January 22 2015
by Todd Hixon

Cut The Fluff From The Sales Pipeline

[This post first appeared at on December 16, 2013.]

Or: The Quantum Theory Of Business

Gazing into the ever-murky crystal ball of the sales pipeline.

Gazing into the ever-murky crystal ball of the sales pipeline.

I’ve listened to more sales pipeline reviews than I can count, and I expect you have too. Typically, there is an array of opportunities, some sounding very attractive, and discussion of how far each is from a close. The sales guys and gals lead the discussion. They are naturally bullish about the key proposals: “this one is 90% sold”. And, they have a long list of early-stage prospects, each with some probability attached, adding up to a comforting backlog for the next period.

The big problem is: how do you filter this happy talk and come up with a number that you can bet on? Over the years I’ve developed two rules that help me get to a realistic assessment.

1. No deal is more than 2/3 likely until it is fully closed. There are always substantive approval steps at the very end of the decision process: people who have to say yes, who have not been heard from yet, who may have agendas that are not yet visible. For example, an investment banker friend was closing a deal to invest $50m in a private equity fund. The rails were supposedly greased, but an investor board member discovered that the fund had invested in a small arms manufacturer, raising responsible investing concerns, and the board killed the deal at the 11th hour.

Black swan events happen more often than most of us expect. I had two portfolio companies teed up for transactions right after Labor Day …  of 2001. A big black swan came out of the sky (the September 11th attack) and both counter-parties pulled back. One company went out of business. The other got emergency financing from existing investors and exited two years later, for half the price that was negotiated before 9/11.

And sometimes the deal is not really done. We had a deal to sell a portfolio company at a decent price that had already been traded down, fully negotiated, and papered. Guess what? Ten days before close the buyer decided to trade down again. The deal fell apart, and we took the company off the market and sold it two years later.

My point is: 80%-90% sold just does not exist in nature. Until the deal is irrevocably closed, you are no more than 2/3 of the way there.
2. Probability of close below ~1/3 is effectively zero. You’ve probably seen sales pipelines that have dozens of customers in the early stages, each with a small probability attached. In my experience, most of these customers either disappear in successive reports or hang in limbo at the early stage; very few advance. But a small probability multiplied by many prospects of this type adds up to a lot of backlog [and makes the math quick and easy]. This is total fluff.

There are two problems here. 1) We don’t actually know much about these customers yet. So the estimates of both potential deal value and probability are inherently bad. 2) Humans are poorly equipped to comprehend small probabilities; they naturally judge them to be bigger than they. This is why lotteries sell so well. We focus on the prize ($100 million in Megabucks this weekend!!) and not the 0.00000001% chance of winning, and cheerfully stump up $5 for a ticket that has an expected value of $0.50.

So, my rule is: everything below about 33% probability should be assigned zero probability. That way you avoid relying on backlog that you really don’t understand.

There’s a charming parallel to quantum physics here. [Those with no interest in physics or history of science might skip this paragraph.] Late 19th century physicists were challenged to explain why the light emitted by hot objects looks the way it does: an object at a temperature of ~4,500 °F emits about the same amount of power in red light as it does in blue light, and the eye adds that up and sees white. Then-existing physical laws predicted that the light on the blue side should be more powerful, because, all else equal, shorter wavelengths (blue is shorter) carry more power. So the light should have a blue tint, but it doesn’t. This conundrum led Max Planck to theorize that only certain frequencies of light are emitted, and the others are “not allowed”.  Further, the allowed frequencies are more closely spaced on the red side than the blue side, and this offsets the higher power per frequency on the blue side, so the overall power distribution is symmetrical, and light looks white, as we observe. This was the beginning of quantum theory: light is not emitted smoothly at all frequencies; rather it is emitted in chunks (quanta) at a subset of “allowed” frequencies. This seems odd and non-intuitive, as does most of quantum mechanics, but it has remarkable power to explain what we observe in nature. Deal probabilities are the same way: they are meaningful only in the 1/3-2/3 range; the other probabilities are “not allowed”.

The quantum mechanics analogy is fun, however, there is a very practical point here. My rule that the very low and very high probabilities are “not allowed” forces focus on two things: closing the deals in the 1/3-2/3 probability range, and qualifying the deals at the start of the pipeline well enough that they cross the 1/3 likely threshold and have backlog value. This is exactly where focus pays off.


Image credit: violetkaipa / 123RF Stock Photo



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