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Optimize Supply Chain
Optimize Supply Chain- Over the years, the adoption of artificial intelligence (AI) in supply chain management (SCM) has increased significantly across the globe due to higher demand for transparency and visibility on supply chain data and processes, along with the need to enhance customer service. The leading industries in terms of adoption of AI in SCM are telecom (26%), high tech (23%), healthcare (21%), professional services (19%), and travel, transport and logistics (18%), among others.
Recently, UPS Supply Chain Solutions partnered with Softeon to design a warehouse network technology for making distribution centers smarter and more efficient by speeding up order intake as well as delivery. The aim is to minimize delays for customers by ensuring delivery on time.
Uber Freight has partnered with BluJay Solutions to create a robust global supply chain based on a cutting-edge freight technology. The new technology interface enables customers to obtain prices/quotes (for booking and carrier matching) in real time, leveraging a network of more than 50,000 carriers, and, thereby, enhances visibility. These partnerships underscore the use of AI in optimizing supply chain functions.
The benefits of integration of AI notwithstanding, several organizations are unable to implement it due to the following challenges:
- Limited availability of high quality, consistent and updated (real-time) data
- Availability of supply chain data in different silos (for example, marketing department, inventory team, purchasing manager and others have own databases)
- Limited integration between systems and databases for accessing, cleansing and analyzing data
- Limited data governance policies related to extended supply chain
Procurement experts opine that the recent disruptions in supply chain caused by the COVID-19 pandemic more than ever highlight the need to integrate AI in supply chain for optimizing the operation. To avoid critical supply chain failure, it is essential for an organization to have complete visibility on the overall ecosystem; to accurately forecast demand and supply; and to optimally plan logistics and delivery, among others. AI, along with machine learning (ML), enables organizations to accurately foresee challenges/issues in supply and accordingly take necessary (precautionary/corrective) steps beforehand.
