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What is Supply Chain Analytics - Types, Use Cases, Benefits & Solutions


The post-pandemic scenario is making businesses sit up, take notice and deploy supply chain analytics. The supply chain is an essential element of business success today. An optimized supply chain can enhance the cost-efficiency and customer satisfaction of a company. With vast amounts of data generated at various supply chain touchpoints, managing the data for efficient business practices becomes challenging. Supply chain analytics helps to streamline the data and enables data-driven decision-making.

The Making of a Supply Chain Leader - Blog Procurious


What are the key skills supply chain professionals should be developing in an AI-enabled future? "I'm a great believer in great passion," says Ron Castro, Vice President, IBM Supply Chain. And it's just as well given that Ron is responsible for all strategy, execution, and transformation of IBM's US$70Bn global end-to-end supply chain, delivering to clients across more than 170 countries. "Always be as bold and as fast as you can," he says. "I've never looked back in a transformation and thought'Darn it! I wish I had gone slower.' There's always room to be bolder and to go faster."

Building value-chain resilience with AI


Across industries, value chains are facing increasing uncertainty from climatic anomalies, market volatility, and the COVID-19 pandemic, among other factors. Industries as diverse as agriculture, oil and gas, and mining face essentially the same problem: they need the ability to both run with increased efficiency and recover quickly from unforeseen or unexpected challenges. But these two goals often conflict. If companies simply increase production levels, they'll inevitably run into bottlenecks--and if failures occur that worsen those bottlenecks, the entire network can slow down and become less resilient. For more on how COVID-19 has affected supply chains, see Knut Alicke, Richa Gupta, and Vera Trautwein, "Resetting supply chains for the next normal," July 21, 2020. Resolving this conflict presents several challenges.

Disrupting Procurement: AI, Predictive Analytics, Blockchain And IoT - Disruption Hub


We hear a lot about how emerging technologies such as artificial intelligence (AI) and machine learning (ML) are disrupting the future of work, but very often this is a high-level narrative that doesn't dive into specifics in terms of the enterprise business functions being most impacted. In this article, we'll look specifically at the procurement function to examine how and where business processes are being transformed – and even disrupted – and some of the most impactful technologies involved. These include AI/ML, predictive analytics, blockchain and IoT, as well as AR/VR and intelligent agents. While procurement might be one of the last places you'd expect to find digital transformation, the fact is that it's well underway and a sizable organisational opportunity for unlocking cost savings and operational efficiencies. By way of example, the Ariba Network supports over 3.4 million companies in over 190 countries and conducts over $2.1 trillion in commerce annually.

Gartner Top 8 Supply Chain Technology Trends for 2018


Olay Skin Advisor is a mobile app that relies on machine-learning algorithms to analyze skin care needs. The app performs a facial analysis from a consumer's no-makeup selfie and recommends products based on personal data and best practices from skin care experts. The artificial intelligence (AI)-enabled app also collects buying behavior data directly from the consumer and uses that data to determine the demand for and recommend specific products. Supply chain leaders must assess their company's risk culture to determine their readiness to explore and adopt emerging offerings Similarly, FlavorPrint, an AI-based platform introduced by McCormick spinoff Vivanda, determines what is called a "flavor DNA" -- a digital taste identifier that matches consumers to food items. Through this direct customer engagement, FlavorPrint is sensing demand by better understanding customer preference.