Decision Support System (DSS)

A Decision Support System (DSS) is a computer-based information system that supports a decision support task.

• Context:
  • It can be supported by an Analysis System, such as a business intelligence system.
  • It can range from being a Real-Time Decision Support System, to being a Tactical Decision Support System to being a Strategic Decision Support System.
  • …
• Example(s):
  • a Clinical Decision Support System.
  • a Customer Relationship Management System.
  • an Enterprise Resource Planning System.
  • an Executive Information System.
  • …
• Counter-Example(s):
  • a Logging System.
  • a Queuing System.
• See: Decision Act, Problem-Solving System.

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References

2023a

• (Wikipedia, 2023) ⇒ https://en.wikipedia.org/wiki/Decision_support_system Retrieved:2023-2-5.
  • A decision support system (DSS) is an information system that supports business or organizational decision-making activities. DSSs serve the management, operations and planning levels of an organization (usually mid and higher management) and help people make decisions about problems that may be rapidly changing and not easily specified in advance—i.e. unstructured and semi-structured decision problems. Decision support systems can be either fully computerized or human-powered, or a combination of both.

    While academics have perceived DSS as a tool to support decision making processes, DSS users see DSS as a tool to facilitate organizational processes. Some authors have extended the definition of DSS to include any system that might support decision making and some DSS include a decision-making software component; Sprague (1980) defines a properly termed DSS as follows:

    1. DSS tends to be aimed at the less well structured, underspecified problem that upper level managers typically face;
    2. DSS attempts to combine the use of models or analytic techniques with traditional data access and retrieval functions;
    3. DSS specifically focuses on features which make them easy to use by non-computer-proficient people in an interactive mode; and
    4. DSS emphasizes flexibility and adaptability to accommodate changes in the environment and the decision making approach of the user.
  • DSSs include knowledge-based systems. A properly designed DSS is an interactive software-based system intended to help decision makers compile useful information from a combination of raw data, documents, and personal knowledge, or business models to identify and solve problems and make decisions.

    Typical information that a decision support application might gather and present includes:

    • inventories of information assets (including legacy and relational data sources, cubes, data warehouses, and data marts),
    • comparative sales figures between one period and the next,
    • projected revenue figures based on product sales assumptions.

2023b

• (Wikipedia, 2023) ⇒ https://en.wikipedia.org/wiki/Decision_support_system#Taxonomies Retrieved:2023-2-5.
  • Using the relationship with the user as the criterion, Haettenschwiler differentiates passive, active, and cooperative DSS. A passive DSS is a system that aids the process of decision making, but that cannot bring out explicit decision suggestions or solutions. An active DSS can bring out such decision suggestions or solutions. A cooperative DSS allows for an iterative process between human and system towards the achievement of a consolidated solution: the decision maker (or its advisor) can modify, complete, or refine the decision suggestions provided by the system, before sending them back to the system for validation, and likewise the system again improves, completes, and refines the suggestions of the decision maker and sends them back to them for validation.

    Another taxonomy for DSS, according to the mode of assistance, has been created by D. Power: he differentiates communication-driven DSS, data-driven DSS, document-driven DSS, knowledge-driven DSS, and model-driven DSS. *A communication-driven DSS enables cooperation, supporting more than one person working on a shared task; examples include integrated tools like Google Docs or Microsoft SharePoint Workspace. *A data-driven DSS (or data-oriented DSS) emphasizes access to and manipulation of a time series of internal company data and, sometimes, external data. *A document-driven DSS manages, retrieves, and manipulates unstructured information in a variety of electronic formats. *A knowledge-driven DSS provides specialized problem-solving expertise stored as facts, rules, procedures or in similar structures like interactive decision trees and flowcharts.

    • A model-driven DSS emphasizes access to and manipulation of a statistical, financial, optimization, or simulation model. Model-driven DSS use data and parameters provided by users to assist decision makers in analyzing a situation; they are not necessarily data-intensive. Dicodess is an example of an open-source model-driven DSS generator. Using scope as the criterion, Power differentiates enterprise-wide DSS and desktop DSS. An enterprise-wide DSS is linked to large data warehouses and serves many managers in the company. A desktop, single-user DSS is a small system that runs on an individual manager's PC.

2014

• (Trivedi et al., 2004) ⇒ Madhukar H Trivedi, Janet K Kern, Bruce D Grannemann, Kenneth Z Altshuler, and Prabha Sunderajan. (2004). “A Computerized Clinical Decision Support System As a Means of Implementing Depression Guidelines.” In: Psychiatric Services. doi:10.1176/appi.ps.55.8.879
  • QUOTE: The authors describe the history and current use of computerized systems for implementing treatment guidelines in general medicine as well as the development, testing, and early use of a computerized decision support system for depression treatment among "real-world" clinical settings in Texas. …

    … Although computerized decision support systems are being used in many areas of medicine and have demonstrated improved patient outcomes, their use in psychiatric illness is limited. The authors designed and developed a computerized decision support system for the treatment of major depressive disorder by using evidence-based guidelines, transferring the knowledge gained from the Texas Medication Algorithm Project (TMAP). This computerized decision support system (CompTMAP) provides support in diagnosis, treatment, follow-up, and preventive care and can be incorporated into the clinical setting.

1998

• Ghodsypour, Seyed Hassan, and Christopher O'Brien. “A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming." International journal of production economics 56 (1998): 199-212.

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