For 11 years, RPM has evolved into a leading non-asset-based supply chain solutions company operating in North America and European regions. As RPM continues to grow, our tools must stay up-to-date with the world's tactical and technological advancements. As of November 2023, Hydra has been a primary asset for our teams, improving productivity and supporting operations on the front end.
What Is HYDRA?
Hydra is RPM's proprietary, cutting-edge pricing engine, specifically designed to revolutionize how RPM forecasts lane prices for carriers throughout operations. This innovative solution combines the power of advanced machine learning techniques with the effectiveness of ensemble learning. Hydra was created to address the complex challenges associated with pricing in the carrier industry, offering highly accurate predictions and enhanced decision-making capabilities for our shippers and carrier network. Hydra's strength lies in its ability to leverage internal features, such as historical pricing data and carrier-specific information, and external market features, providing a comprehensive pricing approach that accounts for internal dynamics and external market conditions.
How was HYDRA Developed?
The development of Hydra as a concept was inspired by the pressing need for more accurate and efficient pricing solutions. The logistics sector has long grappled with fluctuating market conditions, complex pricing models, and the need for real-time decision-making. Recognizing these pain points, RPM envisioned Hydra as a solution that could leverage the power of machine learning to address these issues effectively.
The inspiration behind Hydra stemmed from the desire to equip RPM's team with fast, market-appropriate pricing when working with the valued carrier network operating daily. Hydra was born out of the aspiration to simplify and enhance the pricing process, enabling all representatives to make data-driven decisions, optimize their pricing strategies, and stay ahead in a highly competitive market landscape.
How will HYDRA Impact RPM?
The development of Hydra was rooted in the need for a more strategic and data-driven approach to pricing within the logistics industry. RPM's primary goal was to create a tool that would enable us to accurately find the appropriate market rates for transporting vehicles from origin to destination, using historical knowledge, specific carrier information and preferences and external market factors.
Hydra's main impact comes from enhancing the pricing strategy, improving cost-efficiency, and increasing profit margins by leveraging advanced machine learning techniques and data analysis. Hydra enables RPM to remain competitive in the market while providing our customers and partnered carrier networks with reliable and cost-effective transportation solutions.
What Roles Are Needed For the Project?
The development of Hydra involved a multidisciplinary team with a range of roles and expertise to bring the project to fruition. Here are some of the critical positions that are necessary to program and develop Hydra-
- Data Scientists- Data scientists played a pivotal role in developing the core algorithms and models used in Hydra. They are responsible for data preprocessing, feature engineering, and implementing machine learning algorithms.
- Software Developers- Software developers are crucial in building Hydra's infrastructure and software framework. They worked on the backend systems, APIs, and user interfaces required to interact with the pricing engine. Their role was to make Hydra user-friendly and accessible to stakeholders.
- Data Engineers- Data engineers are responsible for designing and maintaining data pipelines to feed Hydra with internal and external data sources. They ensured data quality, reliability, and real-time updates to support accurate pricing predictions.
- Domain Experts- Domain experts provide valuable insights, business knowledge, and domain-specific features essential for accurate pricing predictions.
- Product Owners- Project owners oversee the development process, set project goals and timelines, and coordinate the various teams involved. They ensured that the project stayed on track and aligned with business objectives.
- Quality Assurance (QA) Testers- QA testers conducted rigorous testing and validation of Hydra to ensure its reliability, accuracy, and robustness. This role identifies and addresses any bugs or issues that arise during development.
Collaboration among these diverse roles was essential to the successful development of Hydra. Their combined expertise in data science, machine learning, software development, domain knowledge, and project management was crucial in creating a powerful pricing engine that meets the transportation industry's needs.
What are the technological advancements in this project?
The creation of Hydra brought about several technological advancements that have significantly improved RPM's capabilities within the logistics and automated technology space. Some of the critical technological advances achieved through Hydra include:
- Advanced Machine Learning- Hydra leverages advanced machine learning techniques to predict highly accurate carrier prices.
- Ensemble Learning- Hydra employs ensemble learning, a sophisticated technique that combines multiple machine learning models to enhance prediction accuracy.
- Real-time Data Integration- Hydra incorporates real-time data integration capabilities to ensure pricing forecasts are based on the latest internal and external market data. This real-time aspect is crucial for staying up to date with rapidly changing market conditions.
- Predictive Analytics- The development of Hydra has advanced the company's predictive analytics capabilities, enabling it to make informed decisions about carrier prices, optimize pricing strategies, and maximize profitability.
- Post Implementation- Post launch, RPM is continuously learning about changing market conditions and economic trends to provide a targeted price for customers and carriers alike.
These advancements empower the company to make more informed decisions, enhance pricing strategies, and remain competitive in the transportation industry by staying ahead of market trends and changes.
Conclusion
With the vision of equipping our team with advanced support and resources, RPM continues to add new tools to the arsenal. Hydra has led to several technological advancements within the organization, bringing machine learning, data integration, automation, and predictive analytics into an organized, concise, and efficient package. These advancements empower RPM's team to make data-driven decisions, enhance pricing predictions, and remain competitive in the logistics industry by staying ahead of market trends and changes. RPM is excited to evolve Hydra as our primary premiere pricing engine.
