Forecasting Analytics: The Sales Cycle Length

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Occasionally, I go to the LinkedIn sales forums to see what’s on the minds of salespeople and the problems they are struggling with. I get frustrated though, because as the owner of a commercial sales application development business, I am frequently not allowed to post my two cents worth because it is “self-promotion.”

Recently, a sales manager was asking, “What is the best analytic I can use to see if my salespeople have good pipelines and my forecasting has a chance of being accurate.”

I know my answer to this probably won’t come up in the discussion thread. The one piece of data that drives information and knowledge about strategy in the sale and creates the best chance of accurate projections is . . . the length of the sales cycle. Let’s see why.

The sales cycle is a reaction to the customer’s buying cycle because the customer almost always starts the cycle and then the seller discovers it and responds. In chicken and egg language, that one is unarguable (although I’ve had a few heated discussions about it). The corollary is that the sales cycle follows the evolution of the buying cycle with reciprocal tactics to react to the tactics that the buyer is using. This one is simple, but at the same time it is tough for some salespeople to get.

The buying cycle has three phases, so the sales cycle must have three corresponding phases. We’ve talked a lot about this in other HUB posts, but the essence is that the salesperson must get his or her sales strategy in sync with the buyer’s process, i.e. you should only be closing when the buyer is negotiating. If the salesperson is not doing this, the sale will be difficult in any number of different ways.

Here is the point I’m making: there is no way a salesperson can properly plan the sale if they are not conscious of where they are in the sales cycle and the appropriate skills and tactics you must be applying. This problem gets worse if the salesperson is charged with handling multiple products with widely varying sales cycles because with one product you might be in the early Probe Phase for two weeks and for another, six months. Skills application is not time dependent, it is sales cycle phase dependent. And this gets even more difficult if the number of open opportunities is high. This is a classic case of where a computer monitored list of the opportunities (we call it the portfolio) can really help.

Computational selling uses the computer to measure and monitor time in the sales cycle. Throw a gazillion opportunities at a computer and it will do this and won’t even blink. This work is an enormous overhead for the average salesperson if they are trying to “wing it” with their opportunity portfolio. It helps to get that portfolio into a CRM or Sales Automation system, but, and it’s a big BUT, if the computer doesn’t know when the sales cycle started and when it’s going to finish, it can’t seriously help matters.

So, the most important analytic for your sales team is the sales cycle. When did it start. When will it end. Where am I every day.

I guess that this is really a bit long for the LinkedIn moderator to have allowed. I’ll go away and see if I can shorten it up a bit. Might write a book about it, actually. 😉

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