Predictive Analytics

Overview:

The Analytics Technlogies most common to business are descriptive, diagnostic, predictive and prescriptive. Predictive Analytics is the stage where you ask the question “What will happen?” This information is typically needed in order to forecast demand, market behavior and other factors that influence decisions that need to be made in advance as in how much supply to order, inventory to keep and what price to charge. Until recently, the method most used for this was linear regression – that is matching the trend lines based on historical information. In the last few years, with the introduction of Machine Learning techniques such as regression trees, binary…you can look at product and competitive characteristics and therefore make more sophisticated and accurate predictions.

Main Capabilities:

  • You can upload data with any number of fields
  • Select the dependent and independent variables
  • Select the Mode and Type of analysis

Opalytics Technology Benefits:

  • Easy to use interface for Machine Learning – no coding required
  • Run various options and compare
  • Configure to suit your problem
  • Solve for large sized data sets
  • Connect to other solvers for prescriptive analytics

Example:  Price Optimization

Challenge: Solve complex price and promotion optimization challenges
Solution: Deploy machine learning to define the pricing curves and optimization to take into account business rules such as promotion budgets, timing constraints and cannibalization

Deploy: Deploy both  machine learning and custom optimization and work closely with business users.