The pricing variance analysis aims to provide insight into price increase and price decrease patterns for the different product categories, brands and suppliers. If several different product items are purchased under the same category, the algorithm recognizes them as sub-items.
The product classification algorithm aims to automatically classify the purchased products into the different product families, categories and item groups. This is the foundation for a good spend analysis. This algorithm is based on Machine Learning.
The spend consolodation algorithm aims to reduce the number of suppliers (supplier consolidation). in view of a number of specific constraints. The algorithm indicates how the spend can be optimized over the different and reduced number of suppliers..
ABC analysis is a method in which inventory is divided into three categories, i.e. A, B, and C in descending value. The items in the A category have the highest value, B category items are of lower value than A, and C category items have the lowest value. In stead of calculating the ABC categorys on spend alone, the ABC categories are based on more data attributes like: delivery leadtimes, criticality of products etc. This results in a improved ABC categorization.
The duplicate payment of invoices algorithm aims to find the double paid invoices. The matching takes place, among other things, with the help of fuzzy matching. In this way there is the greatest chance that the invoice paid twice will be found. In order to be able to check the results quickly, the matches found are clustered.
The Late payment of invoices analysis aims to find the most important exceedances and the influence factors that are important. The analysis provides the insights in the form of a readable text. You can also zoom in on case level and the process flow to view the details. A Process Mining algorithm is used for visualizing the process flow.