In general, all of us involved with information technology and decision support need to remember the possible benefits of computerized decision support. During our hectic work week, it is very easy
to become myopic and think that what we are doing is an end in and by itself. Myopia refers to seeing nearby objects clearly, but distant objects are not seen or are blurry. In the world of
computerized decision support, many technical specialists have myopia. It is easy to see the need for an expanded infrastructure or the need for security patches or even master data management. The
solution to any problem is often an upgrade in the database software or purchasing a new software product from a persistent vendor.
Why the technology myopia? Technical skills are usually valued more than conceptual skills by people involved with information technology. Technical skills are critically necessary, but they
quickly become obsolete. We technologists need to see the “big picture” benefits of using technology. We cannot just focus on the technical details in the architecture, infrastructure
or applications framework. Each of us periodically needs our decision support vision corrected, enhanced and augmented.
The goal in this article is to review common benefits that have been, may be or can be achieved by implementing various types of computerized decision support capabilities in an organization. Every
decision support system (DSS) will not result in every benefit; and in the worst case, a poorly designed DSS may result in no benefit. Nonetheless, unless we IT folks keep an eye on the
computerized decision support prize, it becomes much less likely that any prize will be won. We need to evaluate the possible benefits of computerized decision support early in a project and set
goals to achieve some of them. Once a project is complete, we need to periodically revisit the intended benefits and measure how well the project is delivering them.
Let's review nine major potential benefits of computerized decision support:
Reduce cycle time and create time savings. For all categories of decision support systems and for decision automation, research has demonstrated and substantiated reduced
decision cycle time, increased employee productivity and more timely information for decision making from using specific systems. The time savings that have been documented from using
computerized decision support are often substantial. Researchers have not, however, always demonstrated that decision quality remained the same or actually improved.
Enhance decision making effectiveness. A second category of benefit that has been widely discussed and examined is improved decision making effectiveness and better decisions.
Decision quality and decision making effectiveness are, however, hard to document and measure. Most research has examined soft measures such as perceived decision quality rather than objective
measures. Advocates of building data warehouses often identify the possibility of more and better analyses that can improve decision making.
Improve communication among decision makers. DSS can improve communication and collaboration among decision makers. In some circumstances, communications-driven and group DSS
have had this impact. Model-driven DSS provides a means for sharing facts, assumptions and analyses.
Increase data accuracy and data sharing. Data-driven decision support systems make "one version of the truth" about company operations available to managers and hence can
encourage shared, fact-based decision making. Improved data accessibility and data sharing is often a major motivation for building a data-driven DSS.
Gain a competitive advantage. Vendors frequently cite achieving competitive advantage as a major reason for implementing business intelligence systems, performance management
systems and web-based DSSs. Although it is possible to gain a competitive advantage from computerized decision support, this is not a highly likely outcome. Vendors routinely sell the same
product to competitors and even help with the installation. Organizations are most likely to gain this advantage from novel, high risk, enterprise-wide, inward-facing decision support systems.
Measuring this is and will continue to be difficult. For more discussion of this issue, please read Can DSS provide firms with a sustainable competitive advantage? If so, how?
Reduce decision process costs. Some research and especially vendor case studies have documented computerized decision support cost saving associated with reduced labor costs in
making decisions and from lower infrastructure or technology costs.
Increase decision maker satisfaction. The novelty of using computers has and may continue to confound analysis of this outcome. DSS may reduce frustrations of decision makers,
create perceptions that better information is being used and/or create perceptions that the individual is a "better" decision maker. Satisfaction is a complex measure and often researchers
measure satisfaction with the DSS interface rather than satisfaction with using a DSS in decision making. Some studies have compared satisfaction with and without computerized decision aids.
Those studies suggest the complexity and the "love/hate" tension of using computers for decision support.
Promote decision maker learning. Learning can occur as a by-product of the initial and then the ongoing use of a specific DSS. Two types of learning seem to occur: learning of
new concepts and the development of a better factual understanding of the business and decision making environment. Some DSSs serve as "de facto" training tools for new employees. This
potential advantage has not been adequately examined, and it is probably much less likely to occur with data-driven DSSs.
Increase organizational control. Data-driven decision support systems often make business transaction data available for performance monitoring and ad hoc querying. Such systems
can enhance management understanding of business operations, and managers perceive that this is useful. It is not always evident that firms can realize financial benefit from accessing better
data. Regulations like Sarbanes-Oxley often dictate reporting requirements and hence heavily influence the control information that is made available to managers. Managers need to be very careful
about how decision-related information is collected and then used for organizational control purposes. If employees feel threatened or spied upon when using a DSS, the benefits of the DSS can be
reduced. More research is needed.
Even though the focus in this article has been on benefits of computerized decision support, part of any decision support feasibility study is evaluating potential harms and disadvantages of a
proposed system. Once we begin a DSS project and then complete implementation, we need to strive to achieve the intended benefits.
Keep expectations for benefits realistic and achievable. Set the goals for the project, communicate them and measure the accomplishment of them. For more information of computerized decision
support advantages and benefits, interested readers are encouraged to check the suggested readings listed below and review some of my Ask Dan! columns at DSSResources.com.
Alter, S.L. Decision Support Systems: Current Practice and Continuing Challenge. Reading, MA: Addison-Wesley, 1980.
Power, D. J. Decision Support Systems: Concepts and Resources for
Managers, Westport, CT: Greenwood/Quorum Books, 2002, ISBN: 156720497X.
Power, D., "What are the advantages and disadvantages of data warehouses?" DSS News, Vol. 1, No. 7, July 31, 2000.
Power, D., "Can DSS provide firms with a sustainable competitive advantage? If so, how?" DSS News, Vol. 6, No. 17, July 31, 2005.
Power, D., "What are the advantages and disadvantages of computerized decision support?" DSS News, Vol. 7, No. 24, November 19, 2006.
Udo, G. J. and T. Guimares. "Empirically Assessing Factors Related to DSS Benefits." European Journal of Information Systems, July 1994.
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