What is the reason for the significant difference in bid win rates among teams using bidding programs? Surprisingly, even the same company's chances of winning a bid vary by more than tenfold depending on the announcement.
In an electronic bidding system, the number of competitors is not merely background information; it changes your entire bidding strategy. To use a bidding program effectively, you should not view it simply as a tool that recommends prices. The key is to analyze the competition rate and formulate a strategy accordingly.
A bidding program that formulates realistic bidding strategies through competition analysis
Bidding programs are broadly divided into three types. Automated bidding programIt automates the entire process from login to bidding, and, Bid Amount Calculation ProgramIt recommends an appropriate bid price through example ranges and competitor analysis. Bid Analysis ProgramIt evaluates performance after the fact.
Among these, the key to analyzing the competition rate lies in the bid price calculation type. This is precisely where most companies overlook. This is because the probability of winning a bid can vary completely depending on the number of competitors, even within the same price range.
| Program Type | Key Features | use |
|---|---|---|
| Automated bidding | Login, Authentication, and Bidding Automation | Streamlining the input process |
| Calculation of bid amount | Example Scope · Competitor Analysis | Fair Price Recommendation & Pricing Strategy |
| Bid Analysis | Performance evaluation and data analysis | Strategy Revision and Performance Management |
Why Counting Only Winning Bids Makes You Miss Out on Strategy
There is a common mistake made by heads of bidding departments. They compare only the pure number of successful bids, saying things like, “We had 15 successful bids last month, and 12 this month.” However, this is a big misconception.
Compare the probability of winning a bid in a tender with 10 competitors to the probability in a tender with 50 competitors. In actual analysis, the expected value of a company winning a bid is 0.1 in a tender with 10 companies, compared to 0.02 in a tender with 50 companies. This means that even with the same bid price, the difficulty of competition differs by more than five times.
The number of successful bids that does not reflect the number of competitors can be a misleading indicator of performance.
Therefore, “how many multiple estimates have been secured” becomes a much more objective evaluation criterion. You must look at how many times the average has been secured to determine the actual effectiveness of the strategy.
The relationship between multiple estimate structure and the probability of winning the bid
In the domestic electronic bidding system, 15 preliminary prices are generated for each announcement. Four of these are selected by lottery, and the number of possible combinations alone amounts to 1,365.
The fact that the program secures a sufficient number of multiple estimates means that it covers as many cases as possible out of these 1,365 combinations. This increases the probability of winning the bid regardless of which four are drawn.
Looking at the actual data, the average number of multiple estimates that can be secured is approximately 2,191. Teams whose strategies worked well actually secured around 2,216, maintaining a level about 1.01 times the average. While this difference may seem small, it appears as a much larger gap in the bidding results.
Historical data required for accurate analysis
The accuracy of a bidding program depends heavily on the amount of data used. This is especially true when predicting the success rate.
It is difficult to expect high reliability with a small sample size. This is why maintaining bidding data for the past two years should be considered a standard. Sufficient historical records are essential to reflect seasonality, construction types, market changes, and more.
The more past bidding records a company has accumulated, the more accurate the analysis of the program's competition rate becomes. Therefore, to reduce forecasting errors, you must first organize your bidding data and update it regularly.
Try actually formulating a bidding strategy
Once you have received the competition analysis results, you now formulate a strategy. The first is Identify stable winning bid zonesWe focus on announcements with few competitors, low minimum price standards, and types where it is easy to secure multiple estimated prices.
The second one is Risk announcement judgmentYou should not blindly invest in bids with many competitors or large companies applying, no matter how low the probability of winning is. You must calculate the ROI based on the probability of winning relative to the cost of securing multiple estimated prices.
The third one is Portfolio BalanceIf you only target stable job postings, the number of cases will not increase, and if you only chase difficult ones, losses will accumulate. It is realistic to create a portfolio by appropriately mixing the two types.
Wrap-up: Making decisions with numbers
The value of a bidding program lies in recommending good bid prices, rather than, Changing decision-making based on the objective indicator of competition rate Yes, if performance is evaluated based on the status of securing multiple estimated prices and competitor analysis rather than the number of successful bids, the team's bidding strategy becomes much more realistic.
Starting now, try analyzing the competition rates for the job postings your team has entered. You will see patterns in why certain bids were rejected while others were raised when the same bid was submitted. That is the most reliable strategy for your next bid.