Yeah, yeah, we all know it’s how we’ve “always” forecasted probability and weighted our pipelines. Yes, for some reason all the CRM vendors “out of the box” implementation of the pipeline ties probability of winning to where you are in the sales process. But when are we going to stop this simplistic and flatly wrong thinking about the probability of winning a deal?
You know what I’m talking about. We have a prospect who returns our call, we immediately declare a 10% probability of winning, because our systems are set up like that. We have a couple of meetings, have qualified them, determined their needs, determined who will make the decision and who our competition is. Our probability of winning skyrockets to 50%, again because that’s what our systems say. Then in the simple step of presenting our proposal, our probability of winning is suddenly 70-85%–again because the system tells us to do this.
None of these assessments and probability weightings have anything to do with whether the customer likes what we are doing, cares about our solution, or even is interested in buying from us. None of these looks at what the customer thinks of our solution relative to the competition or the other alternatives they may be considering. The customer’s point of view means little when we assess our probability of winning–at least according to our CRM systems and current methodologies. All of these measure where we are in our sales process—we’re 25% through, 50% through, 80% through, until ultimately we are 100% through the sales process—but we haven’t won the business.
We all know that assessing our probability of winning based on where we are in the sales process is flat wrong, but I’ve never seen a probability assessment based on anything other than where we are in our sales process! When are we going to stop this foolishness? When are we going to base our assessment of our likelihood of winning based on the customer’s buying process, what they think of our solution compared to the alternatives, and the sense of urgency they have about doing something at all?
What is we did something outlandish? What if we started assessing our probability of winning based on what the customer thinks? Wouldn’t we be much better served if we started thinking about things from where the customer is in their buying journey and their assessments of the alternatives they are considering? What would we learn if we started basing our assessment of the probability of winning on things like:
- The urgency the customer has to change and do something different–and the level of commitment they have to changing?
- The understanding the customer has about what they want to do and how well our solution enables them to achieve their goals?
- The customer’s assessment of what alternative best fits their needs–ours, the competitor’s, doing nothing?
- Our relationship with the customer and their confidence in doing business with us?
- The customer’s ability to get support and funding from their management.
- ….and a whole number of other factors important to the customer in their buying journey.
Imagine how assessing our probability of winning based on what the customer thinks would change our forecasts? Imagine how periodically assessing our probability throughout the buying process might actually change how we sold and interacted with the customer? Imagine how, knowing what they think, we might adjust our sales strategies and activities to improve our positioning?
Maybe then, we would have a much more accurate view of our real likelihood of winning. Maybe if we had a good understanding of how we stood, we could take actions to improve the customer’s assessment of how we can help them achieve their goals.
Understanding our probability of winning based on a customer assessment, adjusting our strategies to improve things can be very powerful.
When are we going to change decades of bad thinking about the probability assessment? When are we going to start challenging our software vendors to provide tools that enable us to correctly understand our probability of winning and take action on improving it?
(If you want, we’ve thought about this a lot. I’ve some “starter” templates on assessing the probability of winning a deal based on where the customer is in their buying journey. I’d be glad to send them to you, just ask for them–dabrock@excellenc.com)
David, I wouldn’t write this off as “bad thinking”. The pipeline way of thinking is a very simplified model of a complicated process. In most cases simple is good, adding complexity simply causes confusion. Granted there are cases where the model can be evolved and that some companies are mature enough to add the complexity.
The factors you present are clearly valuable to know, but how can you get an honest answer on the questions or where whould you dig to find an answer?
Summerised, I like your thinking, I worry about how it can be executed.
Hakan, thanks for the comment. Let me clarify a few issues. The pipeline is a critical tool to help sales people assess their business–are they pursuing a sufficient number of opportunities to achieve their goals, is there good flow through the pipeline, are they compressing the sales cycle, are they improving the win rate, are they improving deal profitability. Sales people must leverage the pipeline to help manage their personal productivity. Managers must look at it from an overall organizational performance point of view.
However, the probability assessment, based on where the deal is in the pipeline is not just bad thinking, it is tragically wrong. Let’s look at a simple example. What if both you and I are competing for a deal. If we are in the final phases, proposing and moving into closing, we would each, in pipelines where “probability” is determined based on where we are in the selling process, be stating probabilities of 70-85% (it varies based on how the pipeline system has been put together). We know from freshman statistics this cannot be possible. Between all competitors and alternatives, we cannot have a total probability greater than 100%. Yet our pipeline management systems would have us projecting the probability in a way that for at least one of us is very misleading. Let’s then say that we are selling products that have long lead times for manufacturing. Manufacturing will look at the pipeline and might be ordering inventory based on the 70-85% probability determined by the system. I’ll stop here, but you can clearly see the tragic flaw in this thinking.
Our job is to ask customers what they think of our solutions and how they fit. We have to probe, test, talk to many people, and develop our strategies based on these assessments. Properly done–against a number of customer buying factors, the sales person can come up with an assessment that is much more realistic and much more likely to represent a probability of winning. Assessing our positioning and competitiveness through the customer buying process needs to be a key element of our sales process. If sales people can’t get honest answers to these questions, then there is something wrong with what they are doing and with the relationship they are developing with their customers.
Hakan, you raise very good points. I wasn’t clear in my descriptions, but these issues are at the core of sales effectiveness. If we don’t focus on the real issues, instead leveraging a meaningless measurement based on progress through the sales cycle, then we can’t maximize performance.
