analycess procurement | Method
Taste the power of our algorithm
At the core of analycess lies a regression mechanism that reflects state-of-the-art mathematical research. It will find the statistically best approximation function for the given prices, based on the observed product characteristics. Especially in the case of product characteristics that are correlated among each other (e.g. size and weight), simpler regression mechanisms often are not able to find a statistically valid approximation function. Statistics like Adjusted R2 are mathematical quality criteria against which the performance of analycess can be measured.
The concrete result of the application of analycess to a range of products in industrial procurement is a linear approximation formula that describes the price sufficiently. The deeper added value of analycess for the strategic buyer is to appreciate the real impact of various product characteristics on the price.