Predictive Analytics is Critical in the Logistics and Supply Chain

Posted by Land Link Traffic Systems on Sep 23, 2020 10:13:21 AM

predictive-analytics-5-examples-of-industry-applications-2In todays Logistics business time and performance are key to success. Now more than ever analytics, metrics and key performance indicators are critical components in planning and execution protocols. Today’s logistics market is more demanding than it’s ever been. Businesses across the supply chain are now expected to easily adjust to shipment patterns, predict customers’ buying behaviors, provide on-time deliveries through the most efficient routes possible, and reduce the risks of cargo inventory errors and miscalculations. Predictive analysis allows for advanced planning for future demand based upon historical data. This movement towards anticipatory logistics is already widely accepted among industry decision-makers: A study by the Council of Supply Chain Management Professionals revealed that 93% of shippers and 98% of third-party logistics firms feel like data-driven decision-making is crucial to supply chain activities, and 71% of them believe that big data improves quality and performance. 

Enhanced Supply Chain Visibility

New supply chain visibility technology promotes quick response to change by allowing privileged users to take action and reshape demand or redirect supply, and fully integrated supply chains see 20% more efficiency than those without integration. Gone are the days of fielding calls from irate shippers demanding to know the location of their freight. Obtaining real-time visibility across all tiers in the supply chain can significantly increase speed to market, reduce capital expenditures and manage risk.

KPI’s, Metrics and Analytics

These key elements allow Logistics professionals to monitor performance on an ongoing basis and identify inefficiencies based on real-time information. As soon as data indicates errors in picking rates, delays in picking procedures or that shipping lacks some items, managers have the information they need to intervene immediately. Predictive analytics can also be used to anticipate demand peaks for any product, at any time, at the right place, and the right price. Moreover, having insights on how customer demand will evolve helps plan and anticipate shifts, inventory shortages, and reduces costs. What does not get measured, does not get fixed. It would be difficult if not impossible for any rational person to repudiate this thought-provoking statement and important underlying principle of business. Yet, many companies to do just that. Most companies, in fact, do not have the proper measurements and KPIs in place necessary to drive intelligent business decisions and to serve as support to the policies that are relied upon to drive day to day business activities. The leverage of data through innovative technologies that allow companies to have better and new data, and use it in more robust applications, is speeding up the path to a more efficient and sustainable supply chain. 

A Future of Increased Efficiencies

It’s clear that for logistics and the supply chain, predictive analytics is the key to opening new doors of cost-savings and efficiency gains. Additionally, these solutions are transforming the industry from human-driven to data-driven decision-making, a huge factor in the digitization of the industry as a whole. Investing in a predictive analytics solution is no longer an option. It has become a necessity to maintain competitiveness with all the players who already benefit from emerging predictive technologies. Both consumers and organizations continue raising expectations to receive their shipments faster and cheaper. Therefore, those logistics and supply chain businesses that do not invest in predictive technologies within their operations will find themselves at a life threatening competitive disadvantage.

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Michael Gaughan
Technology Officer
Land Link Traffic Systems

Topics: Intermodal Freight, Logistics News