Using Data for Effective Tender Preparation
A data-driven approach requires an understanding of what metrics are important when measuring a company’s tendering performance. In this post, we discuss these key metrics, which can be obtained by analysing tender data. If you are not familiar with the data-driven approach to tendering, do check out the previous post (Part 1 of the Data-Driven Approach to Tendering), in which we introduced the data-driven approach to tendering and how we could infuse insights from data analytics into the tendering workflow.
The Basic Metrics of Company Tendering Performance
“What gets measured, gets managed” – only by understanding the current state, can we seek to improve it. It is important for a company to know how it is performing before trying to figure out what and how to improve. We therefore start by focussing our attention at the company level. By exploiting data, we are able to extract some basic tendering performance metrics that allow us to better understand a company’s tendering performance and to enhance its competitiveness. Further, benchmarking these metrics allows us to see how a company is performing compared to its peers within the industry. The basic metrics include:
Tendering Success Rate
The ratio of winning bids to total bids tells us how successful the company generally is in its bids.
Total Awarded Value
The total amount of value awarded for all winning bids. This summarises the market value captured by the company.
Average value per winning bid
The total awarded value divided by total wins. This metric gives a sense of the potential value of each tender to the company. In relation to competitors, it reveals a company’s price competitiveness.
Average value per bid
The total awarded value divided by total bids. This metric gives a sense of the actual value of each bid made by the company. There are real costs associated with each bid submission and companies should be sure that their value per bid exceeds their tendering costs.
Putting Them Together
By calculating these metrics for all companies in each industry, we are able to benchmark each company against its peers and get a quick snap shot of its current performance. This allows us to begin identifying potential areas for improvement.
We include some charts below that illustrate the means of the 4 basic metrics in 3 industries.
Mean Success Rate by Industry
The success rate varies quite a bit from industry to industry, and it certainly varies a lot between companies in each industry. What is the average success rate of your industry? More importantly, what is your company’s success rate and how does it stand in relation to your competition? Is your current success rate and your relative position within the industry where you would like it to be?
Mean Total Awarded Value by Industry
It should come as no surprise that there is great variance between industries for the mean total awarded value. The products and services in some industries would naturally be far dearer than others. For example, the value of a Building Construction tender would be much larger than a tender for Office Furniture. Is your company’s Total Awarded Value meeting its targets?
Average Value per Win and Average Value per Bid
The Average Value per Win and Average Value per Bid are 2 of the most important metrics to track for a company (in fact, the Success Rate and Total Awarded Value metrics factor into these 2 metrics as well). Together, they give a company insight into the commercial viability of its tendering efforts. Does each win add sufficient value to the company? Is the Average Value per Win moving in the correct direction with each Win? Does it cost more to bid than the current Average Value per Bid?
What else can we do with this data?
Our proprietary profiling engine analyses data at both the Company and Industry levels. Each profiler derives its own set of metrics, which we summarise in the illustrations below:
These metrics offer a detailed understanding of a company’s tendering performance, as well as of its competitive landscape, the context, in which that performance was achieved.
At this point, you might ask if it is necessary to go into such details. After all, many factors influence the outcome of tenders and some of these factors may never be revealed through analysis of tender data. This is certainly true, and we are under no illusions that the insights gleaned from such analysis are a cure-all for unsuccessful tendering.
However, we believe that exploiting data to better understand your company and its operating environment can better prepare you for success. The data-driven approach to tendering should therefore be regarded more as a discipline, rather than a formula for quick and easy wins.
As we wrap up our 2 parts series on the Data-Driven Approach to Tendering, we invite you to share your thoughts in the comments below. Have you been exploiting data as part of your tendering workflow? If not, have you been thinking about how to use data or how data could improve your odds of success in tendering? Are there any data related challenges you would like to share?