Limitations & Disadvantages of Decision Support Systems

Limitations of Decision Support Systems

Decision support systems have been incorporated into businesses to support human intelligence for years. However, these systems are not perfect. Although DSSs stop a decision maker from promoting a bias, they simply aid in decision making by offering useful insights into easily consumable bites. The idea is to present all tangible information in the forms of graphs, pictures or text, so that you don’t overlook facts.

Depending too much on a decision support system and placing an unusual amount of trust in it is not a healthy sign. A lot of uncertainties are associated with DSS, such as:

  • Difficulty in Quantifying All the Data: A decision support system majorly relies on quantifiable data. Consequently, it’s difficult to analyze intangible or indefinable data. In reality, some values cannot be very specific and defined in numbers. Even though a DSS may quantify some of these aspects, the end result must be duly considered by the decision makers. They must use their own judgment when making the final decision.

  • Unaware of Assumptions: As a decision maker, you may not be fully aware of the assumptions that a decision support system has considered when analyzing data for a specific problem. Making decision without considering uncontrollable factors may prove to be dangerous. A decision maker must realize that a computerized DSS is only a supporting tool. You must consider an unstructured or partially structured situation in-depth and analyze the limitations and assumptions.

  • System Design Failure: Decision support systems are designed to the specific needs of a decision maker. If you don’t know what you want a DSS to do or how it should help you, it will be difficult to design a system that fits your needs. And when you use a vague DSS, the results generated are not what you’re looking for. Such situations may arise because of system design failure.

  • Difficulty in Collecting All the Required Data: As a decision maker, you must realize that it’s not possible to capture all of the related data mechanically. While some data is difficult to record, some cannot be recorded at all. Therefore, the value presented by a DSS may not be 100% true.

  • Lack of Technology Knowledge in Users: Although decision support systems have become much simpler over the years, many decision makers still find it difficult to use. Lack of technological knowledge remains an issue.

Disadvantages of Decision Support Systems

Besides limitations, decision support systems also have some disadvantages, such as:

  • Information Overload: A computerized decision making system may sometimes result in information overload. Since it analyzes all aspects of a problem, it leaves a user in a dilemma what to consider and what not to consider. Not each bite of information is necessary in decision making. But when it’s present, a decision maker finds it difficult to ignore information that is not a priority.

  • Too much Dependence on DSS: It is true that decision support systems are integrated into businesses to make everyday decisions faster and more easily. Some decision makers develop a tendency to depend too much on computerized decision making and don’t want to apply their own brains. Clearly, there is a shift in focus and decision makers may not hone their skills further because of excessive dependence on DSS.

  • Devaluation of Subjectivity: A decision support system promotes rational decision making by suggesting alternatives basis the objectivity. While bounded rationality or restricted irrationality plays a critical role in decision making, subjectivity cannot and should not be rejected. A DSS promotes objectivity and relegates subjectivity, which can have serious impact on a business.

  • Overemphasis on Decision Making: Clearly the focus of computerized decision making is on considering all aspects of a problem all the time, which may not be required in many of the situations. It is essentially important to train the users to ensure effective and optimal use of DSS.

  • Cost of Development: The cost of decision making decreases once a decision support system is installed. But development and implementation of a DSS requires a huge monetary investment. Customization may attract higher cost. If you’re on a tight budget, you might not get a customized DSS specific to your needs.

Resistance to Using Decision Support System

While a large number of organizations have already incorporated DSS into business decision making, a lot are still resistant to integrate it. There may be a number of factors why they are still hesitant in adopting a DSS. These may include:

  • Fear of Learning: Almost all of us have some level of fear instilled in us. We are afraid of exploring and learning new things. In fact, we fear of admitting that we lack technological knowledge required to use a DSS. This attitude makes an organization resistance to use a decision making system.

  • Getting Out of Comfort Zone: It’s not only the fear of learning that stops companies from adopting a DSS. Rather it’s about getting out of comfort zone and laying hands on to new things that may require some extra effort on their part. They don’t want to shed their age-old practices and admit that technology, if used correctly, actually turns things in their favor.

  • Fear of Implementation of New Technology: Technology can be scary for many individuals. They are not comfortable with the idea of doing things using the latest technology. Moreover, they fear undergoing training or participating in workshops geared towards providing functional skills. They also are afraid of chaos occurred due to implementation of a new system.

A proper address from the managers and C-suite can help employees overcome the fear and resistance to using new technology.

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