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Classical Approaches vs. Quantisweb
This slide compares various points between classical methods like One Factor At A Time, the more modern 6 sigma way of: "Defining, Measuring, Analyzing, Influencing, Controlling" using Design of Experiments methods and Quantisweb's Multivariate approach.

Application Examples from the Quantisweb Innovation Formulation Methodologies white paper
In this section four examples are presented, where standard methods and the novel Quantisweb methodology are used to allow for a scientific comparison.  The first example is a classical formulation case. The second is a mixture case where the formulation is provided by a mixture of two or more major compounds, within which, a mixture of two or more compound subset is obtained. The third is a case where the characteristics have very large variability. In the last case, a data set is processed with a full factorial design involving 4 parameters of two levels each, hence a total number of 16 experiments. The goal here is to show that the generated behavioral laws by Quantisweb coincide with those generated by any statistics software package in case the number of experiments becomes large enough.
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The current product development process varies from industry to industry. In many cases, it is a mix of the following methods, but mostly dependent on both the scientists, engineer and or the statistician knowledge and expertise, and gathering information.
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Competitive Analysis
A study in 2006 demonstrates that the Quantisweb tool integrates all functionalities such as: multi-criteria methods, statistical analysis, constraints in design of experiments, independent variables, dependent variables, discrete variables, continuous variables, an unlimited number of variables, and optimization algorithms with the exception of knowledge data bank.