With Predictive Analytics there is no guesswork
The Predictive Power to Avoid Risk & Target Omnimodal Opportunity
Boost your transportation team with superior business intelligence. Steer clear of risk and toward opportunities for improvement. Our advanced business intelligence and analytics tools empower decision makers with data-driven accuracy. Users no longer have to create data cubes or manipulate data to derive intelligence and insights into decision-making. Our analysis tools transform raw data into robust information that can be easily displayed and shared.
Perform advanced analysis with a point-and-click interface. Quickly identify the summaries, exceptions, and anomalies you’re looking for. These data points are critical for your transportation supply chain efficiency. Reports can be scheduled as needed to ensure timely access to critical information.
Processing Capacity That Keeps Your Supply Chain At Its Best
The easier it is to access shipment analytics, the easier it is to integrate them into your ongoing business processes. While other solutions take hours or even days to display and manipulate high volumes of data, MercuryGate TMS shipment data is available within minutes.
Our platform enables terabyte-scale analytics in real time, predefined best-practice key performance indicators (KPIs), and reports and dashboards with easy-to-follow visualizations. Data models are managed with a simple drag and drop. The platform provides mission-critical data across any device, including desktops, tablets, and smartphones.
The platform can predict capacity needs for any given lane (e.g., estimations based on loads picked up and dropped off). It can also calculate ongoing changes within the final mile, especially for couriers. It determines capacity in advance of actual demand by using historical information and data from various third parties. All while considering the unique needs and activity that occur within the final mile.
Machine Learning for the Ongoing Advantage
Our TMS also feeds critical business intelligence back into the platform, enabling machine learning. For example, many shippers use a reverse auction process to allow their preferred carriers to bid on loads. These auctions typically are determined by historical data by lane and adjusted to meet the current business needs of the shipper.
These analytics feed back into the platform so that the solution learns the best way to manage freight. Users can enhance the data model to factor in unique constraints when considering routes – whether it’s the long-haul of an inbound shipment or the final-mile delivery to a third-party reseller or end-user. Data can then be embedded into processes to improve the overall effectiveness of routes using historical transit information as well as other data.
Predictive Analytics for Invaluable Prescriptive Insights
The TMS provides users with insights that continuously evolve. At the moment of action, users can see future arrival times with a predictive ETA, assess the likelihood of outside influences, and know that a delay might occur before the shipment is ever executed.
This supports more transparent communications between TMS users and their customers and further builds customer rapport regarding their purchase delivery details.