Big data and the supply chain: The big-supply-chain analytics landscape (Part 1)

Big data and the supply chain: The big-supply-chain analytics landscape (Part 1)

Big data and the era of digital means a big analytics landscape for supply chain to work with.

Your supply chains generate big data. Big supply-chain analytics turn that data into real insights.

The explosive impact of e-commerce on traditional brick and mortar retailers is just one notable example of the data-driven revolution that is sweeping many industries and business functions today. Few companies, however, have been able to apply to the same degree the "big analytics" techniques that could transform the way they define and manage their supply chains.

In our view, the full impact of big data in the supply chain is restrained by two major challenges. First, there is a lack of capabilities. Supply chain managers—even those with a high degree of technical skill—have little or no experience with the data analysis techniques used by data scientists. As a result, they often lack the vision to see what might be possible with big data analytics. Second (and perhaps more significantly), most companies lack a structured process to explore, evaluate and capture big data opportunities in their supply chains.

In the second part of this article series, we will show how companies can take control of the big data opportunity with a systematic approach. Here, we will look at the nature of that opportunity and at how some companies have managed to embed data driven methodologies into their DNA. Exhibit 1 provides an overview of the landscape of supply chain analytics opportunities.