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Managing Big Data in the Electronics Supply Chain

The abundance of data in the modern-day supply chain presents both opportunities and challenges for procurement professionals.

A term used to describe the huge volume of structured and unstructured data that inundates businesses on a daily basis, the term “big data” is permeating every corner of the business world these days. And the electronics supply chain is no exception, what with the many opportunities there are to analyze that big data and glean insights that can be used for better decision making, problem solving, and strategizing.

Data is proliferating at an unprecedented rate. According to research firm IDC, between 2013 and 2020, the digital universe will grow by a factor of 10—from 4.4 trillion gigabytes to 44 trillion. “It more than doubles every two years,” IDC points out, noting that during the same seven-year time period the “division of the digital universe between mature and emerging markets (e.g., China) will switch—from 60% accounted for by mature markets to 60% of the data in the digital universe coming from emerging markets.”

Facilitating Procurement Processes

The abundance of data in the modern-day supply chain presents both opportunities and challenges for procurement professionals, most of whom by now have enormous volumes of data to tap into when making their buying decisions. “Very soon, big data will become a core element of procurement and will help facilitate procurement decisions, form processes, and choose suitable procurement solutions,” market intelligence firm SpendEdge predicts.

“There will be a collaboration of big data and artificial intelligence to revolutionize the speed and overall efficiency of the supply chain and procurement processes. Companies will maximize their cost and time saving with the combination of machine learning algorithms and big data.”

The question is, how can procurement professionals leverage effective strategies for managing those huge data sets across the supply chain. In Why is Big Data, and Managing it, Such a Big Deal? Kuebix’s Dan Clark says the challenge lies in extracting the data and then determining which of it is—and isn’t—actually useful. Then, that information has to be turned into actionable insights.

“Good data management allows companies to more efficiently and effectively orchestrate their global supply chains,” Clark writes. “The good news is that leading organizations have found ways to harness their data in creative, intelligent ways and, in return, have gained competitive advantage.”

For example, by connecting business partners, suppliers, customers, and other entities via a single, cloud-based platform that’s accessible 24/7/365, all parties gain extreme efficiencies and improved data management capabilities. Buyers can also look at how incoming data can be used to plan logistics movements (e.g., freight, ordering, carrier relationships, etc.), then consider how their company can be more efficient by leveraging the data housed in its central repository. “This, in turn, leads to significant transportation and logistics efficiencies,” Clark points out.

The Next Frontier

In Making Big Data Work: Supply Chain Management, the authors call big data and advanced analytics “the next frontier of supply chain innovation,” and point to more accurate demand forecasts, identification of new demand patterns, and better sharing of data across partners as three of the ways organizations can utilize it to improve supply chain performance.

Looking more closely at demand forecasting, for example, the authors point out that determining demand across a “sprawling manufacturing operation can be cumbersome and time consuming,” and usually based on inflexible systems and inaccurate estimates from the sales force to predict the future. As a result,  “forecasting has grown even more complicated in the current era of greater volatility in demand and increasing complexity in product portfolios.”

To solve these issues, companies can utilize data generated by customers, suppliers, sensors, and other sources—combine that information with weather forecasts and pricing positions—and come up with more accurate demand forecasts. “Companies that have a better understanding of what they are going to sell tomorrow can ship products whenever customers request them and can also keep less stock on hand,” the authors conclude, “two important levers for improving operational performance and reducing costs.”

Going forward, these and other big data-driven capabilities will play an increasingly important role in the electronics supply chain, where managing demand, projecting inventory needs, increasing visibility (i.e., over the end-to-end supply chain), and managing costs are all part of a day’s work for the typical procurement professional.

“It is becoming increasingly apparent that supply chains which learn to harness the power of the data sources benefit significantly,” writes KPMG’s Simon Rowe in How Big Data is Shaping the Supply Chains of Tomorrow, “leveraging the advantages of advanced analytics, supply chains can become more responsive, demand-driven, and customer-centric.”

 

 

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