We are looking to work with a couple of companies who would be interested in assessing trends within their pipeline, all at no cost.  All we require is simple historic data in order to import it into SymVolli to show you the trends that your sales has gone through over the last few months.  SymVolli, our sales Performance management system, has been developed with sales performance optimisation in mind.  A trend analysis database based on the input of the sales force, without having to employ added resources to build a business intelligence database.  Please contact us (either by clicking on the link or by calling us on +44 (0)1276 683449) if you are interest in developing your pipeline datum easily.

Sales Performance Optimisation: It’s obvious isn’t it?  If you have an experience you learn from it.  If you touch an object that glows and you get burnt, hopefully the next time you see a glowing object you will think twice whether to touch it or not, and if you have to touch it you will take the necessary precautions, like wearing protective clothing, or switching the current off and let it cool down before touching it.

It’s the same in sales.  We need to understand what has happened in particular situations and if it desirable, try and repeat it or take alternative action if it is not what you expected.  Most people are intuitively aware of monitoring and assessing situations as and when they occur.  The trick is to have an early warning system that informs you that it is going to happen rather than when it is happening.  We need to establish a datum from which we can measure variations from the norm.

Let us take the example of sales conversion rates.  It seems in most cases organisations can establish what their win conversation rate for each sales person is so they have a datum to see if  it needs to be improved or if it is being maintained.  This tells us what has happened and what is happening, but it might not be good enough to show us what will happen in the future.  We need a way of instantly being able to view how forecast for each sales period, (month, quarter, etc.), and the conversion rate for each sales period.

So if we are looking at the June 2010, we need to monitor what the value of the pipeline is in April 2010, May 2010, and June 2010. If we repeat this exercise for each month we will see trends of how the pipeline behaves over a time for a given period.  In effect you are building a trend analysis of pipeline behaviour.  If we generally have a pattern over the length of the sales cycle, e.g. three months, we can then judge if we are on track to make our numbers. It does not mean we will not make target, but it will help us decide what do we have to do in marketing, sales , etc. to make up for the shortfall?

This is only the first step in the path of ‘learning from the past, improving the present, and realising the future’. The next step is to establish the validity of the pipeline and that subject is for another blog. Watch this space!