The Ultimate Guide to Shipment Data 2021
What is Shipment Data?
The shipment of cargo is the most crucial aspect of any economy as it facilitates exports and imports of goods. Export and import are indicators of a country’s economical well-being. For manufacturing and retail organizations, understanding shipment data is a critical aspect of tracking down the day-to-day running of operations. As a crucial driver of the supply chain of any given business, shipment data helps business organizations to quantify their shipping metrics and work on ways to improve them.
How is Shipment Data collected?
Shipment data is often collected and compiled by logistics companies that are directly involved in the shipping business. However, aided by proper documentation, companies can also keep a copy of their shipment data when they receive or dispatch goods. By working hand-in-hand with shipping companies and logistics-based government agencies, businesses are also in a better position to collect shipment data.
What are the attributes of Shipment Data?
Shipment data consists of information that pertains to the qualities of the cargo and transport moving it. This data gives details about the weight of the cargo, cubic metrics, the destination of the shipment, shipper, consignee, loading number, departure date, and arrival dates. Furthermore, shipment data offers a view of the total cost of carrying, loading, unloading, and transferring cargo.
What are the uses of Shipment Data?
When businesses decode their shipping data, they are in a better position to carry out a quantitative and qualitative analysis of their shipping metrics. Based on the core attributes of shipment data, businesses can build their shipping profile by:
• Comprehending the shipping weights of the cargo
• Knowing which zones they ship to and from
• Assessing how the business takes care of the billing aspect of the whole shipping process
• Fully comprehending the technical specifications is crucial in the management, consolidation, and packaging of shipments
• Evaluating the synchronization aspect of various company departments in different geographical locations
• Determining the robustness of the organization’s shipment and tracking technology to get an insight into the best alternatives.
When businesses have a developed shipment profile that is drawn from shipment data, they are placed to have a ‘panoramic view’ of the whole shipping operations. This clear view of operations is used by organizations to plan their budget and arrest any mistake that might arise during the shipping process.
How can a user assess the quality of Shipment Data?
Operationally, users of shipment data can define data quality by taking into account the aspect of quality parameters and quality indicators. A data quality indicator is a data attribute that gives objective information concerning the data. Sources, time of creation, method of collection are examples of a quality indicator. On the other hand, the data quality parameter refers to a qualitative dimension through which a user assesses the data quality. Factors such as credibility and timeliness are perfect examples of quality parameters. Based on this analysis, the dimensions of data quality management (DQM) objectives for shipment data involves taking into account the following general accounting settings:
- Accuracy/correctness - can the shipment data be verified as true when compared to other sources?
- Level of completion - are there gaps in the data provider’s shipment dataset?
- Timeliness - can the data provider supply real-time shipment updates?
- Consistency - does the shipment data provider offer reliable cutsomer service?
How can I get Shipment Data?
You can get Shipment Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Shipment Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time Shipment Data APIs, feeds and streams to download the most up-to-date intelligence.
What are similar data types to Shipment Data?
What are the most common use cases for Shipment Data?
The top use cases for Shipment Data are Supply Chain Intelligence.