Decision-Guidance Systems
Why do we need them?
An
increasing number of decision-guidance systems need to guide human decision
makers to move a complex process toward desirable outcomes. Examples include
finding the best course of action in emergency, deciding on business
transactions within a supply chain, and developing public policies guided by
most positive outcomes.
The
abundance of information is a blessing and a curse at the same time for a
modern decision maker. Contemporary information systems are relentlessly
efficient to collect and process huge amounts of factual data, but they are
weak in terms of insights and wisdom. While human decision makers have plenty
of useful intuitions, insights, judgments, and preferences, they can be quickly
overwhelmed by the amount of dynamically available data. Typical operations
research approach involves mathematical optimization to find the best course of
action, but this requires a formally defined model, which defines the search
space and the objective. Such a formal model is often not available a priori,
but rather need to be extracted from historical data,
and iterative dialog with human decision makers. Approaches
to move information systems toward intelligence comparable to human's have only
seen small progress, while humans are notoriously hard to change and upgrade!
What do they do?
Decision-guidance
systems support an iterative process of giving actionable recommendations to
and extracting feedbacks from a human decision-maker, with the goal of arriving
at the best possible course of action. This needs to be done (1) in the
presence of large amounts of dynamically collected data, (2) while learning
objectives or decision preferences from historical data and decision maker's
responses, and (3) under diverse constraints that capture complex real-world
processes, composite services, and supply and demand.
Research focus
The
technical tools involve (1) mathematical and constraint programming, (2)
database management, and (3) statistical learning and data mining to extract
user preferences and objectives. Research
on Decision-guidance focuses on the development of models, languages, and, most
importantly, algorithms toward the first Decision-Guidance Management System
(DGMS), which is productivity tool for fast development of decision-guidance
applications. This is analogous to Database Management Systems (DBMS) serving
as a productivity tool for fast development of database applications.