC survey shows that most companies aren’t leveraging its true power.

Big data analytics – examining large data sets to uncover hidden patterns, correlations, market trends, customer preferences and other vital information – is still relatively new. Many companies are still researching what skills, investments and risks are involved.

Daniel Chen, David Preston and Morgan Swink, professors in business information systems and supply chain at TCU, know that now is the time for organizations to stake out a leadership position for competitive advantage. So they researched hundreds of companies to find out why they aren’t taking advantage of big data analytics.

“Since supply chain success depends on organizational learning and knowledge, and IT plays an instrumental role in this information exchange, we explored how big data analytics influences productivity and growth, and key drivers to using it in supply chain management,” Chen said.

Why supply chain? “Big data analytics has the potential to particularly impact supply chain management due to the complexity and data intensity involved,” Preston said.

Chen, Preston and Swink surveyed supply chain managers worldwide, from heavy users of big data analytics to those just getting into the practice. They found that big data analytics directly influences internal efficiency and external growth for the companies using it, and that the key drivers are technological compatibility, organizational readiness and competitive pressure.

The data they collected suggest that 15 percent of the variance in asset productivity improvement, and 17 percent of the variance in the jump of business growth, are due to using big data analytics.

“The heavy users agreed that using big data analytics is consistent with their business practices, and that their supply chain management staff have the knowledge required,” Swink said.

Most use big data analytics to optimize inventory, logistics, forecasting/demand management, network/design and customer relationship management. Heavy users think production run optimization is the biggest benefit, closely followed by customer relationship management and network/design optimization.

All believe that big data analytics makes work more efficient and improves customer service.

Why aren’t more companies fully utilizing big data? For heavy users, the main deterrent is lacking skilled resources and access to data. For low users, most lack an organizational vision, a business case for the benefits of big data analytics, and the necessary IT infrastructure.

“How the Use of Big Data Analytics Affects Value Creation in Supply Chain Management,” D. Chen, D. Preston, M. Swink, Journal of Management Information Systems, 2015