DSS News
                       by D. J. Power
                June 17, 2001 -- Vol. 2, No. 13
         A Bi-Weekly Publication of DSSResources.COM
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* DSS Wisdom
* Ask Dan! -- What is the technology adoption curve? Is it relevant to 
* What's New at DSSResources.COM
* DSS News Stories
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DSS Wisdom
Steven Alter (1980) wrote, "It is quite possible that the "information 
utility" concept that was conceived in the 1960s will start to become a 
reality in the 1980s.  Builders of DSSs will be able to purchase or 
lease standard modules that can be transferred immediately over phone 
lines into the memories of their personal computers. Both internal 
corporate data and proprietary commercial data will be available in the 
same manner. Some of the standard off-the-shelf modules will be report 
generators; others will be easily tailored query languages, statistical 
packages, graphical display packages, etc. As noted earlier, the key 
stumbling block to greater use and accepance of DSSs is that it simply 
takes too long and requires too much effort to bring the concept of a 
system or type of analysis to the point where it can be tried out 
realistically. The combined power of network technology plus personal 
computers may have a profound impact in alleviating much of this problem 
in situations where the data exist and the models are reasonably well 
understood and not too complex. The degree to which it will help when 
the data are not readily available or the models are not well understood 
is much more questionable." (p. 191)
Alter, Steven.  Decision Support Systems: Current Practice and 
Continuing Challenges. Reading, MA: Addison-Wesley Publishing Co., 1980.
Ask Dan!
What is the technology adoption curve? Is it relevant to DSS?
The technology adoption curve is a theory about how individuals and 
organizations behave in implementing innovative technologies. A quick 
examination of the framework shows some similarities to the product
life cycle curve discussed in business marketing courses. The theory is 
however more sophisticated than a life cycle or a diffusion model. 
The underlying model of technology adoption identifies 5 types of 
adoptors of technology with very different interests and buying 
characteristics. The companies and individuals that are first to adopt a 
new technology are called innovators. The second type is known as the 
early adopters. The third type is called early majority, then the late 
majority adopters and, finally, the laggards. 
The technology adoption curve is a traditional bell curve with 
exponential growth in the beginning and a slowdown in adoptions 
occurring during the late majority period. When new technology is 
introduced, it is usually hard to get, expensive and imperfect. Over 
time, the technology's availability, costs and features improve to the 
point where a large population of users can benefit from adopting
the technology.
The innovators are technically oriented users and "visionary".
The laggards are practical and conservative. The early adopters are 
seeking a competitive advantage. Productivity issues and conformity 
influence the early and late majority adopters. 
Some technology innovations reach a "dead end" early in the adoption 
cycle. These immature or premature innovations never become "killer 
applications" like the VisiCalc spreadsheet.
To summarize:
Innovators are enthusiasts who like technology for its own sake. 
Early Adopters have the vision to adopt an emerging technology and apply 
it to an opportunity that is important to them. 
Early Majority adopters are pragmatists who do not like to take 
the risks of pioneering, but are ready to see the advantages of 
tested technologies. They are the beginning of a mass market for the new 
Late Majority adopters are also pragmatists and this group represents 
about one-third of available customers.  This group dislikes 
"discontinuous innovations" and believes in tradition rather than 
progress. The late majority buy high-technology products reluctantly and 
do not expect to like them.
Traditionalists (or laggards) don't really like technology.
This group performs a "reality testing" service for the rest of us by 
pointing out the discrepancies between the day-to-day reality of a 
technology product and the claims made for it.
This model is relevant to understanding the adoption of various decision 
support technologies.  Model-driven DSS are probably at the late 
majority stage, but Web technologies have reinvigorated that type of DSS 
and changed its adoption curve.  Data warehousing and OLAP are probably 
still in the hands of the early majority.  Customer Relationship 
Management (CRM) may be at a dead end.  Communications- Driven DSS are 
being adopted quickly. Knowledge-driven DSS are probably still in the 
early adoption stage.  Document-driven DSS are evolving with the Web 
Don Norman is credited with first explaining the technology adoption 
curve model. See an example at of the application of the curve to 
microprocessor technology at
Also check Moore, G. A. (1991) Crossing the Chasm, HarperBusiness, New 
York. Moore's model of technology adoption prescribes that
a company can not expect to target a mass market directly with a 
technology innovation. Rather, the company must first target the early 
SUPPORT TECHNOLOGIES? Will data visualization tools follow this
curve? What about OLAP or data warehouses? simulation models and 
optimization? Web-based DSS? Please send me your comments.
What's New at DSSResources.COM
06/17/2001 Posted case example by DataBeacon Staff, "Databeacon Goes 
Back to the Future in San Francisco", DataBeacon, Inc., Spring 2001, URL 
DSS News Stories - May 30 to June 13, 2001
06/13/2001 IDC Report states IBM is number one server company, 
outselling Sun by 60 percent.
06/11/2001 Cognos e-Applications provide immediate return on investment 
for J.D. Edwards customers. Check release.
06/07/2001 ClearCommerce uses Clementine data mining workbench in its 
fraud prevention solution.
06/06/2001 Business Objects won InfoWorld's Readers' Choice Award in 
Knowledge Management/Business Intelligence category.
06/06/2001 Broadvision and SAS announced a global strategic alliance at 
BVision 2001.
06/06/2001 Decisioneering releases upgrade to Crystal Ball 2000.
06/04/2001 iAnywhere to expand Java support to mobile and wireless 
05/31/2001 Sun announced that it is now in first place in NT workstation 
05/30/2001 Sun Microsystems and Informatica announced iForce Data 
Warehousing Reference Architecture.
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