Decision Models
Analytical structured models to support decision making when decisions involve high levels of complexity, or require processing very large amounts of information very rapidly. Such cases can challenge human abilities. Typical applications are in automating back room operations and automation of functions in customer facing web sites.
Statistical Analysis
Linear models, including regression, ANOVA, regression trees and factor analysis. Used to discover relationships and structure in data. Can be used for online decision making and testing
Forecasting, Time Series and Predictive Models
Applications to demand forecasting for decisions related to sales planning, capacity planning, staffing, and logistics
Data Analysis and Visualization
Typical applications are in diagnosis, problem identification, and detection of change. Visualization is useful for making it easy for people to scan large volumes of data for these purposes. Often applied to sales, cost, performance and transaction data
Optimization and Heuristics
Methods from operations research and systems analysis; commercial “engines” are available for standard models; special cases may required developing custom heuristics
Rule-Based and Neural Models
Techniques from computer science and AI, which can complement or substitute for traditional optimization and statistical methods. Can often surpass them in effectiveness