Discover how decision intelligence technology is poised to transform the logistics industry. Indeed, it’s here to dramatically automate decision-making flows, even real-time if needed. In particular, it leverages advanced algorithms, data science, and machine learning to automate decision processes. Further, this groundbreaking tech helps companies make wiser decisions, optimize decision-making, and streamline operations. With real-time data analysis and predictive modeling, it’s never been easier to tackle bottlenecks, foresee demand changes, and proactively resolve potential issues. In this article, I’ll explore with you how decision intelligence automation can transform supply chains. This includes 10 unique examples covering everything from planning and sourcing to final delivery and customer service.

What Is Decision Intelligence And How Is It Different From Other Automation.

Decision Intelligence (DI) is a groundbreaking technology that can take business decision-making to unparalleled heights compared to traditional automation. While DI platforms can employ artificial intelligence (AI), there’s so much more to it than just AI. Below is a short definition of what decision intelligence is:

“Decision intelligence is a practical domain framing a wide range of decision-making techniques bringing multiple traditional and advanced disciplines together to design, model, align, execute, monitor and tune decision models and processes.” 

Gartner

Now on the surface, decision intelligence appears to be nothing new, just a new IT term to describe business automation. However, it is different especially when it comes to supply chain automation. In the past, most supply chain automation has focused on automating repeatable processes or providing business intelligence (BI) to make actionable decisions. In comparison, decision intelligence is focused on automating decision-making flows in real-time and in a dynamic environment. Further, if desired, decision intelligence can be autonomous or just provide actionable recommendations and options to decision makers. See my article, This Is What Decision Intelligence Technology Is And Know What Its Not for more details.

This Is What Decision Intelligence Technology Is And Know What Its Not

10 Ways That Decision Intelligence Tech Can Empower Logistics.

Decision intelligence automation can provide significant benefits to supply chain planning and execution. Further, supply chain leaders can deploy this type of decision automation at both the strategic and operational levels. Thus, by leveraging advanced analytics and AI algorithms, DI platforms can optimize supply chain decision-making. In particular, it can improve demand forecasting accuracy, optimize inventory levels, reduce transportation costs, and enhance overall supply chain visibility. Further, it enables organizations to make proactive decisions based on real-time data and predictive analytics. As a result, this leads to improved operational efficiency, reduced costs, and enhanced customer satisfaction. Below are 10 examples where DI automation is able to benefit businesses all across the supply chain from supplier sourcing through customer delivery.

1. Supplier Sourcing: Enhance Supplier Relationship Management.

With DI software, businesses can improve supplier relationship management by leveraging real-time insights and data-driven decision-making. Hence, businesses can make better informed choices when both selecting and managing suppliers.

For example, a company utilizing decision intelligence tech can analyze in real-time supplier performance metrics such as on-time delivery, quality, and pricing to identify the most reliable and cost-effective suppliers. As a result of DI automation, supplier selection processes are streamlined, relationships are strengthened. This all results in a smoother supply chain flow.

2. Supply chain planning (SCP): Advance Demand Sensing And Planning.

Supply chain planning (SCP) is significantly advanced through decision intelligence tech, particularly in the area of demand sensing and planning. By analyzing historical data, market trends, and customer behavior, logistics providers can accurately forecast demand and optimize inventory levels accordingly.

For example, DI software can analyze sales patterns and external factors like weather forecasts to predict future demand for specific products. This allows businesses to proactively adjust their supply chain strategies, minimize stockouts or overstocking issues, and meet customer demands more efficiently.

3. eCommerce And Order Fulfillment: Smarter Order Routing And Allocation.

In eCommerce and order fulfillment, decision intelligence technology enables smarter order routing and allocation. By considering factors such as inventory availability, proximity to customers, shipping costs, and delivery timeframes, this automation optimizes the allocation of orders to different warehouses or fulfillment centers. Better yet, supply chain leaders can use this automation ad hoc, periodically, or even real-time. Further, businesses can allow DI automation to act autonomously or with a human-in-the-loop.

For example, an eCommerce platform utilizing DI software can automatically route orders to the nearest warehouse with available stock for faster delivery. This not only improves order fulfillment speed but also reduces shipping costs and enhances customer satisfaction.

