Decision Support System
What is a Decision Support System?
A decision support system (DSS) provides data, analysis, and insights to organizations, to help guide their decision-making process. It integrates information from multiple sources, applies analytics and modeling techniques, and presents the data in a user-friendly way.
Most platforms include features such as data visualization, advanced analytics, and collaboration capabilities, which allows organizations to get a deeper look at the data, identify patterns, and gain actionable insights. By adding automated analysis and utilizing technologies such as AI and machine learning, decision support systems provide decision-makers with timely, updated information to support their strategic and operational choices.
What is the Overall Goal of a Decision Support System?
The primary goal of a decision support system is to provide actionable insights to relevant parties. This aids them in making better decisions for their business. For example, in the maritime industry, a DSS will show real-time updates regarding delays, weather, and port activity. This information allows organizations to adjust their ETAs, or change routes to avoid unnecessary delays.
Maritime AI™ Decision Support Streamlines the Shipping Process
The shipping supply chain consists of millions of moving parts, and a problem with any one of them can result in fees, fines, and unhappy customers. Using a decision support system will provide you with real-time information that will give you insights needed to keep everything running as smoothly as possible.
Here are some of the advantages of using a decision support system for your shipping needs:
- Supply chain and container tracking visibility: get real-time visibility into the complete supply chain and container tracking processes. This allows all the relevant stakeholders to monitor the movement of vessels and containers, track their locations, and gain insights into inventory levels. This visibility helps optimize logistics, streamline operations, and improve overall supply chain efficiency.
- Risk and compliance management: with access to thousands of data points and records, the Maritime AI™ DSS provides enhanced due diligence to help organizations avoid sanctions and mitigate risk. The platform works with top data providers, such as LexisNexis and real-time behavioral data, to highlight any risk exposure, so it can be handled before it evolves into a sanctions violation.
- Behavioral patterns, anomalies, and global trends detection: with integrated advanced analytics and machine learning algorithms, the platform quickly identifies behavioral patterns, anomalies, and global trends in maritime operations. It has the capabilities to analyze thousands of data points, such as vessel tracking, satellite imagery, and historical records, which it uses to detect suspicious activities, recognize exceptions, monitor vessel behavior, and identify emerging trends.
Characteristics of a Decision Support System
Regardless of the industry, a decision support system needs to have the following attributes:
- Data integration: the system must integrate data from multiple sources, both internal and external, to offer a complete overview of the decision context. It combines structured and unstructured data to support analysis and decision-making.
- Analytical capabilities: it takes the data and incorporates advanced analytical techniques – such as statistical analysis, data mining, simulation, and optimization – to extract insights from data. These capabilities enable organizations to analyze complex scenarios, assess risks, and evaluate alternative options in real-time.
- User-friendly interface: an overly complicated user interface makes it more difficult for non-technical users to understand and act on the data. To avoid this, most DSS use data visualization, interactive reports, and graphical representations, so anyone can quickly digest the data and make the right decision quickly.
- Flexibility and adaptability: a flexible and adaptable platform allows organizations to customize models, parameters, and reports based on specific requirements. It understands different decision contexts and can adapt to the organization’s specific business conditions.
- Decision collaboration: businesses don’t work in a vacuum, so a DSS platform needs to support collaborative efforts by sharing the data among all relevant stakeholders.
- Integration with existing systems: DSS integrates with existing systems and data sources within an organization to leverage data assets and ensure data accuracy. It can be implemented into existing workflows via API.
