Network Planning Tool (NPT) Built for a Multinational Package Delivery & Supply Chain Management Company
NeoSOFT delivered this project. It is shown as an example of work, not as Sthenos past performance.
Updated
Streamlining large-scale data management and operations planning through a high-performance planning system
Client Overview
The client is a multinational package delivery and supply chain management company operating across complex logistics networks and high-volume data environments. As operations expanded globally, the organization required a centralized system to manage planning data, integrate multiple services, and support faster, more accurate decision-making.
NeoSOFT partnered with the client to design and develop a Network Planning Tool (NPT) that could process large datasets efficiently, integrate seamlessly with existing systems, and scale alongside growing operational demand.
Challenge
- Handling large datasets and complex queries without impacting system performance
- Designing a platform capable of scaling with increasing user demand and data volume
- Integrating multiple internal and external APIs while maintaining reliability
- Ensuring strong security controls to protect sensitive operational and planning data
Our Approach
NeoSOFT focused on performance optimization, modular design, and security as core principles.
Scalable Platform Architecture
A modular architecture was designed to support high data volumes and evolving business requirements without compromising performance.
Optimized Data Access
Database interactions were streamlined to reduce query execution time and improve system responsiveness for operational users.
Secure Data Handling
Authentication, authorization, and encryption mechanisms were embedded into the platform to protect sensitive logistics and planning data.
Seamless System Integration
APIs were structured to support smooth communication between systems, improving reliability and reducing integration friction.
Technical Spotlight
- Efficient ORM and Database Optimization: Hibernate was used to optimize object–relational mapping, reducing query overhead and improving database performance.
- Microservices-Based Architecture: Spring Boot enabled modular development, allowing independent services to scale and evolve without disrupting the system.
- Robust Security Framework: Spring Security enforced authentication, authorization, and data encryption to safeguard sensitive information.
- Enterprise-Grade Backend: The platform was designed to handle high concurrency and large datasets while maintaining consistent performance.
Solution Delivered
- Optimized query execution improved system responsiveness
- Scalable architecture supported growing data and user demand
- Secure API integrations enabled reliable system communication
- Centralized planning data improved operational visibility
Results
- Improved efficiency, driven by faster data access and streamlined workflows
- Better API integration, improving system reliability and data consistency
- Faster query performance, enabling quicker operational insights
- Improved scalability and stability across logistics planning operations
Tech Stack
A Network Planning Tool (NPT) for a package delivery and supply chain management company, centralizing planning data and integrating the services its operations depend on. Working across complex logistics networks, the company needed faster, more accurate decisions from a system that could handle large datasets and complex queries.
A package delivery and supply chain management company.
A centralized system for planning data, integrated with existing systems.
Independent services scale and evolve without disrupting the rest of the system.
Authentication, authorization and encryption, with Hibernate for object-relational mapping.
On this page
- The planning challenge, and what the tool delivered
- How a planning request moves through the tool
- The tool's layers, from planners to planning data
- Related logistics and Java pages
The planning challenge, and what the tool delivered
The four challenges the case study lists, beside its four Solution Delivered items.
Why planning was hard
Challenge- Handling large datasets and complex queries without impacting system performance
- Designing a platform capable of scaling with increasing user demand and data volume
- Integrating multiple internal and external APIs while maintaining reliability
- Ensuring strong security controls to protect sensitive operational and planning data
What the tool delivers
Solution delivered- Optimized query execution improved system responsiveness
- Scalable architecture supported growing data and user demand
- Secure API integrations enabled reliable system communication
- Centralized planning data improved operational visibility
How a planning request moves through the tool
The case study describes the tool by capability. Followed through one planning request, they read as four stages.
- An operational user signs inSpring Security enforces authentication and authorization before any sensitive planning data is reached.Spring Security
- A service takes the requestSpring Boot microservices handle it as independent services that scale without disrupting the rest of the system.Spring Boot
- The data comes back fastHibernate and streamlined database interactions cut query execution time, keeping the tool responsive for operational users.Hibernate
- Other systems stay in stepStructured, secure APIs connect internal and external systems, and centralized planning data improves operational visibility.APIs
The tool's layers, from planners to planning data
The layers the case study describes, from security at the edge down to the planning data, with the integrations beside them.
Figure 1. Security, services, data access and integrations
Each layer restates the Technical Spotlight: Spring Security for authentication, authorization and encryption; Spring Boot microservices; Hibernate object-relational mapping; centralized planning data. Integrations with internal and external APIs sit beside the services, as the Challenge and Solution Delivered lists describe.
Related logistics and Java pages
The logistics industry page, Java and enterprise services that match the tool's stack, and a second logistics case study.
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