The Supply Chain of the Future – Tomorrow's Vision or Today's Reality?
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Big Data Analytics—How does your supply chain stack up?
Where does your company stand compared to your competitors in implementing supply chain big data analytics that provide trusted results and deliver true, ongoing business value? What challenges do your peers face in implementing these technologies? How much progress have they made in the past year? What benefits are they realizing from big data analytics today and what will they realize tomorrow?
The 2017 inaugural survey, "Big data analytics in supply chain: Tackling the tidal wave," gave supply chain professionals their first meaningful set of benchmarks to these and other critical questions. The survey looked not just at how big data was being used in general, it also mapped these benchmarks by vertical industry. The need for this type of annual benchmarking information has never been more critical, as companies are poised to spend billions of dollars on analytics applications and capabilities. According to industry estimates, company investments in big data analytics expenditures are estimated to grow to US$22.8 billion by 2020.
No doubt about it. Analytics is a hot topic for supply chain professionals.
But harvesting value from analytics requires smart and informed decision making and priority setting. It requires knowledge of how your industry sector and peers are successfully adopting big data analytics, what works, what doesn't.
The 2018 supply chain big data analytics global survey offers the first opportunity to compare year-over-year progress toward these answers and objectives. The survey launches in a few weeks. Please be a part of it. Watch you emails for the survey announcement and participant link.
The survey is anonymous, but your participation will provide an invaluable contribution to building out a global big data benchmarking framework. A framework and findings from which your company can, in turn, gain insights. You will be able to use them to build out your own investment strategies and priorities to capitalize on the potential of big data analytics in your supply chain—and ultimately to drive profits.
Your input is essential. So please participate!
For questions, please contact Tami Kitajima at email@example.com.
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We Want to Hear From You! We invite you to share your thoughts and opinions about this article by sending an e-mail to ?Subject=Letter to the Editor: Quarter : Big Data Analytics—How does your supply chain stack up?"> . We will publish selected readers' comments in future issues of CSCMP's Supply Chain Quarterly. Correspondence may be edited for clarity or for length.