How SFL helped Southern Africa’s largest independent neutral consolidator recover 396 hours every month, bring shipment data into CargoWise earlier, and create a path from managed execution to automation.
A single consolidation could contain more than 20 individual shipments.
For Southern Africa’s largest independent neutral consolidator, that was normal operating scale. The problem sat behind the freight. Several overseas partners were not using CargoWise, which meant the shipment information arriving from them still had to be recreated manually inside the client’s own CargoWise environment.
Multiply that across 20 or more shipments in a consolidation and the administrative burden grew quickly. Experienced operations staff were spending valuable hours creating shipment records instead of planning the movement, monitoring exceptions and preparing for arrival.
More importantly, the data was often entering CargoWise too late.
By the time shipment records were complete, the cargo could already be approaching destination. The information was technically in the system, but the operation had lost the window in which that information was most useful: the time before arrival, when teams could anticipate requirements rather than react to them.
The client was growing. Simply adding more local staff to keep pace with the data was not a sustainable answer.
The Client
The client is the largest independent neutral consolidator in Southern Africa, providing global inbound and outbound consolidation, transport and warehousing services through an extensive international partner network.
Established in 2006, the business operates on a strictly neutral model, serving the freight-forwarding community rather than competing for the underlying shipper relationship. Its wider service portfolio includes ocean imports and exports, road freight, transshipment and warehousing, with connections across global trade lanes. Today, the organisation continues to position itself around high-frequency consolidation services and stronger connectivity across African markets.
That neutrality makes operational execution particularly important. The company is not simply moving freight; it is operating as the consolidation layer behind other freight forwarders. Every consolidation therefore carries multiple shipment records, documents, rates and milestones that have to be accurate and available when the operating team needs them.
At the time of the engagement, the client’s network extended to approximately 300 destinations across five continents. The physical network had scale. The information-processing model needed to keep up with it.
The Problem: Shipment Volume Was Creating an Equal Growth in Administration
The pressure first appeared in import documentation.
Because a number of overseas partners operated outside CargoWise, their shipment information arrived through external documentation and then had to be keyed again into the client’s system. With more than 20 underlying shipments possible within a single consolidation, the operation could be recreating large volumes of information before the local team could work with the complete file.
The challenge was amplified by the availability of CargoWise-skilled resources in the local market. Recruiting additional staff took time, and new employees then had to be trained on both CargoWise and the operating processes around it. As volumes increased, using local headcount to absorb every new increment of data entry would have made the business increasingly dependent on a scarce skill base.
There was a second pressure point in Rates.
Volatile market conditions meant promotional rates and carrier tariffs needed frequent updating. Rate Procurement had to keep new trade-lane pricing current for customers while maintaining the data required by the operation. Too much of the team’s capacity was being spent preparing and updating rate sheets when its greater commercial value lay in analysing buying positions and improving box profitability.
The issue was therefore broader than labour cost. Two specialist functions were spending time maintaining information that the business absolutely needed, but that did not require those specialists to perform every step themselves.
The client needed additional capacity without allowing administrative headcount to rise in direct proportion to shipment volume.
Why SFL: CargoWise Capacity Without Starting a Recruitment Cycle
SFL’s answer was not conventional outsourcing.
Moving the work to people who still needed extensive CargoWise training would simply have moved the client’s problem somewhere else. SFL could provide resources who already understood the platform and could operate directly inside the client’s CargoWise environment.
That meant the operating model could be separated more deliberately.
The client’s local teams would retain the work where their knowledge mattered most: shipment planning, exception management, customer decisions and commercial optimisation. SFL would take responsibility for the structured, repeatable system activity consuming that capacity.
There was also a longer-term rationale behind the model. SFL did not view additional back-office resources as the final state. Running the processes gave the team detailed visibility into where rules were consistent enough for automation to replace manual execution later.
That combination—immediate managed capacity followed by progressive automation—was the important design decision.
The SFL Solution: Get the Data Into CargoWise Before the Team Needs It
SFL assigned two dedicated CargoWise-trained resources in India to the client’s import operation.
Overseas documentation could be sent to the SFL team as it became available, allowing shipments and consolidations to be created in CargoWise without waiting for the local operations team to find time around its other responsibilities.
