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Updated Feb 21, 2023

Decision Support Systems Applications and Uses

Decision support systems may provide businesses with more accurate projections, better inventory management and data analysis.

Mark Fairlie
Mark Fairlie, Senior Analyst & Expert on Business Ownership
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Should you base your business decision-making on hard data or a gut feeling? When developing products, Steve Jobs trusted his judgment above everything else, and he seems to have been right more times than he was wrong. 

Intuition is often the source for new products and business improvement projects. But, for many entrepreneurs, acting on just an instinctive feeling alone is too risky. They want to test their ideas before deciding to take a particular course of action.

One way to do this is with decision support software. Below, we explain how decision support software works and how it can help you run your business better.

What is a decision support system?

A decision support system (DSS) is a computer-based information system that organizes, collects and analyzes business data. This analysis is then used by decision-makers to help them better manage and plan their organization or business. 

The typical types of information that are gathered by a DSS include sales figures, projected revenue and inventory data that has been organized into relational databases. The information it analyzes can come from multiple sources, like documents, raw data, management, business models and personal knowledge from employees.

DSS applications can be used in various fields, including credit loan verification, medical diagnosis, various types of business management, and evaluating bids on engineering, agricultural and rail projects.

Did You Know?Did you know
Relational databases contain data points that often connect to each other. For example, your CRM might assign a specific number to each client. It can tell which orders a particular client has placed, because that specific number is contained in the order record.

Types of decision support systems

While there is a DSS application for nearly every decision-making process, most of these tools fall into one of five categories.

Document-driven DSSs

Document-driven DSSs are widely used and allow users to search for information in internal and external databases (including the internet) using keywords. They sift through structured and unstructured data in documents, like profiles, ratings and financial spreadsheets. These systems are typically found online and in electronic files. [Read related article: The Best Spreadsheet Software]

Data-driven DSSs

Like document-driven DSSs, data-driven DSSs use quality data to determine a course of action based on a systematic process. They strategically break down questions and goals into pieces based on data.

For example, a business owner wanting to purchase additional equipment for operations could use one of these systems by looking at any data that supports this decision. Revenue, how frequently current equipment is used and the efficiency of current operations are some factors the owner could consider. By using a data-driven DSS, the owner can analyze ways to collect data to assess these factors and use the findings to make a decision on purchasing additional equipment.

Knowledge-driven DSSs

Knowledge-driven DSSs are mainly used by managers to find recommendations or suggestions for detailed problem-solving. These computer-based systems use artificial intelligence and human intellect to look at how issues of a problem are connected. They’re capable of making suggestions regarding how to act as well as recommending supporting material on a particular issue to users. They can also employ data-mining methods to make predictions for tests or studies and look at patterns to use for marketing plans.

FYIDid you know
A prime example of a model-driven DSS is financial modeling software, which allows companies, for example, to run break-even analyses, create business plans and calculate burn rate.

Model-driven DSSs

Model-driven DSSs help users to make choices and analyze decisions. They use models in areas like finances, simulations and statistics to present possible options in making a decision. Managers and staff use these tools to better understand the potential outcomes of a particular decision.

These systems use databases, but they are typically smaller than the ones used in data-driven DSSs. Simple processes use one model to look at basic decisions.

Combining two or more models often makes a process more complicated but can also help with weighing options for complex decisions.

Communication-driven DSSs

Teams use communication-driven DSSs to work together better. They make it easier for people to communicate and share information during the decision-making process.

Software and technology, such as video conferencing, instant internal messaging, and other network and online platforms are examples of communication-driven DSSs. They allow teams to consider choices and select options while meeting virtually and receiving quick responses from team members.

Specific uses for DSSs in business

There are many different ways managers can use DSS software to their advantage. Typically, business planners will build custom DSSs to evaluate specific operations. These include inventory management, in which DSS applications can provide guidance on establishing supply chain movement, and sales, in which DSS software helps managers predict how changes may affect results.

To manage inventory

DSSs are very helpful in evaluating inventory to help a business’s cash flow and profitability by predicting demand for particular products and itemizing assets.

To aid sales optimization and sales projections

Decision support technology can also analyze sales data, make predictions and monitor existing revenue patterns. Planners can use the technology to tackle sales numbers using a variety of decision support resources.

To optimize industry-specific systems

Other uses for decision support systems include projecting the future of a business or to get a bird’s-eye of a company’s performance. These insights help owners and managers navigate difficult situations better, especially when they have reliable information to predict expenditures and revenues.

Bottom LineBottom line
Retailers are using AI-powered DSSs to help them spot future trends, set prices, decide on store layout and power live chatbots.

Examples of DSSs

We all use DSSs in our personal and business lives every day. For example, every time you use Google, you’re using a highly sophisticated DSS that organizes a massive amount of information in a searchable, retrievable format. It can locate the specific images, videos and text files you need to help your business achieve more.

GPS tracking is another type of DSS. As you can see in our Verizon Connect review, its software allows drivers to determine the best and quickest route between two points while monitoring traffic conditions and helping them avoid congestion.

These are some other uses of DSS, including:

  • Agriculture: Farmers use DSS tools for crop planning to help them determine the best times for planting, fertilization and harvesting.
  • Medicine: Clinical DSS technology has many uses: maintaining research information about chemotherapy protocols, preventive and follow-up care, and monitoring medication orders. DSSs are also used with medical diagnosis software.
  • Weather forecasting: Some states use DSSs to provide information about potential future hazards such as floods. To do this, they factor in real-time weather conditions, floodplain boundaries information and historic county flood data.
  • Real estate: Real estate companies use DSSs to manage data on comparable home prices and acreage.
  • Education: Universities and colleges use DSSs to know how many students they currently have enrolled. This helps them predict how many students will register for particular courses or whether the student population is sufficient to meet the university’s costs.

Additional reporting by Shayna Waltower

Mark Fairlie
Mark Fairlie, Senior Analyst & Expert on Business Ownership
Mark Fairlie brings decades of expertise in telecommunications and telemarketing to the forefront as the former business owner of a direct marketing company. Also well-versed in a variety of other B2B topics, such as taxation, investments and cybersecurity, he now advises fellow entrepreneurs on the best business practices. With a background in advertising and sales, Fairlie made his mark as the former co-owner of Meridian Delta, which saw a successful transition of ownership in 2015. Through this journey, Fairlie gained invaluable hands-on experience in everything from founding a business to expanding and selling it. Since then, Fairlie has embarked on new ventures, launching a second marketing company and establishing a thriving sole proprietorship.
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