The transformative potential of Decision Intelligence (DI) technology in the logistics industry is immense. This innovation is set to reshape how decision-making is executed across all sectors of the supply chain. DI’s use of advanced analytics, data science, AI and machine learning can empower decision cycles like never before. In particular, DI enables companies to make smarter choices, optimize processes, and streamline operations. Using rapid data analysis and recommendation engine capabilities, DI focuses directly on addressing bottlenecks, anticipating changes, and proactively helping to resolve issues. In this article, I’ll look at how Decision Intelligence can transform supply chain decision-making. Specifically, I’ll provide 10 examples that encompass 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 analytical tools. While decision 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. So, some may ask, “Isn’t it just a new IT term to describe business automation?” No, this is not the case. It is different especially when it comes to supply chain analytics and business automation. In the past, most supply chain automation has focused on automating repeatable processes and business intelligence (BI) reporting. However, analytical tools in the past such BI are geared toward descriptive analytics. In comparison, Decision Intelligence platforms are focused on supporting the full range of decision flows, particularly, prescriptive analytics for making recommendations. For more details, see my article, This Is What Decision Intelligence Technology Is And Know What Its Not.

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

10 Ways That Decision Intelligence Tech Can Empower Logistics.

Decision Intelligence tools can significantly enhance supply chain planning and execution by leveraging advanced analytics and AI algorithms. Moreover, it can optimize decision-making at both strategic and operational levels. Also, these platforms can improve demand forecasting accuracy, optimize inventory levels, reduce transportation costs, and enhance overall supply chain visibility. As a result, this enables organizations to make proactive, data-driven decisions. Below are 10 ways these decision platforms can benefit supply chains.

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1. Supplier Sourcing: Enhance Supplier Relationship Management.

With a decision platform, businesses can improve supplier relationship management by leveraging on-demand insights and data-centric decision-making. Hence, businesses can make better informed choices when both selecting and managing suppliers.

For example, a decision platform can analyze supplier performance metrics and generate targeted alerts concerning anomalies or significant changes in suppliers’ statuses. Specific measurements could include on-time delivery, quality, and pricing that monitors suppliers’ performance, reliability and cost-effectiveness. As a result of Decision Intelligence, supplier selection processes can be streamlined and relationships strengthened.

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

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

For example, a decision platform can analyze sales patterns and external factors like weather forecasts to predict future demand for specific products. Moreover, a DI platform will make recommendations based on these predictions. Based on this information, businesses can proactively make decisions to adjust their supply chain strategies accordingly. As a result, these systems can minimize both stockouts and overstocking issues.

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

In ecommerce and order fulfillment, decision intelligence technology enables smarter order routing and asset allocation by looking across the supply chain. For instance, decision platforms can consider factors such as inventory availability, proximity to customers, shipping costs, and delivery time frames. As a result, Decision Intelligence can directly support decision-making to optimize the issuance of orders to different warehouses or fulfillment centers. Better yet, supply chain leaders can use decision tools on-demand or periodically depending on their decision cycle needs. Further, businesses have the option to have decision platforms to act autonomously or with a human-in-the-loop.

For example, an ecommerce operation could utilize DI software to act on situational changes to 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 On-Demand When Markets Change.

With a decision platform, supply managers can streamline inventory management decisions in concert with changes in supply and demand. In this case, decision platforms can continuously monitor stock levels, demand patterns, lead times, and other relevant factors. As a result, logistics companies can make data-driven decisions regarding inventory replenishment and allocation.

For example, a decision platform can analyze historical sales data, current market conditions, and predict future demand to ensure optimal inventory levels. Thus, this reduces the risk of stock outs or excess inventory. Further, this automation improves inventory accuracy, reduces carrying costs, and enhances overall operational efficiency.  As an example, Throughput Inc’s DI software targets key demand and performance data to quickly determine ROI and ROA. It does this by showing operational savings using rapid root-cause analysis with actionable recommendations.

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5. Warehousing: Efficient Resource Allocation And Workforce Planning.

