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Big data analytics in supply chain: Hype or here to stay?

Find out how big data analytics can positively impact a company’s overall operating and financial performance.

Overview

Most companies have high expectations from big data analytics in their supply chain, many have had difficulty adopting it.

We surveyed more than 1,000 senior executives from large global companies to get their thoughts on the importance of big data analytics in their supply chain, the progress they have made in adopting it and how they are benefiting from its use.

Ninety-seven percent of the surveyed executives have an understanding of how big data analytics can benefit their supply chain but only 17 percent have already implemented analytics in one or more supply chain functions.

We also found that many companies are on the verge of making investments to develop a mature big data analytics capability. More than one-third of executives reported being engaged in serious conversations to implement analytics in the supply chain, and three out of 10 already have an initiative in place to implement analytics.

Our research further revealed some commonalities among a small group of companies that have generated a high return from their investment in big data analytics for their supply chain.

Background

The Accenture Global Operations Megatrends research study is designed to explore key trends in the operations function. The research is focused on three areas of concern for supply chain leaders globally: emerging market growth, supply chain risk management and big data analytics. The intent of the research is to understand the specifics of what companies are executing and planning in these areas, and the effectiveness of those strategies.

The research involved a Web-based survey of 1,014 senior executives at large global companies headquartered in the respondents’ locations. Fifty-six percent of respondents held C-level titles, including chief supply chain officer, chief procurement officer, chief sourcing officer, chief operations officer and chief operating officer. The remaining 44 percent were senior-level supply chain, procurement or operations executives.

Key Findings

  • Big data analytics is on nearly everyone’s mind. Companies have high expectations from big data analytics. Forty-eight percent of the surveyed executives expect to create an organizational ability to respond more quickly to changes and 45 percent expect big data analytics to help them gain insights about the future.

  • Actual use of big data analytics is limited. Despite the acknowledged benefits big data analytics can generate, companies face difficulties in adopting it. Sixty-seven percent of the surveyed executives cited worries about the large investment required to deploy and use analytics, and 64 percent are concerned about the security issues.

Recommendations

Big data analytics can have a major impact on a company’s overall operating and financial performance. We found three key practices that distinguished the small group of leaders from the others:

  • Leaders strongly focus on developing a robust big data analytics enterprise-wide strategy to drive business value. Companies with an enterprise-wide strategy are more likely than those with a process-focused strategy to have shortened order-to-delivery cycle times (61 percent versus 14 percent).

  • Leaders embed big data analytics into day-to-day supply chain operations to improve decision making. Companies that embed analytics in their operations have faster and more effective reaction time to supply chain issues than those that use big data analytics on an ad-hoc basis (47 percent versus 18 percent).

  • Leaders hire talent with a mix of deep analytics skills, and knowledge of the business and industry. Companies with a team of data scientists are more likely to have a more effective S&OP process and decision making than those with just traditional database personnel (44 percent versus 11 percent).