The packing list arrives by email. Someone downloads the PDF and drags the attachment into the shipment dossier. The warehouse has the document. The receiving team knows where to find it.
Then someone asks for the business case for robotic unloading. How many cartons do you handle? What sizes and weights arrive? How much time and money does each type of load take today?
Answering those questions means opening attachments, finding another spreadsheet, or asking the customer. The WMS tracks the stock, but the detail needed to support the investment decision sits elsewhere.
Missing carton data does not prevent us from implementing a robot. Our robot uses AI to handle a wide range of packages. A complete database of dimensions and weights is not an implementation requirement.
The gap matters when you want a detailed, well-supported ROI case. Better data helps you explain the expected return, test the assumptions, and decide where automation creates the most value.
Why the data is missing
If carton dimensions and weights play no part in your current receiving, storage, or billing process, there is little operational pressure to maintain them. The WMS might support the fields while your team has no reason to fill them in.
In conversations with logistics operators, we see both missing and disconnected data. Sometimes carton measurements were never recorded because the WMS workflow did not need them. Elsewhere, a product export holds dimensions while a separate inbound export lists container contents.
A PDF attached to a dossier preserves the paperwork. The attachment alone does not create structured carton records. A person still has to connect the shipment, the product, and the packaging.
What missing data does to your ROI case
A container count tells you how often work arrives. Carton counts, dimensions, and weights describe the work inside. Linking those records to actual unloading times and costs shows how the workload varies.
An average cost per container is a useful starting point. A stronger case also explains which loads drive the cost, how often they arrive, and whether the sample represents a normal year. Quiet weeks and peak periods deserve separate attention.
Carton measurements alone do not predict unloading speed or savings. They describe the mix behind your assumptions. Combined with observed handling times and robot performance, they help you judge how well a trial represents the wider operation.
Without this detail, the first estimate needs broader assumptions. As the record improves, you have more evidence for the volumes, costs, and utilization behind the return.
Record the data behind the decision
Build a record connecting the incoming load to the work performed and the cost incurred. Start with these fields.
| Data to capture | How it supports the case |
|---|---|
| Container reference and arrival date | Connect the records for each load and show volume, arrival patterns, and seasonal peaks. |
| Customer, SKU, pack format, and carton count | Describe the mix and quantity of handling units. Keep product units and units per carton separate from carton counts. |
| Carton dimensions and gross weight | Describe the physical workload. Record outside length, width, and height, plus weight including packaging, with explicit measurement units. |
| Unloading time and crew involvement | Establish current labor hours per load. Two people working for two hours means four labor hours. Record waiting and downstream work separately. |
| Labor or contractor cost | Use fully loaded hourly costs or the contractor’s charge per container, plus relevant extras. Avoid counting the same work twice. |
| Exceptions and data source | Record damage, rework, and unusual handling. Mark values as measured, supplier-provided, or estimated, and retain their source and date. |
Measure the shipping carton you handle. Retail-unit dimensions describe a different package. The GS1 Package and Product Measurement Standard provides a repeatable convention across packaging levels, including when to update measurements.
Keep unknown values visible. A clearly marked gap is more useful to a decision-maker than an estimate presented as a measurement.
Start with two separate exports
If dimensions and container contents live in different systems, start with two CSV files or spreadsheet tabs. They give you a connected picture of the workload for the ROI calculation.
Export 1: carton specifications
Use one row per customer, SKU, and pack variant. Include outside dimensions, gross weight, units per carton, and any relevant packaging notes. Add the source and last verification date.
Give different case packs separate identifiers and update the record when packaging changes.
Export 2: container contents
Use one row per container, customer, SKU, and pack variant, with the carton count and arrival date. Repeat the shared identifiers exactly as they appear in the specifications file. Mark whether counts are expected or confirmed at receipt.
If an export only shows product units, establish the case pack before calculating carton counts. Record partial or mixed cartons separately.
Match the records using shared identifiers
Match customer or account ID, SKU, and pack identifier together. A SKU alone risks matching the wrong customer or packaging variant. Each contents row should match one specifications row. Flag missing or duplicate matches.
Here is a fictional example. The specifications file describes account DEMO, SKU ITEM-01, pack CASE-12: 400 × 300 × 250 mm, 7.2 kg gross, 12 units per carton. The contents file lists 80 cartons of the same combination in container DEMO-001. Together, those rows describe 80 handling units containing 960 product units.
Use the container reference to connect this workload to unloading times and cost records. Check carton totals against the packing list and retain unmatched rows as visible gaps in the analysis.
How we help get the data out
We help operations teams export and combine their data. We have built integrations for nearly all WMS platforms commonly used in the Netherlands. Existing records often provide a useful starting point for the business case.
Where a packing list only exists as a PDF, ask for the underlying spreadsheet or extract the rows and check them against the document. Confirm whether quantities mean pieces or cartons. An export will not recover measurements nobody recorded, so request those from the supplier or measure representative cartons.
Our robot’s AI handles variation in the package mix. The purpose of connecting these records is to give your operations and finance teams better evidence for the investment decision.
Build the case around representative work
Start with a sample of recent containers and expand across customers, load types, and busy periods. Compare current costs with expected robot performance, the robot fee or investment, and the labor and operating costs still required after automation.
Keep the work being compared consistent. If the current bill includes sorting and palletizing, identify which parts the proposed setup covers. Separate hours freed for other work from cash costs you expect to remove.
Test lower-volume and slower-throughput scenarios alongside the expected case. Use observed performance to refine the assumptions. Our container unloading ROI calculator provides a starting estimate. Your own records help turn the estimate into a more substantial case.
Start keeping the record now
Begin capturing the useful detail on incoming shipments as early as possible. Keep carton specifications, container contents, handling times, and costs linked. Assign responsibility for maintaining the records and updating packaging changes.
Start with the fields you already have and add the missing detail as work arrives. A growing record gives you a stronger basis for comparing investments, planning capacity, and understanding the cost of serving different customers.
When the next automation decision comes, you will have evidence from your own operation to support it.
Common questions
No. Our robot uses AI to handle different packages. Complete carton records strengthen the ROI analysis, but they are not an implementation requirement.
No. Separate exports work when shared identifiers connect them reliably. Add time and cost records through the container reference to support the financial comparison.
Start with what is available and label the assumptions. We help with exporting and connecting existing records. Improve the dataset over time and refine the business case as evidence accumulates.
Build an ROI case from your own data.
Share the records you have. We'll help connect them and work through the business case for your operation.
