Recent posts have focused on setting up a bid win-loss review process, conducting bid win-loss interviews and reporting on bid win-loss reviews.
Companies conducting large numbers of reviews per year should also consider using win-loss analyses to aggregate review data to see performance patterns and trends. This post will show you how to get started.
- Brainstorm all the parameters against which you might want to analyze results. Examples of common header items include:
- Bid review tracking number (if used)
- Bid/No bid decision score (if known)
- Result (win or loss)
- Incumbent (use a code for each key competitor)
- Product category
- Sales territory
- Client type (e.g. by industrial category)
- Pre-RFP sales contact
- Degree to which you were able to shape the RFP
- Prospect is/is not a current client
NOTE: The headers you choose will determine the ways you can sort bid results to see what’s happening. Selecting header items is an important step with long-term consequences. While you can always add new headers later, you will only be able to use those new items to analyze future bids—unless you go back and reconstruct historical header data.
Now, add placeholders for the header items to your review format, so you collect all header items each time you perform a review. Assign a code to each header item, using letters or numbers.
Add quantitative questions to each section
For each of the interview areas (refer to our earlier post on win-loss reviews), add a question that can be scored numerically. For example, to the questions on responsiveness, add the following (or a similar) question:
- “Overall, on a scale of 1 to 5, how well did XYZ Co. demonstrate it understood your needs?”
You can also ask:
- IF A WIN: “Again on a scale of 1 to 5, how would you rank the next closest bidder on responsiveness?”
- IF A LOSS: “Again on a scale of 1 to 5, how would you rank the winning bidder on responsiveness?”
To obtain high quality responses, ask your quantitative questions at the end of each section, rather than grouping them as a separate set of questions.
Assemble the review data and analyze
Input the header information and quantitative responses to a database or Excel spreadsheet. Over time you will be able to answer questions such as:
- How does pre-RFP sales contact affect our win rate?
- What is our responsiveness score on winning bids vs. losses?
- Does our loss rate as incumbent vary by territory?
Of course, the headers you assign and the questions you ask will depend on your specific business.
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