The value was not simply that somebody else performed the data entry.
The information began entering CargoWise earlier in the shipment lifecycle.
That gave the local team a more complete view of incoming freight before arrival and changed what it could do with the time available. Instead of using the pre-arrival window to build records, Operations could use it to review the consolidation, identify gaps, prepare the movement and manage the exceptions that required local judgement.
Across import documentation, the new model returned 264 hours every month to the operation.
SFL then extended the same principle into the client’s commercial process.
Two additional trained resources took responsibility for maintaining promotional rates and updating tariff information inside CargoWise. The purpose was not merely to produce rate sheets faster. Keeping the rate information current in the system meant Sales and Operations had better access to the data required for quoting and auto-rating, while Rate Procurement could redirect time towards carrier strategy and box profitability.
That released a further 132 hours per month.
Together, the two workstreams gave the client four dedicated CargoWise resources without requiring another cycle of local recruitment, onboarding and platform training.
The Next Gain Was Not More People. It Was Less Data Entry.
Once the processes were operating through a more controlled model, SFL could see where the next efficiency would come from.
Payable invoices were one such area.
Rather than continuing to treat document entry as work that simply needed additional processing capacity, SFL began introducing OCR-driven invoice capture, including validation between accrued and actual costs. The objective was to extract structured information from the incoming document and reduce the amount of information that had to be entered manually before financial validation could take place.
That progression matters because it shows where SFL’s managed-services model is intended to lead.
The first step solved an immediate capacity problem. The next step began removing the repetitive activity itself.
It also reflects SFL’s current approach to CargoWise data automation, which includes OCR-driven document ingestion, rule-based shipment creation, rate and surcharge logic, validation controls and automated financial processes. The aim is not automation detached from operations; it is to structure the process first, understand the exceptions, and then automate the activity that can be executed reliably without unnecessary human intervention.
The Results
The clearest outcome was capacity.
396 hours returned to the business every month.
Import documentation accounted for 264 hours per month, as SFL’s dedicated resources took responsibility for the high-volume shipment and consolidation entry associated with overseas partner documentation.
Rate maintenance returned another 132 hours per month, allowing the client’s procurement specialists to spend less time maintaining rate information and more time on the commercial decisions that influence box profitability.
The client also gained four trained, dedicated CargoWise resources without having to recruit and develop that capability locally.
But the operational result was more important than the hours alone.
Shipment information could be available in CargoWise earlier, giving Operations more time to plan before arrival. Rate data was maintained in the system rather than depending as heavily on manually prepared rate sheets. And the processes SFL had taken over became candidates for further automation instead of simply becoming permanent manual workloads in another location.
- 264 hours saved every month on import documentation
- 132 hours saved every month on rate maintenance
- 396 hours total monthly capacity returned to the operation
- 4 Dedicated CargoWise-trained resources
What Changed Was Not Just Where the Work Happened
It would be easy to describe this as a BPO engagement.
That misses the more important outcome.
The client had reached a point where increasing freight volume was also increasing the amount of administrative work required to support it. More consolidations meant more shipment records. More volatile pricing meant more rate maintenance. The conventional response would have been to keep adding capacity behind those activities.
SFL changed that relationship.
The first step was to move structured CargoWise work away from the specialists whose time carried greater operational and commercial value. That immediately recovered capacity and, in the case of import documentation, brought information into the system early enough to be more useful.
The second step was to use the visibility gained from running those processes to determine which activities could be automated rather than continually resourced.
That is particularly important for a consolidator. The entire commercial model is built around creating efficiency through scale. The information layer supporting that model should be capable of doing the same.
For this client, the result was 396 hours returned every month, earlier operational visibility, stronger rate maintenance and a clear route towards reducing manual document processing further.
Is Data Entry Still Growing With Your CargoWise Volumes?
For established CargoWise operators, manual workload can increase quietly as shipment volumes, partner networks and rate structures become more complex. The platform may be capable of supporting the growth while the activity surrounding it continues to consume more people.
SFL Tech helps logistics businesses change that equation through CargoWise optimisation, managed operational support, master-data governance and automation. Rather than simply moving repetitive work to a lower-cost location, SFL looks at which activities need specialist judgement, which can be centralised, and which should ultimately be removed through automation.
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