Prediction of Enterprise Purchases Using Markov Models in Procurement Analytics Applications

Abstract

Procurement is a set of activities and processes related to acquisition of goods and services through purchase orders placed by organization employees,from external contractors. Thisarticle describes practical experiments with procurement dataset of a major governmental organization in Singapore. In particular, we highlight the problems that emerge when trying to implement analytics for prediction of future purchases. The goal of such analytics is to deliver beneficial information to procurement office that plans and manages relationships with external sellers. In the article we describe the characteristics of the procurement dataset specifics and its implications on the future purchase problem that we attempt to solve using Markov chains model. Our analysis showshigh diversity of purchase descriptionsresulting in low ability to detect sequential patterns of purchasing officers. The solution presented in the article is additional dataset preprocessing involving use of hierarchical clustering. Our experiments with various similarity measures show an improvement allowing a practical deployment within our procurement analytics system prepared for the case study governmental organization.