The four characteristics of decision support systems

The four characteristics of decision support systems

There are four defining characteristics of decision support systems that separates them in the world of software. Namely, these types of systems turn data into decisions.

The core purpose of a decision support system is to provide useful information for making a decision. That is, the system collects relevant information from the world, analyses it and then presents it to the decision maker. In this way, the system tells the user something new about their world that they would not otherwise have known. The four characteristics of decision support describe how this type of software collects and presents data in an insightful way.

Four characteristics of decision support

Data is at the heart of every decision support system: every time, without exception. Data, data, data! Through these four characteristics of decision support, you can turn your data into decisions.

One: Data collection

The first of the four characteristics of decision support is that the system must collect data. A familiar example of a decision support system is daily weather report. This is a system that collects information about the temperature throughout the world. There use a range of devices to collect measurements, such as the temperature. These gauges become part of a massive decision support system that is useful for any person interested in the heat of the day. If a decision support system is to be useful, it must first collect data that is relevant to your decision.

Two: Data Management

Once you have the data, you have to manage it. First and foremost, that means somewhere to store it. For example, all of the measures of a temperature gauge needs to be stored so that it can be analysed. This usually means some kind of database or data log. A system that provides decision support, also has a way to manage the data that it collects.

Three: Data Analysis

The third of the characteristics of decision support system is when data becomes insight. By itself, raw data is rarely useful. Rather, it must crunched to meet the needs of the people who may benefit from it. However, with some high quality analysis, that data may become essential for making big decisions. This can be the difference between helping a farmer plan the next day’s harvest or a pilot flying an airliner at 38,000 feet. Same source data, but very different types of analysis. Therefore, analysis makes a world of difference when it comes to decision support.

Four: Data Presentation

Data presentation is all about how you deliver your information to people. It is the interface and interaction between data and user. This is the user interface, look and feel, column graph or pie chart.

How a system present information can make all the difference as to how useful a decision support system is. As with temperate, you can represent today’s maximum using a sun or snowflake icon. In this way, you immediately know what the day is going to be like. This example, is decision support at it’s best because it is relevant, timely and useful!

Relevant and useful information

To sum up, a decision support system is a computer-based information technology with four characteristics:

  1. data collection;
  2. storage of data;
  3. analysis of data; and
  4. data presentation.

The characteristics enable a system to deliver relevant and useful information for making decisions. Together, they enable people to turn data into decisions.

Carl Sudholz is the founder at AGContext and specialist in the integration of information technology within organisations. He holds two degrees, is a certified Business Analyst and a Director of the Australia Chapter of the International Institute of Business Analysis. Carl’s expertise and experience spans 15 years serving public, private and non-for-profit organisations to take control over technology.