DSS News
                D. J. Power, Editor
         November 19, 2006 -- Vol. 7, No. 24

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     Check the article by Mark Demarest "Improving Data 
 Legibility in Decision Support Systems" at DSSResources.COM



* Ask Dan: What are the advantages and disadvantages of 
computerized decision support?
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   "Decision Support for Global Enterprises" Conference
           Jan. 2-4, 2007, Calcutta, India


Ask Dan!

What are the advantages and disadvantages of computerized decision

by Dan Power

This question in various forms has been popular in the Ask Dan!
email. For example, J. Maclearn asked "What are the advantages and
disadvantages of decision support systems?" On a related topic, Wong
Soon Chen asked me to justify the statement that "Managers need
computerized decision support and supporting technologies to do their
jobs better" with relevant facts and figures. Mick Spain wrote "I'm
trying to do an academic literature review of decision support
systems in general and measuring how they benefit strategic decision
making in particular." He requested my comments on the topic and
recent references. Lynn Oelke wrote asking "What are the benefits of
using DSS for Health Care Administrators?" Rosjalina asked "How can
data warehouses benefit organizations?" 

A number of Ask Dan! columns have addressed related questions, but
now seems like a good opportunity to summarize the advantages and
disadvantages of computerized decision support. It is not possible in
an Ask Dan! column to cite all of the studies that support the
following conclusions, but interested readers are encouraged to check
Alter (1980), Power (2002) and Udo and Guimaraes (1994) and review
articles that have been published in the Decision Support Systems
journal (ISSN: 0167-9236, imprint: NORTH-HOLLAND, began publication
in 1985). Let's start with the advantages:

1) Time savings. For all categories of decision support systems,
research has demonstrated and substantiated reduced decision cycle
time, increased employee productivity and more timely information for
decision making. 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.

2) Enhance effectiveness. A second category of advantage 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 like perceived decision quality
rather than objective measures. For example, Hogue and Watson (1983)
reported the most important reason managers cited for using a DSS was
to obtain accurate information. Studies of model-driven DSS have
examined this outcome more than research on other types of DSS (cf.,
Sharda, Barr, and McDonnell, 1988). Advocates of building data
warehouses identify the possibility of more and better analyses that
can improve decision making.

3) Improve interpersonal communication. DSS can improve communication
and collaboration among decision makers. In appropriate circumstances,
communications-driven and group DSS have had this impact. Model-driven
DSS provide a means for sharing facts and assumptions. Data-driven DSS
make "one version of the truth" about company operations available to
managers and hence can encourage fact-based decision making. Improved
data accessibility is often a major motivation for building a
data-driven DSS. This advantage has not been adequately demonstrated
for most types of DSS.

4) Competitive advantage. Vendors frequently cite this advantage for
business intelligence systems, performance management systems, and
web-based DSS. Although it is possible to gain a competitive
advantage from computerized decision support, this is not a 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 read Ask Dan!
(Vol. 6, No. 17, July 31, 2005).

5) Cost reduction. Some research and especially case studies have
documented DSS cost saving from labor savings in making decisions and
from lower infrastructure or technology costs. This is not always a
goal of building DSS.

6) 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 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 "love/hate"
tension of using computers for decision support.

7) Promote learning. Learning can occur as a by-product of initial
and ongoing use of a 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
DSS serve as "de facto" training tools for new employees. This
potential advantage has not been adequately examined.

8) Increase organizational control. Data-driven DSS 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. What
is not always evident is the financial benefit from increasingly
detailed data. Regulations like Sarbanes-Oxley often dictate
reporting requirements and hence heavily influence the control
information that is made available to managers. On a more ominous
note, some DSS provide summary data about decisions made, usage of
the systems, and recommendations of the system. 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 on these questions.

Decision support systems should accomplish a purpose that is valued
in an organization, but in addition it is important to examine the
impact of computerized decision support from individual, group and
organizational perspectives. I am a computerized decision support
"evangelist". I have concluded based upon experience and research
that DSS when appropriately implemented and used can provide
individuals, groups and organizations with advantages and benefits. I
have been spreading the word about computerized decision support for
more than 30 years, but I have tried to remain objective and balanced
in my writings and research. In that spirit, let's examine "the dark
side", the disadvantages of computerized decision support.

