I recently conducted a Request for Proposal (RFP) for a project that seemed pretty straight forward, however, everything that could possibly go wrong during a sourcing event went wrong! A lot of time, confusion, and frustration could have been avoided if the data collected was clean and accurate.

The purpose of the engagement was to identify a supplier that would provide secondary packaging items used to protect the goods inside of another form of packaging. This is a savings category we source for a number of clients, and we have a lot of experience in it. We received usage reports and data from both the client and supplier, which we combined to create the market basket that each alternate supplier would bid on during the RFP process. Once we received the proposals, it was clear that there were issues with the bids as there were major differences in the price proposed for each item across the participating suppliers. As a result of further analysis of the proposals, it was determined that the suppliers were not quoting "like for like" or providing quotes for the exact items contained in the market basket due to inaccurate information in the RFP.

This was a major problem -- it is impossible to evaluate the current market and develop accurate targets if the pricing submitted by a supplier during the bidding process is incorrect. In order to remedy the situation, the data included in the market basket had to be cleansed and resubmitted to the bidders, so that they could confirm whether the pricing they originally proposed match the items contained in the market basket.

Data collection is one of the most important phases of a sourcing event. It sets the foundation of the initiative, providing the overall spend figures necessary to evaluate the current state of a spend category and is used to compare the results of sourcing initiative. When collecting data that will be used during any sourcing initiative, it is important to:

  • Ensure that descriptions are as accurate as possible. General or incomplete descriptions creates assumptions, which in turn, causes discrepncies in pricing when the assumptions are invalid.
  • When applicable, provide any associated part number and/or manufacturer information. Bidders can use this information to research the product and ensure that they are quoting the item correctly.
  • The unit of measure should be clearly stated. For example, the "price per case" will be different than the "price per unit" 
  • Make sure you are knowledgeable of the items contained in the market basket. Suppliers will reach out to about with questions and it is important that you understand the functions of the products.
  • When assessing the current price during data collection, it is important to know whether tax or freight is built into the price. Often, suppliers may quote a delivered price include the cost of freight, so make certain that this information is known and communicated to Bidders during a sourcing engagement.
Gathering accurate data during the data collection phase is imperative as the data will be used during each phase of any sourcing process. Trying to conduct sourcing events with data that is incomplete increases the time and effort during a sourcing event for both the supplier and the company facilitating the event. Clean data can eliminate thes 
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Victoria Baston

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