With the popularity of advanced data analytics, such as machine learning (ML) and artificial intelligence (AI), decision support systems (DSS) are also receiving broader attention. Originally rooted in organizational decision theory at Carnegie Mellon University, DSS have rapidly co-evolved with computational capabilities to help decision-makers utilize databases and quantitative methods. These methods include traditional statistics and operations research as well as genetic algorithms, neural networks and agent-based simulation. An early DSS example that changed an entire industry is airline yield management systems.

The screenshot shows the top level, interactive graphical user interface of a DSS for Auto Interior & UX. It has been built to help decision-makers spend the next $1 to maximize improvement of in-car customer satisfaction – as measured in J.D. Power Initial Quality Studies (IQS). It has been constructed in three layers: presentation layer, analytics engines and data foundation.