DSS can create advantages for organizations and can have positive
benefits, but building and using DSS can create negative outcomes in
some situations. For example, some data-driven DSS development
efforts lead to power struggles over who should have access to data.
Also, managers may have personal motives for advocating development
of a specific DSS that harms other managers or the organization as a
whole. My discussion of disadvantages builds upon the work of Klein
and Methlie (1996, p. 172-181) and Winograd and Flores (1986). The
following are eight disadvantages:

1) Overemphasize decision making. Clearly the focus of those of us
interested in computerized decision support is on decisions and
decision making. Implementing DSS may reinforce the rational
perspective and overemphasize decision processes and decision making.
It is important to educate managers about the broader context of
decision making and the social, political and emotional factors that
impact organizational success. It is especially important to continue
examining when and under what circumstances DSS should be built and
used. We must continue to ask if the decision situation is
appropriate for using any type of DSS and if a specific DSS is or
remains appropriate to use for making or informing a specific

2) Assumption of relevance. According to Winograd and Flores (1986),
"Once a computer system has been installed it is difficult to avoid
the assumption that the things it can deal with are the most relevant
things for the manager's concern." The danger is that once DSS become
common in organizations, that managers will use them inappropriately.
There is limited evidence that this occurs. Again training is the only
way to avoid this potential problem.

3) Transfer of power. Building DSS, especially knowledge-driven DSS,
may be perceived as transferring decision authority to a software
program. This is more a concern with decision automation systems
(check than with DSS. I advocate building
computerized decision support systems because I want to improve
decision making while keeping a human decision maker in the
"decision loop". In general, I value the "need for human discretion
and innovation" in the decision making process.

4) Unanticipated effects. Implementing decision support technologies
may have unanticipated consequences. It is conceivable and it has
been demonstrated that some DSS reduce the skill needed to perform a
decision task. Some DSS overload decision makers with information and
actually reduce decision making effectiveness. I'm sure other such
unintended consequences have been documented. Nevertheless, most of
the examples seem correctable, avoidable or subject to remedy if and
when they occur.

5) Obscuring responsibility. The computer doesn't make a "bad"
decision, people do. Unfortunately some people may deflect personal
responsibility to a DSS. Managers need to be continually reminded
that the computerized decision support system is an intermediary
between the people who built the system and the people who use the
system. The entire responsibility associated with making a decision
using a DSS resides with people who built and use the system. 

6) False belief in objectivity. Managers who use DSS may or may not
be more objective in their decision making. Computer software can
encourage more rational action, but managers can also use decision
support technologies to rationalize their actions. It is an
overstatement to suggest that people using a DSS are more objective
and rational than managers who are not using computerized decision

7) Status reduction. Some managers argue using a DSS will diminish
their status and force them to do clerical work. This perceptual
problem can be a disadvantage of implementing a DSS. Managers and IS
staff who advocate building and using computerized decision support
need to deal with any status issues that may arise. This perception
may or should be less common now that computer usage is common and
accepted in organizations.

8) Information overload. Too much information is a major problem for
people and many DSS increase the information load. Although this can
be a problem, DSS can help managers organize and use information. DSS
can actually reduce and manage the information load of a user. DSS
developers need to try to measure the information load created by the
system and DSS users need to monitor their perceptions of how much
information they are receiving. The increasing ubiquity of handheld,
wireless computing devices may exacerbate this problem and

I briefly identified advantages and disadvantages of data warehouses
in DSS News, Vol. 1, No. 7 in July 31, 2000. I have also discussed
unintended negative consequences of DSS (Vol. 4, No. 8, April 13,
2003), rational thinking (Vol. 5, No. 21, October 10, 2004),
sustainable competitive advantage (Vol. 6, No. 17, July 31, 2005),
cognitive biases (Vol. 6, No. 20, September 11, 2005), and how use of
a Communications-Driven DSS impact a decision-making meeting (Vol. 7,
No. 4, February 12, 2006).

