In economics, the ideal decision making is where the consumer has full knowledge of all opportunity cost presented for a range of goods or services and chooses the best fit for their demands and ability to acquire. Much in the same way any company head or authority figure would not choose a path for an organisation without knowing what other opportunities would be forgone in choosing this path.

Most times they rely on data gathered and presented to make such strategic decisions - for this there is a specific class of systems called Decision Support Systems.

According to Information Builders, Decision Support Systems (DSS) are a specific class of computerised information systems that supports business and organisational decision-making activities. A properly-designed DSS is an interactive software-based system intended to help decision makers compile useful information from raw data, documents, personal knowledge, and/or business models to identify and solve problems and make decisions.

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

An inventory of all your current information assets

Comparative revenue figures between one period and the next

Projected revenue figures based on new data and assumptions

Consequences of different decision alternatives, given past experience in a context that is described

There are different types of DSS applications which are driven by different components:

1. Model-driven: Model-Driven DSS uses complex financial, simulation, and/or optimisation models to provide decision support. This system uses data and parameters that are set by the decision maker, which in turn assists in analysing a situation.

2. Data-driven: Emphasises access to and manipulation of a time series of internal company data and possibly external data.

3. Communications-driven: Utilises network and communications technologies (LANs, WANs, Internet and Virtual Private Networks) to facilitate collaboration, communication, and decision-making.

4. Document-driven: Incorporates a variety of storage and processing technologies to provide complete document retrieval and analysis, which aids in decision-making. Examples of documents that would be available through a Document-driven DSS are policies and procedures, product specifications, catalogues, and corporate historical documents, including minutes of meetings and corporate records.

5. Knowledge-driven: A person-computer system with specialised problem-solving expertise that can suggest or recommend actions to management.

6. Web-based: Delivers decision support information or decision support tools to management through a web browser. A web-based DSS can be communications-driven, data-driven, document-driven, knowledge-driven, model-driven, or any combination of these.

The typical architecture of a decision support system includes mechanisms for collecting and storing the data, as well as rendering the data into a useful format for persons to query. If a there was DSS for strategic decision making by the government then it would be a large integrated system that would span across several agencies for collecting data, such as shipping and manifest data, tax compliance data, fuel importation and the stock index levels, and also ministries for preparing reports for key decision makers such as ministers and council members. Below shows a diagram outlining the basic architecture of such a system

Advantages

1. Time saving: Research has demonstrated that all categories of decision support systems reduce decision cycle time, increase employee productivity, and provide more timely information for decision making.

2. Improved interpersonal communication: Improved communication and collaboration between decision makers can be a result of DSS. Model-driven DSS allows users to share facts and assumptions.

3. Increased decision maker satisfaction: DSS can help reduce frustrations of decision makers by providing the perception that better information is being used.

4. Increased organisational control: Data-driven DSS often makes business transaction data available for performance monitoring.

5. Targeted marketing: DSS can be used to target a specific customer segment and gain an advantage in meeting needs in that particular segment. DSS can help track customers and make it easier to serve a specialised customer group.

Challenges

1. Transfer of power: Building any form of DSS may be seen as transferring decision authority from a human to a software programme. DSS should only be used to improve decisions. The system cannot capture all the complexities of human decisions; therefore, the human decision maker should still be a part of the process.

2. Unanticipated effects: The implementation of the decision support technology may reduce the skills required to perform a decision task because some DSS tend to overload the decision maker with information, resulting in decreased decision-making effectiveness.

3. Obscuring responsibility: Some users may deflect personal responsibility to DSS. Users may need to be constantly reminded that the computerised DSS is an intermediary between the people who built the system and the people who use the system. All responsibility should be held to the users and designers of the system.

Possible Way Forward

It is possible that an inter-governmental DSS would be beneficial for an in-depth analysis of the true elements of the economy and country as a whole. In moving forward, more importantly moving in the right path, it would be best to be as accurately informed as possible, so at least the right decisions can be made.

- Vallana Hill