Efficient resource allocation and workforce planning are essential in warehousing operations. This is where decision platforms can play a crucial role in optimizing resources. By focusing on specific decision requirements, DI can rapidly analyze data such as order volumes, warehouse capacity, and labor availability. Moreover, it will provide allocation recommendations. As a result, logistics companies can allocate resources effectively even in rapidly changing situations.

For example, decision platforms can help decision-makers determine the most efficient picking routes for both warehouse workers and robotics. Specifically, these decision platforms can focus data analytics on order locations and order data. From there, DI can make recommendations to help 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 platforms through optimal routing and dispatching. DI software can target its analysis on factors such as delivery locations, transportation modes, traffic conditions, and carrier performance metrics against the current operational environment. Then, the DI platform can provide specific recommendations to maximize routing and selecting the appropriate carrier.

For example, a decision platform can consider real-time traffic data to help 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 a decision platform can provide rapid metrics analytics. As a result, DI software can make recommendations 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 be proactively alerted by the DI platform to identify issues early and take corrective actions.

For example, a decision platform can detect a delay in a shipment’s progress and automatically alert and make rerouting recommendations to the relevant stakeholders. This enables logistics providers to improve operational efficiency, enhance customer satisfaction, and optimize supply chain performance.

8. Freight Bill Auditing And Payment: Provide Timely Insights to Reduce Costs.

Freight bill auditing and payment processes can be streamlined through Decision Intelligence that provides timely insights to reduce costs. By augmenting the freight audit process using advanced algorithms, companies can detect billing errors or discrepancies more efficiently.

For example, decision platforms can automatically compare freight invoices against agreed-upon rates, contracts, and shipment data to identify any discrepancies or overcharges. Further, DI can make recommendations on minimizing these errors in the future. What’s more as part of the audit process, DI can recommend ways to improve shipping operations to reduce costs. Thus, this capability ensures accurate billing, helps companies avoid unnecessary expenses, and provide recommendations to improve delivery performance.

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

Customer service is greatly enhanced by decision platforms through real-time insights and recommendations. By analyzing customer data, order histories, and feedback in real-time, companies can gain valuable insights into customer preferences and behaviors. Further, the DI platform will make actionable recommendations to optimize the customer experience going forward.

For example, a decision platform can identify patterns in customer complaints or inquiries related to specific products or services. From there, the DI platform can make targeted recommendations. This enables businesses to address issues promptly, improve product offerings or service quality, and ultimately boost customer satisfaction.

10. Compliance: Insights and Recommendations To Maximize Regulatory Compliance And Sustainability Practices.

Compliance is another area where decision platforms can provide rapid 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, decision platforms can track changes in regulations or industry standards and provide timely alerts and recommendations to ensure that logistics operations align with the latest requirements. Thus, this DI capability helps companies maintain compliance, reduce risks, and enhance sustainability practices.

References.

For more references on the benefits of Decision Intelligence, see:

• Tellius’ Decision Intelligence: What It Is and Why It Matters
• Gartner’s, Analytics and Decision Intelligence (A&DI) Technology For Supply Chains for more on decision intelligence automation providers in the supply chain space.
• My article, An Agile Decision Platform to Empower Executives For Superior Supply Chain Performance: Here Are The Best Attributes, for more on the unlimited potential of Decision Intelligence to support executives’ agile decision-making cycles to maximize supply chain performance.

An Agile Decision Platform to Empower Executives For Superior Supply Chain Performance: Here Are The Best Attributes

Lastly, if you are in the supply chain industry and have a need to supercharge your decision-making cycles, please contact me to discuss next steps. I’m Randy McClure, and I’ve spent many years solving data analytics and decision support problems. As a supply chain tech advisor, I’ve implemented hundreds of successful projects across all transportation modes, working with the data of thousands of shippers, carriers, and 3rd party logistics (3PL) providers.  I specialize in launching new analytics-based strategies, proof-of-concepts and operational pilot projects using emerging technologies and methodologies. To reach me, click here to access my contact form or you can find me on LinkedIn.

For more articles from SC Tech Insights, see the latest on decision science.