As always, your comments and suggestions are welcomed.


Alter, S.L. Decision Support Systems: Current Practice and Continuing
Challenge. Reading, MA: Addison-Wesley, 1980.

Hogue, J.T. and H.J. Watson, "Managemt's role in the approval and
administration of decision support systems," MIS Quarterly, 7(2),
June 1983, pp. 15-26.

Klein, M. and L. B. Methlie, Knowledge-based Decision Support Systems
with Applications in Business. Chichester, UK: John Wiley & Sons,

Power, D. J. Decision Support Systems: Concepts and Resources for
Managers, Westport, CT: Greenwood/Quorum Books, 2002, ISBN:

Power, D., "What are the advantages and disadvantages of Data
Warehouses?" DSS News, Vol. 1, No. 7, July 31, 2000.

Power, D., "Can using a DSS have unintended negative consequences?"
DSS News, Vol. 4, No. 8, April 13, 2003.

Power, D., Do DSS builders assume their targeted users are rational
thinkers? DSS News, Vol. 5, No. 21, October 10, 2004.

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., "Can computerized decision support systems impact,
eliminate, exploit, or reduce cognitive biases in decision making?"
DSS News, Vol. 6, No. 20, September 11, 2005.

Power, D., "How does the use of a Communications-Driven DSS impact a
decision-making meeting?" DSS News, Vol. 7, No. 4, February 12, 2006.

Sharda, R., S. Barr, and J. McDonnell, "Decision Support Systems
Effectiveness: A Review and an Empirical Test, Management Science,
vol. 34, no. 2, 1988, pp. 139-159.

Simon, Herbert A. "Decision Making and Problem Solving." Research
Briefings 1986: Report of the Research Briefing Panel on Decision
Making and Problem Solving. Washington, DC: National Academy Press,

Udo, G. J. and T. Guimares. "Empirically Assessing Factors Related to
DSS Benefits." European Journal of Information Systems, July 1994.

Winograd, T. and F. Flores, Understanding Computers and Cognition,
Reading, MA: Addison-Wesley, 1986.


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DSS Conferences 

1. Pre-ICIS 2006: SIG DSS Research workshop, Sunday, 
December 10, 2006, Milwaukee, WI. 
Check .

2. ICDSS 2007, 9th International Conference on DSS, Jan. 2-4, 2007, 
Calcutta, India. Theme: Decision Support for Global Enterprises.
Check . 


What's New at DSSResources.COM

11/17/2006 Posted an article by Mark Demarest, "Improving Data
Legibility in Decision Support Systems". Check the articles page.


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DSS News Releases - November 4 to November 17, 2006
Read them at DSSResources.COM and search the DSS News Archive

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11/15/2006 Open Text launches customer information management
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Enhances Capabilities of Health Care Fraud-Fighting Tool. 

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11/14/2006 Empagio delivers fully integrated business analytics
solution for decision support and metrics. 

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11/10/2006 Web collaboration: evolving trends as collaboration is
driven into the mainstream. 

11/09/2006 Tableau Software co-founder, Pat Hanrahan, wins
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11/08/2006 Information Builders and iWay Software release
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integration platform for BI. 

11/08/2006 TIBCO receives 2006 APICS Corporate Award of Excellence. 

11/08/2006 Fair Isaac Enterprise Decision Management technology
supports remote patient monitoring in innovative healthcare solution.

11/07/2006 myDecide, first social networking site dedicated to
decision making, debuts at Web 2.0 conference. 

11/07/2006 Business Objects honors customers for excellence in
Business Intelligence. 

11/06/2006 Microsoft rallies developers to build next-generation

11/06/2006 Stottler Henke enhances DataMontage Visual Data Analysis

11/06/2006 Palo Alto Software's business plan web site
listed on PC Magazine's 'Top 101 Classic Web Sites of 2006' list. 

11/06/2006 Cognos unveils new performance solution designed to help
corporate and retail banks improve customer profitability. 

11/06/2006 Analyst report confirms market share growth of 130 percent
for SAP NetWeaver(R) Business Intelligence, featuring BI Accelerator
with In-Memory Technology.

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