4. Inventory Management: Streamline And Optimize Real-Time.

Inventory management is streamlined and optimized through decision intelligence tech in real-time. By continuously monitoring stock levels, demand patterns, lead times, and other relevant factors, logistics companies can make data-driven decisions regarding inventory replenishment and allocation.

For example, DI software can analyze historical sales data and predict future demand to ensure optimal inventory levels, reducing the risk of stockouts or excess inventory. This automation improves inventory accuracy, reduces carrying costs, and enhances overall operational efficiency.  As an example, Throughput Inc’s DI software will automatically determine ROI and ROA. It does this by showing operational savings using real-time root-cause analysis with actionable recommendations.

5. Warehousing: Efficient Resource Allocation And Workforce Planning.

Efficient resource allocation and workforce planning are essential in warehousing operations, and decision intelligence technology can play a crucial role in optimizing these aspects. By analyzing real-time data on order volumes, warehouse capacity, and labor availability, logistics companies can allocate resources effectively.

For example, decision intelligence tech can determine the most efficient picking routes for warehouse workers based on order locations and optimize the allocation of tasks to minimize idle time. This leads to improved productivity, reduced operational costs, and enhanced customer service.

6. Transportation: Optimal Routing And Dispatching Using Decision Intelligence.

Fleet owners and carriers can greatly benefit from decision intelligence tech through optimal routing and dispatching. DI software can analyze factors such as delivery locations, transportation modes, traffic conditions, and carrier performance metrics in real-time. Thus, it helps companies make informed decisions regarding shipping routes and carrier selection.

For example, DI automation can consider real-time traffic data to choose the fastest and most cost-effective route for each shipment. This not only reduces transit times but also minimizes fuel consumption and transportation costs.

7. Supply Chain Visibility And Tracking. Real-time Metrics Analytics To Mitigate Potential Disruptions, Reduce Waste, And Drive Continuous Improvement.

Supply chain visibility and tracking are crucial for effective logistics management. This is where decision intelligence technology can provide real-time metrics analytics to mitigate potential disruptions, reduce waste, and drive continuous improvement. By monitoring key performance indicators (KPIs) such as on-time delivery rates, order accuracy, and inventory levels, companies can proactively identify issues and take corrective actions.

For example, DI software can detect a delay in a shipment’s progress and automatically alert the relevant stakeholders to address the issue promptly. This enables logistics providers to improve operational efficiency, enhance customer satisfaction, and optimize supply chain performance.

8. Freight Bill Auditing And Payment: Provide Real-time Insights to Reduce Costs.

Freight bill auditing and payment processes are streamlined through decision intelligence automation, providing real-time insights to reduce costs. By automating the auditing process using advanced algorithms, companies can detect billing errors or discrepancies more efficiently.

For example, DI automation can automatically compare freight invoices against agreed-upon rates, contracts, and shipment data to identify any discrepancies or overcharges. This automation ensures accurate billing and helps companies avoid unnecessary expenses.

9. Customer Service: Boost Customer Satisfaction Through Decision Intelligence Real-TIme Insights

Customer service is greatly enhanced by decision intelligence tech through real-time insights. By analyzing customer data, order histories, and feedback in real-time, companies can gain valuable insights into customer preferences and behaviors.

For example, DI software can identify patterns in customer complaints or inquiries related to specific products or services. This enables businesses to address issues promptly, improve product offerings or service quality, and ultimately boost customer satisfaction.

10. Compliance: Real-Time insights To Optimize Regulatory Compliance And Sustainability Practices.

Compliance is another area where decision intelligence software can provide real-time insights to optimize regulatory compliance and sustainability practices. By monitoring and analyzing data related to regulatory requirements, environmental impact, and ethical standards, companies can ensure compliance and make informed decisions.

For example, DI software can track changes in regulations or industry standards and provide real-time alerts to ensure that logistics operations align with the latest requirements. This automation helps companies maintain compliance, reduce risks, and enhance sustainability practices.

For more references on the benefits of decision intelligence automation, see Tellius’ Decision Intelligence: What It Is and Why It Matters. Also, see Gartner’s, Analytics and Decision Intelligence (A&DI) Technology For Supply Chains for more on decision intelligence automation providers in the supply chain space.

Business Decisions Made Better: First Automation, Then Data, Now AI Tech

For more related articles from SC Tech Insights, see my articles on decision science.