Presales includes anticipated Volume and Value in sales of software over time. We would like to choose a model of monthly periodicity beginning on 1st of January of the year; and as consisting of 52 weeks wk01...wk52 each spread from m01..m12.
Success of presales is, essentially, a function of the sales following the presales process. A more detailed look would also need to consider whether the solution put forward actually addressed the customer requirement. To go to this level will require more than a single KPI and a supporting process that allows one to look at the life cycle of a sale up to the point where it is handed over to operations.
In its simplest form the KPI's could simply measure the anticipated Volume and Value against what is actually sold. The danger of not measuring it against the actual is that inflated numbers could be proposed by the presales consultant to ensure that his KPI is reached; this would jeopordize the presales proccess and the trust relationship with the customer.
My suggestion would be to also measure the accuracy of the solution in terms of questioning the customer after implementation (in the form of a small survey maybe) about their sattisfaction with the solution.
I would consider three seperate KPI's to start with:
1. Measure anticipated Volume against actual volume. The measurement can be done using a percentage of anticipated volume over actual volume where 100% would be rewarded but any deviation upwards or downwards (i.e. 110% or 90%) is penalised. An investigation into the distribution of the historic volume information should provide one with a deviation percentage breakdown (i.e. 1 standard deviation left or right lowers the KPI score by x).
2. Measure anticipated Value against actual value (as above)
3. Measure customer satisfaction (a % calculated from the score on a survey done with customer)
KPI 1 and 2 above would, in my opinion, fall into the Internal Process perspective and 3 in the Customer perspective.
Hope this helps.
Marius van Niekerk | February 29, 2012 at 3:47 am
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