Data Verification in the Logistics Outsourcing Tender Process

I recently had three separate conversations about logistics tenders and how they haven't gone to plan.

In the first conversation, a company provided a significant amount of data which should have allowed the third-party logistics company (3PL) to provide an accurate quotation for the business.

However, this was not the case. The volumes despatched from the current supplier was significantly understated and this had an impact, not only on the resource requirement but also on the existing operation. The tender was quoted for, based on a certain set of figures which would fit in with the volumes currently received and despatched by other clients in the shared-user warehouse operation.

The second conversation discussed terminology in the warehouse and the misunderstanding between two parties. The tender data suggested that there was a large number of single SKU (stock keeping unit) pallet despatches. This would require forklift truck movements directly from the racking to the outbound area. However, this was not the case. The pallet despatches related to picked pallet quantities and not full pallets - in fact, there were no full, single product line despatches at all.

Having relayed this conversation to another colleague, he recalled a situation where the tender documents showed a mix of full pallet picks and picked cases with an 80/20 ratio in favour of full pallet, single SKU picks. This was queried by the operations team, but the sales team were adamant that the ratio was correct.

It turned out that the full pallet pick was the first stage operation where products were picked in bulk quantities, in full pallets, to be broken down into single item despatches. The picked cases related to less popular items which sold in lower quantities.

The profile of the client was such that it was very unlikely that customers would take full pallet deliveries, yet the sales team were adamant that this was the case.

So, what do we learn from this?

Firstly, 3PLs need to verify data and, where possible, visit the customer’s premises to see at first hand the operation and understand what the processes are. They need to clarify the terminology used and ensure they are happy with the data. It is always difficult to make assumptions if the operation is different to previous contracts.

This may not always be possible if the warehouse is being operated by an existing 3PL. However, if operated by the company outsourcing the work, there is no excuse.

Secondly, the operations team need to be involved at an early stage to verify the data and, where possible, discuss the operation with the potential client's operations team.

In a subsequent conversation, it was revealed that the 3PL had not had any contact with the operations team, had not visited any of the sites and had only dealt with the procurement team who were not experienced in logistics.

As a consultant involved in assisting clients in putting tenders together, I always find it useful to do the following when managing the data sharing:

Quotations can be wildly inaccurate if based on poor data. This will lead to companies being awarded contracts based on spurious data. If these anomalies are picked up at the implementation stage, then it will result in some acrimony and the need to renegotiate the contract at this stage.

If the anomalies are not picked up until the volumes are in excess of the expected number, this can have a significant effect on the operation and not only affect the new client, but also existing clients if it is a shared-user operation.