  Research on formulae production in spreadsheets has established the practice
as high risk yet unrecognised as such by industry. There are numerous software
applications that are designed to audit formulae and find errors. However these
are all post creation, designed to catch errors before the spreadsheet is
deployed. As a general conclusion from EuSpRIG 2003 conference it was decided
that the time has come to attempt novel solutions based on an understanding of
human factors. Hence in this paper we examine one such possibility namely a
novel example driven modelling approach. We discuss a control experiment that
compares example driven modelling against traditional approaches over several
progressively more difficult tests. The results are very interesting and
certainly point to the value of further investigation of the example driven
potential. Lastly we propose a method for statistically analysing the problem
of overconfidence in spreadsheet modellers.
