Many logistics organisations are investing in the automation of business processes. New software, system integrations, and dashboards providing real-time insights.
Still, most working days start in the same way.
A planner is looking for a missing document. A colleague is correcting a consignment note that has been entered incorrectly. A consignment is held up at the border because a field has not been filled in.
Research shows that logistics teams lose an average of 8 hours a week correcting, searching for and re-entering data. For a team of five people, that amounts to one full working day a week. Week in, week out.
The systems are working. The data being fed into them isn’t.
That is the problem that undermines most automation projects in logistics. It is not the technology, but the quality of the information coming in at the front end.
In this blog, you’ll find out why this happens, how much it costs and where to start.
Every day, time is wasted on work that really should already have been done.
A planner is looking for a document that is somewhere in an email inbox. A colleague is entering details from a consignment note into a system. A consignment is held up because a field has not been filled in.
These are not exceptions. For many logistics teams, this is the reality of everyday life.
The problem doesn’t lie with the systems. They’re doing what they’re supposed to do. The problem lies in what comes in at the front end: orders sent by email; incomplete attachments; fields filled in manually based on experience; and data being retyped from one screen to another.
If you automate this process without addressing the root cause, you’ll simply be processing the errors more quickly.
When data is checked immediately upon receipt, it brings about a structural change in the operation. Planners no longer have to chase up missing information. Documents no longer need to be checked manually before a consignment leaves the premises. The day begins with work that is moving forward.
Research shows that manual data processing in logistics leads to errors in 3 to 5 per cent of transactions, and that rectifying these errors takes up 25 to 35 per cent of administrative time. Automated validation at the point of entry reduces the error rate to below 1 per cent.
What this means financially depends very much on when an error is discovered. An error found immediately upon entry costs an average of 1 to 5 pounds to rectify. The same error, if it only comes to light during a customer or customs inspection, can easily cost 50 to 500 pounds.
Suppose a logistics organisation processes 500 consignments per month with an error rate of 4 per cent. That amounts to 20 consignments per month containing an error. If, on average, these errors are only detected late in the process, we estimate a correction cost of £150 per error. That amounts to £3,000 per month, or £36,000 per year.
With a validated intake process, the error rate falls to below 1 per cent. Two corrections per month instead of twenty. The savings: more than £32,000 per year, excluding the indirect costs of border delays, empty return journeys and lost planning time.
(Sources: ISOPro Software, 2025; Lido App, 2026)
Trouvé has Fluentia Developed as an AI-powered platform that automatically extracts, interprets and processes unstructured logistics data. The system tackles the problem at its source: at the intake stage.
In practice, this means that a consignment note received by email is automatically processed. Any missing fields are flagged immediately. A dispatcher no longer needs to search for information, make phone calls or retype details manually. The data is already in the system, validated and complete.
Fluentia integrates with existing systems such as TMS, WMS and ERP. The team’s way of working remains the same. What changes is how much time is left for work that really matters.
Validated data intake does not have to be a major IT project. The first steps are operational, not technical.
First, identify where data comes from. Email, portals, scans, handwritten documents. Every source poses a potential risk if it is not validated.
Next, define which fields are mandatory for each document type. What is the minimum information required on a consignment note to process a shipment? What must a customs document always contain? These fields form the starting point for validation.
Next, identify where data is being entered twice. Every time someone transcribes data from one system to another, there is a potential for an error to occur. These instances are the priority.
Download the Fluentia white paper or book a demo. Then we’ll look at your intake process together and identify where there’s room for improvement.
Most errors do not arise within the system itself, but during data entry. Incomplete documents, manual data transfer between systems and missing mandatory fields are the main causes. As long as data enters a system without being validated, automation merely passes the errors through the chain more quickly.
Digitisation means that documents and data are available in digital form. Automation means that systems process and pass on data independently. Validation at the intake stage is the link between the two: without validated data, automation cannot produce reliable results.
The initial effects become apparent as soon as the validation rules have been set up and the intake channels have been configured. The amount of correction work decreases immediately. The financial impact becomes measurable within the first month.
Fluentia scales in line with the size of the operation. The first step is a analysis of intake channels and document types, regardless of the organisation’s size.