The problem of revenue management is a common one in many capacity constrained industries. This involves business decision making to maximize one’s profitability in a market by allocating the right inventory to the right customers at the right price through the right channel. In a very dynamic marketplace where the factors change at the speed of thought, human decision makers are just too slow to process everything and make the optimum decision. The CodeGen Revenue Management Platform is designed with this complexity in mind.
It’s a collection of tools and algorithms to facilitate the business analytics and decision making. The tools model Knowledge Units, ontology bound semantic representations of data which can be universally accessed by its tools. This lets the business analyst without any technical knowledge in database programming to use the data in terms of the business semantics that he understands. The tools themselves employ statistical learning, time series modeling, and machine learning techniques to predict and represent data. In addition, the data can be optimized under various models such as quadratic optimization problems to handle cases where the number of variables can grow to 2030 thousands or even higher. Data mining is also used to suggest the user tour packages that have a higher chance of selling. Prediction engines can be plugged into strategy analysing algorithms to dry run any strategy and analyse its performance against the competing strategies in order to select the strategy that has better likelihood to provide the best profit.