Are you tracking win rates, team performance and analysing the market?
Bid-related data is increasingly being used by companies to improve and enhance all bidding and tender related activities. We discuss why bid data is being increasingly being captured and analysed, and how it can help you achieve competitive advantage.
Bidding strategy is one of the important strategies in the early stages of a project’s lifecycle to shape a winning bid, and ultimately project success. The quality of decision making at the pre-contracts stage can enable a business to adapt quicker than competitors to the opportunities and threats presented in the market, and it can also unlock potential to develop other intangible competitive differentiators in the business identified through team dynamics, service methodologies, and technical expertise. Now, more than ever before, data is helping to round out the decision making process – making it less about gut feel, and more about getting the answers needed to win the work that the company wants.
Why is tracking bid data important?
Gone are the days of scatter gun bidding. This is expensive and draining on company resources. Knowing where to focus time and energy means the company can put their best teams on the bids they want to win.
By combining financial and non-financial data in bid analysis, we can provide deeper insights into relational factors behind bid success and failure. Having this data paints a more complete picture, allowing the company to create a bidding profile to learn more about bid performance by team, by business line and by customer.
By adding external market data, companies can enrich their understanding by benchmarking their performance against competitors. Additionally, with more meaningful insights companies can identify patterns and outliers, helping them quickly adapt to market forces, and arming them with intelligence that can improve their competitive strategies and win rate.
What bid data should bidders be tracking?
Getting started with analytics is about exploring the available data to generate new knowledge and insights. For bidding companies starting on a bid analytics journey, a good starting point is to consider defining some questions and then identifying the data that you know is relevant to answering them.
- Capturing number of incoming tender opportunities and creating a digital bid register (or bid board).
- How many bids progress from open market to qualification, to bid/no bid, to number submitted, and to won / loss?
- Bids submitted and won by value, and by volume
- Win/loss ratio (won bids compared to lost bids)
- Capture ratio (won bids divided by qualified submitted bids)
- Win ratio for customers new and incumbent
- Diversity of customers
- % bids going to core customers (total bids from core customers / total number of submitted bids)
- Opportunities month on month (increasing or declining? Are there seasonal trends?)
- Mark up (or profit margin) % influence on win ratio
- % bids across business lines.
Tracking tender and contract market data
In addition to tracking your previously awarded bid results, open market data published by public sector businesses (and aggregated by Bidhive) now makes it more accessible to capture topline tender and contract data to supplement the bid data you are already capturing within your business. Combined, this data can be used to deliver you competitive advantage because it gives you access to:
- Competitor price points
- Market intelligence such as competitor contract durations, including renewal options
- Previously awarded bid results
- Upcoming planned public sector opportunities.
A key advantage of including market data in your bid analysis is the ability to use it for benchmarking against competitors; quote with more certainty; and optimally price your bids so that you neither price too high and lose the bid nor price too low to lose on margin (leaving ”money on the table”).
Bid teams bring incredible value to organisations and quantitative analysis allows them to put hard numbers to their successes and opportunities. Adding qualitative analysis to understand reasons for won/loss outcomes can help the business to uncover opportunities for additional training, resources or alternative teaming which can influence an outcome.
As with anything strategic, it will be the people, not the technology, who make sense of the data and give it meaning. When embarking on a data analytics initiative, it is important to remember that business intelligence is the work of the people who apply it. The data warehouse is simply the enabler to support you in the process.
updated 21 July 2022. Originally published 7 August 2021.