The former Prime Minister, Benjamin Disraeli once famously said, “There are three types of lies; lies, damned lies, and statistics” and this is still true today.
When we are training or consulting, we will ask people if they know the win rate for their company. Occasionally, we receive a very specific and informed answer but at other times we are given answers that are, at best, guesswork.
In any event, it is the follow-up questions about win rates (for example, do they factor in fiscal variables, or unknown results, or quality of pre-bid relationship) where the wheels typically come right off. The killer question is usually: ‘How do you use your win rate data to drive change?’ and rarely, if ever, does the answer survive proper scrutiny.
Seemingly, many organisations collate win rate data to complete a periodic key performance indicator (KPI) pack with no serious analysis taking place or an action(s) plan being determined and implemented. It does not matter how carefully curated the data is; it is ultimately meaningless if you are not doing anything with it.
What is the data behind the top-line rates?
Firstly, let’s examine what we collect as win rate data and how we interpret it.
We will assume a company has submitted 100 bids in 2019. Of these bids, they have won 20, lost 50, and have no definitive answer for the remaining 30. This means there are currently two possible win rates: 20%, which is the number of wins v. total bids submitted, or 29% (rounded up) when wins v. known results (70) is used as the comparative factors.
Which method should your company use?
The most obvious metric to use is the latter (because you can only work with definitive outcomes), although the former will give you a better understanding of the return on the investment you have made in producing the bids (assuming you know your total bid costs).
Let’s now consider a different way of calculating win rates; based on the fiscal spread (and we will keep this simple). For this exercise, we will assume that a company has written ten bids, nine of which have a value of, say, c.£100K and a tenth which has a value of £500K (a total revenue opportunity of £1.4m if they won all the bids). They know the results of all these bids and won five, so, on the face of it, they have a 50% win rate. But if the five they won were all £100K bids and they missed the £500K bid, then, based on revenue won v. revenue opportunity, the win rate is 36%.
So then, in the two above scenarios, we are faced with statistical analyses that produce different results depending upon how you apply your form of measure. Of course, it does not stop there; there are so many ways to slice and dice win rates that it can almost lead to ‘paralysis through analysis’.
Once you have your top-line rate, you may then want to consider, as a minimum, your win rates for:
However you determine and analyse the data, it is ultimately a pointless exercise unless you are going to do something with it.
In other words, you are going to use it to initiate a process or behavioural change, identify peaks of excellence upon which you can build (or deficiencies that require corrective action), or to recognise training needs.
Three scenarios where win rates can be used to identify the need for change
1. Win rates v. Bid/No Bid robustness
One of the best ways to increase win rates (however you measure them) is to stop writing bids you are probably going to lose. You can map your win rates back onto your Bid/No Bid records to see how closely your initial governance process predicted the actual outcomes. Win rate analysis and Bid/No Bid are at opposite ends of the bid process but, in a circular model, they meet on the other side. One informs the other.
If during your win rate analysis, you compare individual bid outcomes with predictions made during the initial Bid/No Bid evaluation, and the result was not what you anticipated, then it may be that you can identify deficiencies in your opportunity evaluation methodology.
Your win rates are a mechanism for validating the integrity of your Bid/No Bid model.
2. Win rates used to identify areas of excellence
If you track win rates for individual bid managers, writers, and/or bid teams, you easily see where the 'pockets of excellence' are. For example, you might have a bid manager who maintains a consistently higher win rate when compared to their colleagues.
In this instance, you can investigate why this might be (skill levels, previous training, approach to bid strategy, excellent collaboration with Senior Management Executives, etc.), identify the best practice, and share it with others.
Our experience is that the larger and more siloed the organisation, the more likely it is that variations in skills levels and approach will occur; especially if there is no real central quality governance or exemplars of bid methodology. Comparing win rates across people or divisions can illuminate the teams that need to level up.
3. Win rates used to build ‘ideal customer’ profiles
Win rates will gradually enable you to build up a picture of your most likely winning scenario against specific customer profiles. For example, you may find that your win rates are optimised when you are dealing with a customer of a certain size range, in a particular geographic location, with a defined product solution, and with the bid written by a specific project team.
Understanding how customer profiling can be driven by analysis of win rates promotes a better understanding of your sales pipeline and your ideal customer. It may help you to redirect your business development focus.
A final thought
We encourage our clients to think about their loss rates. A 20% win rate is also an 80% loss rate. When you consider this as a factor of the resources you have invested in bidding, it can be alarming. Where else in your business would you tolerate this lack of return on investment?
How much does it cost you to produce a bid? Let’s assume that, on average, a bid costs you £20K (a hugely conservative figure for many companies) to produce. If we further assume you have written ten bids, then you have invested £200K in your bidding activities.
If you have a 20% win rate, then you have effectively spent £200K to capture two contracts. The profit in those two contracts must be enough to cover the cost of bidding in the first place. Careful analysis of win rates and the things we have discussed here could be a way of improving that equation.
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