Dave, I completely agree with you. Forecasting should be off relevance, not activity. Sadly, too many organizations would rather have the comfort of a number, however erroneous, than wrestle through the effort of really understanding what is happening in real conversations.
To the comment above regarding execution, I would simply offer this: since forecasting hit less than 50% accuracy last year, try this different approach (even with the possibility of salesperson “inaccuracy”). I think forecast accuracy will go up beyond 50%. On a more logical note, I would then add that if sales managers are actually attending these conversations and coaching their players, the answers will also have significantly better accuracy. With the extra benefit of a more engaged sales force – and an increase in sales.
Tim, clearly I couldn’t agree with you more. The argument is so compelling, but we continue to do the same things, with the same flawed logic.
Didn’t Einstein say, “The definition of insanity is to do the same thing over and over, hoping for a different outcome.”
As always, I enjoy reading your comments!
I thought the observation that we both cannot be right about our estimated chances at landing the same candidate correct.
But, how would you effectively crowdsource these probabilities so that the seller can broadcast them to the buyers?
Probably be an extraordinary way to prevent certain types of economic recessions.
Michael: Thanks for the intriguing comment. I may not understand you, but here are my reactions:
1. The probability of winning is an assessment the sales person comes up with, based on what the customer has said, the sales person’s assessment of whether they can have any impact on shifting positions, etc. It is not, at least in my experience, something the customer develops.
2. I can’t see any reasons from a buyer/seller point of view about why one would want to make these public or crowdsource them. If the buyer had an assessment and ranking of the alternatives they were considering, what’s in it for them to publish it? Customers want to consider a number of alternatives, and it is to there benefit that each competitor competes vigorously. Publishing this is likely to reduce competition—all but the top two are likely to abandon. From a seller point of view, I’m not sure why anyone would want to publish this or how it can be used in any meaningful way.
I may have misunderstood you, so if you can clarify your question, it looks like it could be an interesting discussion.
Here is the simple model I am thinking of.
Two sellers, S1 and S2, and Buyer, B1.
B1 has asymmetric information – he knows who is going to buy from.
S1 and S2 have estimates of B1’s information; and jointly their estimates are wrong.
In the simple game, there is no problem: one of Si is disappointed when B1 reveals the confidential information.
However, in a big economy, this game is played many times.
Too many joint errors leads to enough of the people becoming too pessimistic, cutting production based on their revised sales funnel – which now is too low.
Interesting point Michael. I think we need to separate Demand Planning from Sales Forecasting. The Sales Forecast is an important element of the demand plan, but the demand plan tends to focus on the aggregate of all deals, as well as a number of other factors (historical run rates, buying behavior, economic indicators, etc.)
Having said that, increasing Sales Forecast accuracy is important–not just for it’s contribution to the demand plan, but to look at how effectively we are engaging and helping the customer in their buying process.
There are a number of ways we can reduce the gap on perception between “S” and “B.” While the buyer may hold some info back, we can understand a number of things to assess the probability the customer will choose us. The problem with most probabilistic models is they have nothing to do with what the customer thinks of us, or their buying need, urgency process. Most simply measure where we are in the sales process.
Thanks for provoking the discussion.
Dave writes: “The problem with most probabilistic models is they have nothing to do with what the customer thinks of us, or their buying need, urgency process. Most simply measure where we are in the sales process.”
Yes, I can accept this.
But, shouldn’t a company try to tweak their CRM rules so that efficient odds are produced: that is, if the CRM says the deal is 9-1 against, then 9 times out of ten we don’t get the deal?
Shouldn’t historical records at least be kept to see how good our sales forecasts were?
Michael, thanks for continuing the discussion. It’s very easy to develop a probability assessment based on the customer’s view and their attittudes to you and the alternatives. This can be embedded in CRM systems easily. However, every CRM system-out of the box- perpetuates the fallacy of measuring the probability based on where the sales person is in the sales process. Most organizations don’t change this. It’s time for the CRM vendors to wake up to the fallacy they perpetuate.
Leveraging sales person past performance is also very powerful. Some of the vendors are incorporating this into their analytics. It’s a very powerful capability.
David,
Yes, I agree with both these statements:
1. Every CRM system-out of the box- perpetuates the fallacy of measuring the probability based on where the sales person is in the sales process.
2. It’s very easy to develop a probability assessment based on the customer’s view and their attittudes to you and the alternatives. (except for the “easy” bit)
I have just been speaking with a major brand, heavy on analytics, measuring and reporting. Talking about a sales/negotiation program.
But, they don’t have a CRM platform that the sales team is all on. Pretty hard to measure the value of training in that case.
Michael, I’ve responded in greater detail privately. Actually, it is not as great a challenge as one might think. We’ve had great experience in putting customer focused probability estimates. Additionally, while a CRM system is very helpful for putting in place metrics you refer to, it is possible to do the same without CRM.
Guys, this is a wonderful discussion. If I may, I’d like to throw in an extra question. Could we move away from activity-based data completely?
As I mentioned earlier, my personal position is to use relevance as the qualifier. Activity, even historical performance, just doesn’t seem to work for sales forecasting due to a wide variety of variables (market dynamics, product maturity, evolving customer needs, etc.). I struggle with using it for anything but demand planning. But am I throwing the baby out with the bath water?
Great point Tim I actually continued the discussion and relationship with demand planning in a post I made today. I think too many people confuse what the Sales Forecast is and how it should be used. I attempt to address some of your points in todays post. (Great minds thinking alike????)