Competing With Data & Analytics
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While some industries like health care and retail are starting to see the transformational potential of big data and predictive analytics, these strategies haven’t quite panned out for supply-chain managers. Why?
The biggest obstacles appear to be the cost of hiring skilled employees and the complexity of connecting nodes across an extended supply-chain network.
With this in mind, researchers Matthew Waller, chair of the department of supply chain management at the University of Arkansas’ Sam Walton College of Business, and Stanley Fawcett, John B. Goddard Endowed Chair in global supply chain management at Weber State University, write in a new research paper that the convergence of data science, predictive analytics and big data have the potential to transform the way in which supply-chains managers lead and supply chains operate.
But, they say, more research needs to be done to investigate the convergence of data science, predictive analytics (they’re calling this convergence DPB) and big data in the field of supply chain management (SCM). The goal: to further the understanding of how to utilize big data effectively and develop a new breed of supply chain leaders that are versed in using data and analytics effectively.
Their research has implications for current managers.
A recent Wall Street Journal article citing a survey by The Economist
points out that while most companies see the value in using predictive analytics and big data to parse out increasingly complex issues within their supply chains, they still perceive the cost of deployment as too high:
As supply chains become more tangled, with a greater number of far-flung suppliers, managers are faced with risks that can crop up in dozens of countries. Companies have long used complex data sets to plan manufacturing to meet customer demand. But firms are now looking to combine data from external sources to better predict future risks.
In their paper, “Data Science, Predictive Analytics and Big Data: A Revolution That Will Transform Supply Chain Design and Management,” Waller and Fawcett write that DPB will be useful to organizations when injecting data and analytics insights into their supply chains.