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3PL Predictive Modelling Accelerator: Mailbox & Document Automation for Data-Driven Demand Planning and Empty Container Management


Predictive modelling and Data-Driven Demand Planning systems are essential for ‘Empty Container Management’. Global Repositioning Teams use them to reduce logistics costs associated with empty container handling and relocation. However, the ability to predict demand and reposition depends on accuracy and speed of data capture.

What 3PL business therefore need is a solution that can overcome challenges of manual extraction of data from emails, attachments, invoices, shipping labels, delivery notes, CMR Consignment Notes, etc. And while the ever dependable excel spreadsheet is not going anywhere, we can optimize workflows around it.

However, it is largely dependent on the availability of real-time cargo tracking data and how it is used to give the complete picture –

How shipping container dimensions’ data is input into the system

How data is standardized when collaborating with external shipping lines

How data is used to arrive at Projected vs Accrued container storage cost

How data being used to generate a plan for empty load and discharge

What process is followed to create a summary of cargo to be discharged at each port

What process is followed to capture Information location, capacity, and heavy lifts

What type of format you follow for storing data about arrival timestamps

What process is followed to calculate optimal storage figures, and peak periods

Completely manual processes of data extraction, data inputs and maintaining excel-based records pose a big challenge for prediction and visibility. Hence you need system integration that can continuously share the latest data to provide consistency across departments and global divisions.

Our Solution: Award-Winning Mailbox Automation and No-Code Adoption for 3PL Business Users

Sun Technologies is a top-tier implementation partner for some the world’s leading No-Code, Low-Code platforms for Automation. Our experts can implement end-to-end automation of your mailbox operations using OCR (Optical Character Recognition) to streamline processes and improve efficiencies.

  1. Mailbox Automation: Automated email processing systems can automatically sort and categorize emails based on predefined rules, extract relevant information, and route them to the appropriate departments or systems for further processing.
  2. OCR for Document Processing: Automate the extraction of data from various documents, such as shipping labels, invoices, and receipts. OCR software can scan and convert paper-based or electronic documents into machine-readable text, extracting relevant information like product names, quantities, addresses, and tracking numbers.
  3. Order and Inventory Management: Automated OCR operations can be integrated with the order and inventory management systems. When new orders are received, OCR technology can extract essential information from shipping instructions, such as item details, quantities, customer addresses, and delivery requirements and feed it into your order management systems.
  4. Improved Accuracy and Cost Savings: By automating these operations with OCR technology, the risk of human errors is significantly reduced, leading to higher accuracy and improved overall quality. Furthermore, automated mailbox and OCR operations can save costs by reducing expenses associated with manual processing.
  5. Scalability and Flexibility: Handle a growing volume of emails and documents without the need for additional manpower. As the business expands, this scalability ensures consistent and timely processing of incoming information. Additionally, OCR technology can be customized to meet the specific needs and requirements of different 3PL tasks and processes.

Challenge: Unregulated data coming from various sources, including sales and purchase forms, invoices, delivery notes, CMRs, customs documents, etc.

  • What 3PL Leaders Aspire to Achieve:

    • Building an application that gives visibility needed to determine which of the ships are underutilized, or even wasteful
    • Giving all concerned stakeholders the ability to prepare scenario-based models based on repositioning of empty containers
    • Integrating anticipatory shipping data that accurately reports or shows availability of products in a nearby hub or warehouse
    • Integrating trend analysis into a common application interface that will show various patterns of demand trends
    • Placing event-based triggers in the Transport Management System (TMS) to raise alerts on future disruptions and plan accordingly
    • Automating data input to show how many last-mile delivery drivers are required at a given time based on shipment status information

How We Can Help: Implement Our Predictive Modelling Accelerators

  1. Auto-populate data: Use of technologies such as OCR creates more robust processes for tracking of inventory levels by scanning barcodes or QR codes on incoming/outgoing shipments, enabling real-time visibility and better inventory control.
  2. Forecast Demand: Once, data related processes are automated, Predictive models can then be used to analyze historical data and other relevant factors to determine the future demand for empty containers. This can help shipping companies and container providers to proactively manage their inventory and ensure optimization of empty containers usage as well as available at the right time.
  3. Optimize Allocation: Our Predictive Modelling acceleration can help in determining the optimal allocation of empty containers to different locations or ports based on predicted demand. This can minimize the need for repositioning containers and reduce costs associated with empty container management.
  4. Optimize Route Planning: Build you customized predictive-modelling-based enterprise application that can analyze historical shipping patterns, trade routes, and other factors to optimize the routing of empty containers. By identifying the most efficient routes for repositioning empty containers, companies can reduce the time and cost required for managing their container inventory.
  5. Plan Maintenance Effectively: Analyze data related to the maintenance history of containers, environmental conditions, and other factors to predict when a container is likely to require maintenance or repairs. This can enable proactive maintenance planning, ensuring that containers are in optimal condition and reducing the likelihood of unexpected.

The Possible Impact

  • Reduce cost of maintaining manual processes by 50%
  • Automate 80% of all Transport Management System data input tasks
  • Automate 90% tasks related to empty container repositioning
  • Forecast demand for full containers and predict empty containers
  • Gain visibility into the future container shortages at locations
3PL Transformation


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