Communications Driven and Group Decision Support System
February 12, 2025
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Why do we determine whether a computerized decision support system application is worth considering or not?
Why is there a need to predict the actual impact of a proposed DSS?
In short, the question is - why is it necessary to evaluate a decision support system project?
The answer is simple.
It’s done to assess the scope and benefits of a DSS. Evaluation is a systematic approach to identify whether its implementation will help resolve problems for which it’s being developed.
The primary purpose of evaluation is to reflect on to its usage and scope, along with identify the changes/upgrades it will need in future.
Evaluation of decision support system projects is a systematic, rigorous and painstaking application of scientific, statistical and mathematical methods to assess their design, implementation, outcome and improvement. Having said this, it’s a resource-intensive process that needs a sizeable budget, time, labor, human intelligence and unswerving dedication.
Evaluating a DSS project is important because an organization spends a lot of time and money in developing and implementing it. It must fulfill the expectations of users and aid in decision making.
Assessing its scalability is also important as technology is changing very frequently. It must be scalable and able to integrate new tools and web technologies whenever need arises.
When we evaluate a decision support system project, we must ask questions to:
Evaluating a DSS project may be difficult yet important. In this article, we focus on their evaluation process and issues and ethics that you may come across while evaluating them.
Evaluating DSS projects is an ongoing process, given their large scale and constant requirement in decision making. Evaluation process should be in proportion to the size, scope, complexity and cost of a proposed DSS.
Generally evaluation process is not much time consuming, if it’s not carried for a web-based project. Therefore, it’s important for managers to understand the quantity of information that will be required to evaluate a DSS. They must also mull over the type of evaluation that needs to be carried to assess a particular DSS.
When they consider evaluating a DSS, this very idea gives rise to a lot many related questions, such as:
Asking these questions is important for a thorough evaluation of a DSS project. We will find answers to these questions along the way when we study the steps involved in a DSS project evaluation process.
DSS project evaluation is a multi-stage process and its scale determines the activities/steps to be taken to evaluate a project. One shouldn’t think that a project will work equally well years after as it does in present. Nor should one continue with a bad project just because they’ve invested time and money in building and implementing it.
A well-designed feasibility study provides a background of the project, a description of what it will do, details regarding research, technology, time, effort and money required for developing a project and legal, political, geographical ad cultural obligations to be fulfilled. Web-based DSS projects must be rigorously analyzed.
Evaluating DSS is a collaborative process. Digital analysts, managers, developers and decisions makers must come together to evaluate a DSS.
The number of resources required to DSS depends on latter’s size and complexity. Besides, it always pays up to evaluate in-house capabilities to evaluate a project. This will actually enhance the expertise of employees in using technological and other evaluation tools.
While a number of tools and techniques are used to evaluate decision support systems, it’s important to determine which tool works best for your project. Let’s now learn about different DSS evaluation tools and techniques.
If cost outweighs benefits, the idea is either further nurtured or dropped. Cost-benefit analysis tool takes into account hardware and software cost, personnel cost, process change cost, vendor/consultant cost, user training cost and infrastructure cost.
Cost-Benefit Analysis Process
Both costs and benefits can be tangible and intangible, hidden and explicit. Cost-benefit analysis only weighs the tangible aspects of a DSS project. Therefore, relying on this technique alone won’t be a great idea. Another tool must be deployed to approximate intangible aspects along with cost-benefit analysis.
The aim is to determine whether or not a proposed DSS work will work equally well in future scenarios. Qualitative Benefits Scenario is a rigorous, long and a systematic process, with steps including:
A DSS project is evaluated against four major criteria. What are those? Let’s learn about these here:
As the saying goes – everything has certain risk factors associated with it. A DSS project stands no exception to the rule. It is also associated with a number of risk factors. And risk increases with the ambiguity and disorderliness of objectives. The most common risk factors associated with a DSS project are:
Although DSS project risk factors cannot be completely eliminated but they can certainly be subsided or reduced to a considerable extent. This can be done by assessing and evaluating various aspects of a project at each stage of its development.
As businesses nowadays operate in a global marketplace, decision support systems must eliminate issues and obstacles pertaining to its use in different countries. These issues could be:
In addition to international and cultural issues, decision support systems are exposed to ethics and privacy problems. A DSS project fails dramatically, if it fails to address these concerns. As a developer or a manager, you may think that a computerized system is ethically neutral and therefore, it shouldn’t raise any ethical issues. Wrong!
You’re ignoring the importance of values and principles that go into decision making. When knowledge or model driven DSS are used, each choice is known to have made an ethical impact. Certain people may resort to a particular technique while some will not because there conscious or their principles don’t allow them to use it.
Therefore, while constructing a decision support system, all such issues must be taken care of, in order to ensure its smooth implementation and use. In addition, privacy concerns must be considered during the evaluation of a project.
The users expect a system to keep their personal, behavioral and habitual information private. The exact extent of privacy though cannot be defined but there should be an arrangement where DSS users can secure their private information.
Final Thoughts: Decision support systems are not a new technology. Rather they are being used more frequently. However, it’s really important to evaluate the scope of a project before taking it off the ground. This gives a clear idea of whether its implementation will be beneficial for a company or not.
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