Why are some organizations slow to adopt new decision support technologies?
by Dan Power
Editor, DSSResources.COM
Change and innovation continues related to computerized decision support. Some managers seem quick to purchase new technologies and try out new capabilities, others are slower to adopt an innovation. Adopting a new technology is the first step in building a new capability and gaining technology acceptance in an organization. Managers can adopt an innovation, but intended users may not accept the new technology. So why are some managers quick to adopt and others delay. Leaders and laggards are common among individuals and organizations in the adoption of technology. In the late 1950s, sociology researchers (Bohlen, Beal and Rogers, 1957) proposed a technology adoption lifecycle model. Moore (1991) in Crossing the Chasm proposed a variation of the lifecycle.
Moore suggested that for discontinuous or disruptive innovations there is a gap or chasm between the first two adopter groups, the innovators and early adopters and the early majority. The early majority are pragmatists and hence are generally slower to adopt. The technology adoption curve (TAC) theory is explained in more detail in Power (2001). TAC helps understand the adoption of the wide variety of decision support technologies marketed in the past 30 years.
Decision support technologies are often disruptive innovations. Also, some decision support innovations are quickly obsolete or "faddish". Some decision support applications are purchased and adopted, but quickly become dated or revised. Also, underused and poorly accepted software known as "shelfware" sits on shelves in many IT departments.
Buying or building a new decision support capability can be a significant or a trivial decision. The innovation may be a one time purchase or an ongoing commitment of resources. Decisions about new technology involving a major commitment of resources are of primary interest. Some general reasons why one company is often an early adopter of significant decision support innovation and another is often slow can be identified. Reasons include the availability of resources, risk propensity, knowledge of the technology, the culture, and senior management characteristics. The interaction of these factors hinders a researcher or consultant trying to understand a particular company's situation.
A recent Ventana Research survey suggests some more detailed reasons for slow adoption of innovative technologies, including: 1) mistrust between IT and business executives, 2)lack of data quality and too many data sources, 3) delayed infrastructure projects have higher priority, 4) IT staff are poorly trained, and 5) new technologies are confusing and poorly understood. This list related to the maturity or level of adoption of information technology is more specific and suggests changes managers could make to encourage faster adoption of new technologies.
Adoption of decision support technologies should be a pragmatic, rational decision. Practical considerations should be the most important factors when managers adopt decision support technologies for their organizations. In some situations organizations have gained advantages from early adoption of technology, but examples of waste and negative disruptions are also common. In general, managers who are slow to adopt a potentially disruptive decision support technology are cautious and practical.
References
Beal, G. M., E. M. Rogers, and J. M. Bohlen (1957) "Validity of the concept of stages in the adoption process." Rural Sociology 22(2):166–168.
Moore, G. A., Crossing the Chasm, HarperBusiness, New York, 1991.
Power, D., Is there an ‘information culture’ that encourages building Decision Support Systems? DSS News, Vol. 2, No. 8, April 8, 2001 at URL http://dssresources.com/faq/index.php?action=artikel&id=17 .
Power, D., What is the technology adoption curve? Is it relevant to DSS? DSS News, Vol. 2, No. 13, June 17, 2001 at URL http://dssresources.com/faq/index.php?action=artikel&id=23 .
Ventana Research, "Five Causes of Information Management Immaturity," at URL http://www.information-management.com/gallery/IM-Ventana-governance-big-data-analytics-DM-ROI-10022546-1.html?ET=informationmgmt:e3246:207884 .
Last update: 2012-07-22 06:47
Author: Daniel Power
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