SHIPPING DATA – IT’S ALL IN THE DETAILS
Having the right data on hand is merely one step in a larger process that puts it to work. Whether you use your data effectively and to its full potential comes down to the details.
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By Quinn Nelson
ata is at the heart of everything shippers do, from refining shipping operations and lowering costs, to securing better terms and conditions in carrier contracts and providing crucially important intelligence for operational and financial leaders. Shippers often ask me if there are steps they can take to make their data more usable — not just for fulfillment and warehouse operations, but across the business for pricing strategies, accounting, and expansion efforts. The ensuing data science is often complex and unique to every organization, but several practices are broadly applicable to all shippers. Normalize Your Shipping Data One of the key findings in our “2025 Parcel Shipping Intelligence Market Survey Report” last year was that a vast majority of shippers, 91%, expect to expand their carrier networks to help reduce parcel shipping costs. A multi-carrier approach has many benefits, including more inherent resiliency and the ability to match the right parcels with the right carrier, but it also requires shippers to have a much better handle on their data. This includes ensuring that they are able to do everything from monitoring agreed-on volume tiers to comparing carriers’ costs quickly and easily in an apples-toapples fashion. Importantly, each carrier has its own vernacular for the same charges. For example, FedEx says Standard Overnight, but UPS says Next Day Saver. Yes, there are nuances, but we’re essentially talking about the same services with different names. This disparity occurs across numerous data elements within each data source and makes translating data sources into a common normalized language paramount. It’s vastly easier to analyze costs between carriers when the entire dataset adheres to the same format for important
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parameters like service, zone, currency, units of measurement for weight, units of measurement for dimensions, etc. Speak Your Own Language It is also imperative to add customized elements to your data that reflect your organization’s terminology. This allows data to be aggregated in ways that are familiar not only to the shipping operation, but also to business functions and departments that can benefit from shipping intelligence. The addition of custom data elements like account groups, business units, location names, location types, fiscal dates, and other parameters can immediately make data much more useful. It is much easier to report and apply data internally if it mimics the terminology used by everyone. Check out the difference: Unmodified: Next Day spend is elevated on account numbers 123456 and 456789 during the week of October 15. In your organization’s language: Expedited spend is elevated for the Furniture Group, impacting Outbound Shipments at the Reno DC during Fiscal Week 45 because of new delivery area surcharges for the following ZIP Codes... Combine Data Sources Carrier data is sterile and purposely limited to include only the basic data elements a carrier must provide to get paid. It is also very transportation-specific and fails to touch on the many ways that shipping practices impact the business’s operations and finances. By creating true hybrid datasets, you can combine carrier invoice, TMS, OMS, WMS, and rate shop data to obtain a far more granular view into shipping performance and costs. Previously, you only had the service, weight, location, and cost for each shipment. With a combined dataset, you can append