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Top Trends Of Supply Chain Technology
Supply chain leaders are concerned that their supply networks "are not well-positioned to meet the difficulties of the next two years," according to 38 percent of respondents.
FREMONT, CA: As the profession seeks to navigate change and meet future expectations, embracing and integrating novel technologies will be a critical aspect of supply chain management in the coming years.
Hyper automation, also known as intelligent process automation or digital process automation, uses robotic process automation, machine learning, artificial intelligence, and process mining to automate tasks that previously required human intelligence, decision-making, or judgment.
Digital Supply Chain Twin (DSCT)
A sophisticated digital simulation model that leverages real-time data to create a holistic perspective of an organization's real-life supply chain is known as a DSCT.
By boosting transparency and efficiency, driving greater quality control, lowering risks, and advancing sustainability, a DSCT can save time, resources, and money.
Edge ecosystems include applications for both edge computing and edge data processing. These ecosystems have the potential to revolutionize data processing by bringing compute, data storage, and electricity as near to the point of action or occurrence as possible. It can help supply chain experts improve the breadth and visibility of their supply chains, do in-depth data analysis, and respond and make decisions faster.
Supply Chain Security
To protect against counterfeits and cyberattacks, complex and digitally integrated global supply chains necessitate sophisticated solutions.
Supply chain assaults, which aim to harm a company by targeting the weakest links in its supply chain, are becoming more common. The number of supply chain attacks, for example, jumped by 78 percent in 2019.Analysts predict that as companies pursue digitally integrated end-to-end supply chains, a slew of new scalable technological solutions to mitigate cyberattacks will emerge.
Embedded AI and Analytics
Embedded AI involves integrating machine learning and deep learning into device software, which is then programmed to deliver predictive and reactive intelligence to the data collected and processed.
Predictive maintenance for equipment, enhanced productivity, higher quality components, and products, and better risk and cybersecurity management are all benefits of embedded AI for supply chain and manufacturing experts.
Augmented Data Intelligence
Machine learning and predictive analytics are helpful to do advanced data processing in augmented data intelligence. It improves visibility and operational efficiency in supply chain management by providing professionals with the information they need for making informed and efficient decisions.
The ability to blend the strengths of humans and robots is a significant feature of augmented data intelligence. Organizations frequently struggle to digest the massive amounts of data at their disposal, but augmented data intelligence can aid in the transformation of this data into valuable insights.
See Also: Top Supply Chain Solution Companies