Technological Advances That Will Improve the Supply Chain
Technological advances to improve operations and profit margins are prominent within the supply chain services industry. Optimization and integration are two areas where technology continues to play a prominent role in logistics, while machine learning and Uberization are significant trends to watch.
Supply chain optimization and efficiency are targets every logistics provider is aiming for where they reduce overhead and ultimately speed up customer delivery. Real-time information sharing across the supply chain is a fundamental part of achieving efficiency. Distributing information throughout the supply chain is one of the biggest challenges 3PL providers face because there are often multiple software platforms, applications and partnerships in place for each level of the supply chain, from procurement to manufacturing to distribution and everything in between. These systems are often proprietary and don’t always circulate data easily with one another. As a result, data may need to be extracted from each source separately, which is less than ideal.
Integration is the key to an efficient supply chain because it breaks down the walls between software applications. Integration across the supply chain simplifies internal communication and services surrounding inventory management, transportation, warehousing and other supply chain components. The power of optimization provided by integration is why logistics providers are looking to assimilate their enterprise resource planning, transportation management, warehouse management and partner systems together. The TMS is designed to facilitate integration and synthesize data from ERPs, WMS, and partner systems. Customized technology solutions such as SaaS also support integration, resulting in reduced warehousing costs, better inventory management, and quicker shipping and delivery.
Logistics technology provides enormous amounts of data that can be analyzed to increase efficiencies, streamline processes, and offer an improved customer and provider experience. While automation takes defined actions based on set processes, machine learning, an artificial intelligence technology, takes data analytics and automation to a new level by using data to predict patterns and adjust the initiation of actions accordingly. Machine learning for our industry is in its infancy because there are so many granular components involved in logistics, but experts predict that it will play a crucial role in improving efficiency and speed.
The Uberization of the freight market is another emerging technology. Uber takes the taxi concept and marries it with the idea of the sharing economy using a proprietary algorithm, mobile phone app, GPS, and a non-asset based model. There is growing interest in how the Uber concept might by applied in logistics, particularly in the last mile.
To leverage current technology with our organizational, customer, and business goals, all four types of innovation — optimization, integration, machine learning, and Uberization — can overlap. Technology and its applications are continually changing and the effects on the supply chain will likely intensify as we better understand how to harness this power.