Category: Amazon Machine Learning

Supply chain disruption costs in the United States topped $228 million in 2021. These costs go beyond dollars with damage to brands, operational costs, delayed cash flows, customer complaints, loss of customers, and loss of productivity. A 2022 survey by The Economist found that 46% of large corporations (with more than $1B revenue) are launching […]

Global economic, environmental, and social factors are still disrupting supply chains. This limits organizations’ ability to meet customer demand and manage operational costs. While supply chain issues are attributed to a variety of causes, the lack of supply chain visibility is at the top of the list. Research by Gartner found that improved supply chain […]

Previously we argued that, given the world’s current turbulence, many businesses have few alternatives but to modernize their supply chains (SC) in preparation for the future. However, what exactly does modernization entail? What are the common themes for SC modernization? How do businesses in different industries approach these themes? What cloud solutions are useful? This […]

Inventory management for perishable products is a challenge for many industries, such as food manufacturing, grocery wholesale and retail, and pharmaceuticals. For example, excess stock levels of dairy products, meats, fruits, vegetables, medicines, and even beer, to name a few, are all subject to expiration, “best before” dates, or important milestones in product lifecycle (e.g., […]

Unpredictable events such as the global pandemic, Brexit, the Suez Canal, and Ukraine highlight the importance for robust, stress-tested, and agile supply chain (SC) networks. Such large scale and disruptive events level the field and affect all industry players. Consequently, businesses that are quicker and more efficient to adapt to new circumstances gain market share […]

We observe that executives trying to obtain an end-to-end view of their company’s supply chain are often faced with a landscape mostly covered in fog – an incomplete, fragmented, and sometimes incongruent picture of what is occurring. Data may reside in disconnected, siloed systems, and many processes, such as external logistics or the current state […]