Forget that last post. It’s been a while since we finished the manuscript. In reviewing the section I mentioned we quote your blog directly. Slipped my mind. We do credit you completely but would like to have your permission to do so. If you can send along your email address I’ll send you an excerpt so you can see how we handled it.

Sorry about that.

Phil

]]>Recently my co-author Dan Schultheis and I completed a book that is a follow up to our “Willing To Buy; A Questioning Framework for Effective Closing”. The new book, a companion piece, is called “The Willing to Buy Coach”. In the second book and purely by coincidence we talk about the same concern on CRM predictive analysis you do in this blog. We offer a solution using the overlay of our “framework”. We plan to reference your blog to illustrate the common frustration with the “three companies all predicting the same thing” conundrum. Even though we believe the similarities in our book and your blog are coincidental and represent a commonly held concern, we plan to mention you in positive terms and reference your blog. Can you please send along an email to the above address authorizing us to reference the blog to reinforce your point. In return I’ll be happy to send along a copy of the book when available. Let me know what, if anything, you need before you can authorize the reference to you, your blog and analytic thinking in this area.

Best regards,

Phil

]]>Gareth ]]>

Having said that, everyone has the same “Go” probability, so from a competitive positioning point of view, the Go probability is irrelevant.

I tend to agree with you about the assessment based, blindly, on the number of tenders. I think you may end up disqualifying a very large number of opportunities you might otherwise win. Having said that, I don’t believe it’s “Us vs the Rest” either. The assessment needs to really be driven based on actions and attitudes of the customer, commitments they have made, etc. This whole thing becomes very complicated in a bid process, so there are some other things you have to look at–I’ll discuss in my note.

I think we also have to look at why we are using probabilities in the first place. In the sales process, there are far better indicators of our competitiveness and what we need to do to maximize our ability to win. In forecasting, we have to be very careful how we apply these weighting techniques.

Again, the construction industry is a little different than many other industries, so there are some complications many sales people will never see. Thanks for the thoughtful comment. Will send you the white paper along with a further discussion in an email. Regards, Dave

]]>very interesting article, i work in the Construction industry (energy efficiency projects) where all projects are tendered by multiple companies. we originally used two probabilities a ‘Go%’ and a ‘Get%’

Go = probability project will proceed

Get = probability business will win the work

The value of the percentages are adjusted monthly by the BDM in the rolling 12 month forecast.

one item that is always debated among senior management that i have rejected is the idea that the number of tenderers reduces the win %.

Hence senior management have decided to eliminate tenders that have been distributed to more than 4 companies. They have put a 3rd matrix to capture tender numbers (ie 4 tenderers = 25%)

my personal opinion is that the number of tenderers does not matter and this matrix should be 50% (our business v’s all the others) until you are the last man standing in which case 100%

unless you begin to go deeper and assess each of the oppositions capabilities and previous relationships with the client as you suggested in your article

while the 25% may be relevant for the clients probability formula of who is likely to win the project. For our company i believe it is us v’s the rest (50/50).

what is your opinion? i understand that you touched on it briefly within your article.

Also i would be very interested in reading your white paper on this topic, where can i source the document.

Thanks

Roy

In my company’s implementation of CRM I now actually have the option of completely removing the Win Probability/Sales Stage dropdown menu and put, in its place, a Wizard akin to the ‘Odds to Win’ table. It’d give me – at the end of it – not only a SWOT analysis per opportunity but also a numeric ‘OTW’ (Odds to Win) result.

I keep talking about weighted values; Why?

Eventually a forecast commitment has to be given to executive management; and that number cannot be the sum of your entire forecast.

When looking at forecasted opportunities, I generally take a binary approach if the opportunity is scheduled for the current quarter:

I feel that, with <12 weeks for expected deal to happen, it is fair to expect sales person to be able to commit in a binary fashion.

When the timeframe is beyond the current quarter, however, the above binary approach becomes unrealistic; one has to consider a technique that will allow committing a $ value to forecast while also accounting for the likelihood of the deal materializing – the Odds to Win, if you will – in lieu of Win Probability.

I am thinking of an hybrid approach where the weighted value for such periods will be calculated as total value (un-weighted) multiplied by OTW factor will give my new 'enhanced' Un-Weighted value.

Ideal? Not sure.

More thoughts? I will welcome these 🙂

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