The Growth of Supply Chain Computing
Gone are the days of manual order fulfillment and record-keeping in the supply chain. Today, more businesses are integrating advanced innovative technologies in to enhance their warehouse processing.
The supply chain now depends heavily on comprehensive IoT ecosystems that comprising of hardware, middleware, software, connectivity, and advanced technologies to create an ecosystem that can be tweaked or maintained from a central location.
Computing systems in the supply chain industry is primarily segmented into inventory management, fleet management, warehouse management, asset tracking, and connected factories. When set up correctly, they ensure the smooth movement of goods from raw materials right up to delivery to customers.
These processes, which required whole departments in the past, can be easily carried out by a few administrators from anywhere in the world.
The future of supply chain computing
The future will bring the increased adoption of advanced supply chain technologies such as machine learning (ML), artificial intelligence (AI), Big Data Analytics (BDA), and other emerging technologies.
Some of these technologies are already in use today, such as blockchains and robotics. However, we expect that more businesses along the supply chain will invest in these technologies to meet customer expectations.
Stakeholders will have access to almost real-time data, allowing them to respond to market trends and initiate corrective actions almost instantly. This will reduce damages, losses, and disruptions along the supply chain to practically zero.
Problems supply chain computing may face in the future.
Some of the challenges companies may face when adopting supply chain computing to manage their supply chain include:
- Upgrading traditional systems and integrating backward compatibility for existing data.
- Information silos within the current system that may disrupt the flow of information.
- The presence of multiple stakeholders across the value chain may also pose serious data security and privacy risks.
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