October 3 2024 | 9 Min Read

How predictive analytics in logistics create value

Posted By
Tiffany Lentz
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How predictive analytics in logistics create value

The supply chain is certainly no stranger to disruption. Market conditions have been a roller coaster due to COVID, multiple severe hurricanes, the Red Sea attacks on vessels, and even the risks around the East and Gulf Coast port strikes. Shippers are actively looking for ways to reduce their risks, limiting their global focus in favor of minding things closer to home. According to a McKinsey & Company survey, “Almost two-thirds (64 percent) of respondents tell us that they are currently regionalizing their supply chains, up from 44 percent last year. Only half the companies in our survey say that their supply chains are dependent on inputs from another region, but 89 percent of those respondents want to reduce that dependency over time.” Such a model’s reliance on global activities, even if nearshoring, implies that shippers need to get more strategic. In other words, they need to tap the potential of predictive analytics. 

Advanced analytics help shippers understand not only what happened but what’s likely to happen based on current conditions. Accurate predictions lead to success, operational efficiencies, and the ability to predict future demand. A heightened level of insight can directly lead to increased value in logistics across five core areas. 

1. Improved delivery speed and accuracy

Predictive data analytics can help you anticipate potential delays and disruptions, allowing you to proactively adjust your shipping routes and schedules for on-time, accurate deliveries. By leveraging data-driven insights, you can optimize transportation plans, minimize risks, and enhance the overall efficiency of your logistics operations. Together, the combination of planning and advanced analytics reflecting actual market conditions can enable dynamic route optimization. 

Dynamic route optimization provides a lifeline to companies that have to face multiple disruptions with little downtime between them. For example, the East Coast port strike could have multiple impacts on overall equipment availability due to not being able to pick up containers. In turn, that may lead to greater use of equipment for inland transportation. 

In our case study where we saved a plastics company over a million dollars annually, the solution involved continuous improvement through advanced data analytics and visibility. By collecting and analyzing transportation data, IL2000 was able to predict cost-saving opportunities, optimize routes, and streamline operations. Although this isn’t explicitly termed "predictive analytics," the approach aligns with predictive methodologies by using historical and current data to forecast cost reductions and efficiency improvements.

2. More JIT deliveries

Predictive analytics enables you to forecast demand with greater precision, facilitating just-in-time (JIT) delivery and maintaining operations despite market trends and seasonal fluctuations. Aligning inventory levels with anticipated needs lowers carrying costs, minimizes waste, and improves supply chain responsiveness, but again, this depends on optimizing inventory levels across all network facilities. Also, JIT fulfillment models help shippers to reallocate resources, streamline speed of delivery and overcome supply chain disruptions. 

3. Better customer experiences

Meeting customer expectations is paramount, and predictive analytics can play a pivotal role in enhancing the customer experience. Anticipating customer preferences and proactively addressing potential issues ensure timely deliveries, personalized service, and greater customer satisfaction. Identifying service issues before they happen and using data along the way helps shippers reduce confusion and intervene well before a negative experience occurs. Improved customer experience promotes higher customer lifetime value (CLV) and can be an additional source of revenue for your supply chain. Growing revenue strategically is the goal, so better experiences may lead to more word-of-mouth referrals from your customers. Thus, you grow.

4. Enhanced supply chain visibility

woman looking at predictive analytics in supply chainGaining end-to-end supply chain visibility into your supply chain is crucial for effective management. Predictive analytics empower you to track shipments in real time, monitor inventory levels, and identify potential bottlenecks. Transparency powers descriptive analytics – the precursor to predictive analytics. Knowing what will happen can then be applied to risk management, optimized operations, and informed decisions, keeping in line with lead times, tendering loads, planning the dock schedule and much more. 

In another client case study, IL2000 worked with a food manufacturer to increase visibility into their supply chain via our TMS. We were able to proactively manage shipping exceptions, while the use of data to anticipate and prevent future disruptions created 35% more reliability and 10% lower freight spend. 

5. Dynamic resource allocation

Predictive analytics allows dynamic resource allocation by forecasting demand fluctuations and identifying potential disruptions. In the world of management by exception, shippers should keep careful tabs on all their resources–equipment, inventory, and workers. Predictive analytics show where to focus or reallocate resources to reduce risk of additional disruptions.  The supply chain benefits from this level of continual improvement, because ultimately, shippers simply can’t improve what they can’t measure. By optimizing your workforce, equipment, and inventory based on data-driven insights, you can improve efficiency, reduce costs, and ensure timely order fulfillment.

6. Optimized locations

Center of Gravity and predictive analytics map viewAny strategy for using predictive analytics depends on accurate logistics data. The IL2000 transportation management system (TMS) and its API connectivity can be used to help determine the optimal locations for distribution centers, warehouses and production facilities. This is all part of a center of gravity (COG) analysis, which IL2000 conducts to identify low-hanging fruit of optimization. 

Imagine that you're optimizing every load’s staging for your existing transportation strategy and adjusting your dock schedule to boot. Now, you not only want to optimize everything under your control but also consider demand patterns, shipping distances, and costs. In some cases, it may be lower cost to go by ground versus air, provided the shipment will still arrive by the guaranteed delivery date. Meanwhile, predictive analytics models that suggest spikes in certain regions, such as shifting customer expectations and economic conditions, will help your team stay agile. 

Get insight into your supply chain with IL2000

Embrace the power of predictive analytics to revolutionize your logistics operations, optimize efficiency, and unlock new levels of success. Success depends on your ability to harness the potential of data-driven insights for a smarter, more agile supply chain. IL2000 can help you turn that dream into a reality.

Connect with IL2000 to improve your use of predictive analytics in logistics. 

Want to get in touch right now? Fill out the form below!

Topics: Business Intelligence, Data Insights, Freight data, Supply Chain Optimization

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