What is a decision support system?

By Rachel Lee - September 1, 2021

When data becomes big data, with the three Vs—volume, variety, and velocity—making sense of the numbers demands sophisticated data analytics. After all, you want to take the right next steps for your business to progress forward.

Enter the decision support system (DSS). Specifically built to not only organize, but also find meaning in your businesswide data, decision support systems are crucial for taking meaningful data-based action so you can keep up with and even beat the competition.

What is the definition of a decision support system?

Broadly speaking, decision support systems are expert processes that help businesses make informed organizational decisions.

Ways you can use a DSS:

    • To produce reports about key data trends based on specific parameters
    • To build predictive business models and visualizations, such as of projected revenue, product sales figures, or inventory
    • To evaluate current and historical data to gauge the health of a business and what to do about it

Often used by management in their decision-making processes, decision support systems are crucial for making big-picture assessments about your organization.

What are some examples of a decision support system?

The term DSS covers all systems that support decision-making activities. Common examples include:

    • GPS route planners: Think Google Maps or Waze — these DSSes consider multiple routes and road conditions to find you the best path between two points
    • Crop planning: Farmers can rely on DSSes to figure out the ideal schedule for planting, fertilizing, and harvesting their crops
    • Clinical decision support systems: In healthcare, doctors and other clinicians can use DSSes to make medical diagnoses, prescribe medications, and monitor the success of care plans

What are the key components of a decision support system?

Decision support system frameworks comprise three key components:

    1. User interface: The front-facing program enabling users to interact with the DSS
    2. Knowledge base: The all-encompassing collection of a business’s information, including raw data, documents, and personal knowledge — for larger volumes of data, this knowledge base requires data warehousing
    3. Model management system: Builds, stores, and manipulates data models

Commonly used models include:

    • Statistical models, for making connections between events and factors related to them, such as sales related to a given holiday
    • Sensitivity analysis models, for what-if analysis
    • Optimization analysis models, which use mathematics to determine the optimal solution for a business problem you’re trying to solve
    • Forecasting models, for analyzing past and current business conditions and making predictions
    • Backward analysis sensitivity models, for goal seeking, where based on a target value, the model will calculate targets for related variables. For example, when selling tickets for a limited-seating event, what should be the ticket price?

The benefits of a decision support system

Decision support systems benefit organizations in several ways:

    • Holistic point of view: Data warehouses DSSes pull from data sources from all aspects of the business
    • Enhanced business intelligence: DSS go beyond top-line revenue metrics, honing in on the specific factors affecting your business performance
    • Consistency: Data warehouses use standardized methods to process data from across an organization, making it more cohesive across the board
    • Speed: With all your data and queries in one place, perform your data analyses in near real-time
    • Efficiency: Users can access all company-wide data from a single platform
    • Ease of use: Little to no tech support needed for any user to access critical data

Five different types of decision support systems

There are five main types of decision support systems:

    • Communication driven
    • Data driven
    • Document driven
    • Knowledge driven
    • Model driven

Communication-driven DSS

Communications-driven DSSes help users to conduct meetings and otherwise work together on a shared task.

    • Examples: Chats and instant message software, Online collaboration tools
    • Target users: Internal teams

Data-driven DSS

The main focus of data-driven DSSes is to provide access to large repositories of internal and sometimes external data. They are used to query target databases or data warehouses to seek specific answers for specific questions, and are typically deployed via a mainframe system, client/server link, or the web.

    • Examples: Computer-based databases, File drawer and management reporting systems, Executive information systems, Geographic information systems (GIS)
    • Target users: Managers, staff, product/service suppliers

Document-driven DSS

These are a common type of DSS focused on searching web pages and retrieving documents based on specific search terms.

    • Example: Search engines
    • Target user: Broad user base

Knowledge-driven DSS

Knowledge-driven DSS is a blanket term for systems built using artificial intelligence technologies. Equipped with specialized problem-solving expertise, they are used to suggest or recommend actions to managers, using tasks that would otherwise require a human expert. Knowledge-driven DSS are often paired with data mining to sift through large amounts of data to identify the content relationships within.

Other names for knowledge-driven DSSes include advisory, consultation, suggestion, rule-based, and intelligent DSS.

    • Target users: Managers, staff, outside users interacting with the organization including consumers

Model-driven DSS

Model-driven DSS are complex systems that use business models like financial, representational, or optimization models to analyze decisions. They can be used for various purposes, depending on the data and parameters decision-makers set them up with.

    • Target users: Managers, staff, outside users interacting with the organization

Choose the best decision support system for you

With the cloud-scale data available to your modern-day business, you need decision support tools that can not just manipulate your data, but also provide you with the best course of action to further your broad-view business objectives. With Sisu, you can analyze all your businesswide data with just a few clicks.

Learn the what and the why of your key data changes so you can start making quicker and smarter business decisions today. Want to see this in action? Schedule a demo with Sisu today.

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