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Dan Power

Greetings to all of my friends who work in the area of computerized decision support. This blog is a way for me to share stories from my encounters related to decision support, to comment on industry events, and to comment on other blogger's comments, especially those of my friends on the Business Intelligence Network. I'll try to state my opinions clearly and provide an old professor's perspective on how computers and information technology are changing the world. Decision making has always been my focus, and it will be in this blog as well. Your comments, feedback and questions are welcomed.

About the author >

Daniel J. "Dan" Power is a Professor of Information Systems and Management at the College of Business Administration at the University of Northern Iowa and the editor of, the Web-based knowledge repository about computerized systems that support decision making; the editor of; and the editor of DSS News, a bi-weekly e-newsletter. Dr. Power's research interests include the design and development of decision support systems and how these systems impact individual and organizational decision behavior.

Editor's Note: More articles and resources are available in Dan's BeyeNETWORK Expert Channel. Be sure to visit today!

by Daniel J. Power

A recent Capgemini (2012) study found that 9 out of 10 business leaders "believe data is now the fourth factor of production, as fundamental to business as land, labor and capital." That report concludes "Big Data represents a fundamental shift in business decision making." Data-driven decision making refers to the collection and analysis of data to guide or make decisions. Data has been used to support structured decisions since people began collecting and recording data. High velocity data can potentially improve routine, reoccurring decisions, but the impact on unstructured strategic decisions is less certain. Some vendors broadly assert that big data and statistical analysis will be helpful for "all" decisions if we are creative in using data. Decisions are choices among options, but some choices are more complex and difficult than others and some options are ambiguous and poorly defined.

Continue reading at

Please cite as:

Power, D. J. "What is data-driven decision making?" Decision Support News, Vol. 15, No. 23, November 9, 2014 at URL

Posted November 9, 2014 10:57 AM
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by Daniel J. Power

It is generally assumed that managers want to make data-driven decisions, rather than intuitive or "gut feel" decisions. Some evidence suggests that senior managers are only "pushing" data-driven decision making for operations decision makers. Are there important, strategic, long-term decision making use cases? Do senior business and government executives want to use "big data" to support their strategic decision making? Are there any examples of using "big data" to support strategic decision makers?

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Please cite as Power, D. J. "Are there strategic decision making 'big data' use cases?" Decision Support News, Vol. 15, No. 22 October 26, 2014.

Posted October 28, 2014 8:03 AM
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by Daniel J. Power

A data warehouse is a central, integrated repository for historical, enterprise data from multiple business systems. An expanded definition for data warehousing includes business intelligence tools for analyzing the data and OLAP is part of the broader category of business intelligence tools. Answering this question in detail depends upon who is asking. Managers need to be familiar with some DW/OLAP terminology, the basic "what is" questions, and they need to have an idea of the benefits and limitations of these decision support components, the why questions. More technical people in Information Systems need to know how and when to develop systems using these components.

Continue reading this classic column at

Power, D. J. "What do I need to know about Data Warehousing/OLAP?" Decision Support News, Vol. 15, No. 21 October 12, 2014 at .

Posted October 11, 2014 12:08 PM
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by Daniel J. Power

A person-machine interface is central to the effective use 
of a computerized system like a decision support system (DSS). 
The user interface (UI) shapes the user experience (UX). 
Decision support application developers must be kinowledgeable 
about user interface design concepts and principles. This article 
discusses what it means to elicit values in the context of 
building a model-driven DSS, reviews three approaches for 
eliciting values, and then proposes some hypotheses and design 
guidelines for a DSS interface design that is "best" for 
eliciting values.

Please continue reading this classic column at

Power, D. J. "What DSS interface design is 'best' for eliciting values" Decision Support News, Vol. 15, No. 17 August 17 2014 at URL

Posted August 17, 2014 9:00 AM
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by Dan Power

There are many "kinds" of decision support for diverse decision making 
situations. Both IS/DSS software designers and managers should ask about 
appropriate decision support for a situation. Decision support analysts 
and designers should know enough to answer the question given the facts 
about the decision making situation. The "kind of DSS" needed is a 
generic question. If we analyze a business decision as a situation, 
abstractly we can define elements like a decision maker, impacted parties, 
the decision setting, and the business environment. We can also analyze a 
specific decision at a specific time and identify the specific decision maker, 
the impacted parties with specific characteristics, the specific setting, 
the decision content, and the interpersonal dynamics that were occurring. 
We can view the situation from the point of view of the specific decision 
maker, a specific stakeholder, an interest group, or an outside observer. 
Let's explore a specific scenario and review questions or criteria to evaluate 
an array of situations. A number of years ago, "Jimmy" posted a decision 
support scenario and asked this question.

Continue reading this classic column at

Power, D. J. "What kind of DSS does Mr. X need?" Decision Support News, Vol. 15, No. 16, August 3, 2014 at URL

Posted August 3, 2014 7:08 AM
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