The New Supply Chain is Digital, Powered by AI and Analytics

“The digital supply chain will be the predominate model within the next five years,” agree 80% of respondents to the Material Handling Institute’s (MHI) 2018 annual survey. According to the report, digital supply chains are “information ecosystems” where all actions are tracked “to maximize efficiency and meet customer demands for increased flexibility, visibility and transparency.”

Digital supply chains use innovations to increase efficiencies and create competitive advantages for users. As technologies advance, supply chain executives must use new innovations to stay competitive in a changing world.

Artificial Intelligence (AI) and Predictive Analytics
Technology is getting better and more widespread. AI technology can learn from stored data to forecast future actions, like your shopping habits. Supply chains can use AI and predictive analytics to predict factors like carrier performance and traffic delays.

By utilizing AI and predictive analytics technology, the optimization of deliveries is shifted to algorithms rather than tribal employee knowledge. According to MHI, the current adoption rate for AI is only 6%, but is projected to reach 47% by 2023. Supply chain innovations like AI and predictive analytics, “have a potential to disrupt the status quo and create a lasting competitive advantage for companies that embrace them”.

Importance of Going Digital
A digital supply chain is a connected system, bringing visibility, risk mitigation, cost reductions and greater efficiencies. The technology for a digital supply chain starts with a transportation management system like SwanLeap.

Shipping errors caused by outdated TMSs that aren’t using digital supply chain innovations are costing companies money. For instance, a Fortune 500 retailer used a market-leading TMS for e-commerce fulfillment, and the manually entered business rules selected non-optimal routing of a segment of shipments, resulting in a $1.6M overspend for one month.

Furthermore, due to the on-premise nature of traditional TMS, huge restrictions exist for data collection, retention, and analysis. This same retailer requires 24 hours of processing time to collect data from all locations to be compiled into a database each night, which still did not bring the routing problems to light. Traditional TMSs dump their data at the end of the night, rendering them unable to learn from analytics.

The old way of doing TMSs is inefficient. NextGen TMSs bring a level of efficiency and reliability unparalleled by the e-commerce technologies in place at most companies.

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