Open Access

Editorial

Decision Analytics20141:1

DOI: 10.1186/2193-8636-1-1

Received: 9 December 2013

Accepted: 9 December 2013

Published: 19 February 2014

Abstract

Decision making is a balancing act on a three-legged stool of insight, analysis, and action. If we cannot keep the three legs even, we wobble. And sitting on the stool is not even enough. We have to juggle known with unknown, fact with fiction, cognition with sensation and knowledge with ignorance. To make informed and effective decisions, decision makers must keep the three legs of insight, analysis, and action even by embracing:

• Data Mining – to leverage the knowledge hidden within organizational data by utilizing a wide range of statistical methods, data visualization techniques, and pattern recognition approaches.

• Predictive Modeling – to identify organizational risks and opportunities by exploiting patterns found in historical and transactional data.

• Simulation Modeling – to examine and compare options and scenarios prior to implementation by utilizing application of simulation in enterprise and organizational context.

• Optimization Modeling – to make the best choice by means of various optimization models.

• Prescriptive Methods – to create better solutions by exploiting the joint application of predictive models and optimization technology.

• Business Intelligence – to gain and sustain a competitive edge by utilizing the latest techniques in data mining, analysis, and performance management.

I am pleased to announce the launch of Decision Analytics, a peer-reviewed open-access journal, published by Springer. I invite everyone to submit high-quality research papers to make Decision Analytics one of the most prominent international journals in decision sciences.

Decision Analytics promotes the applications of computer technology, operations research, statistics, and simulation to decision making and problem-solving in all organizations and enterprises within the private and public sectors. The journal focuses on predictive as well as prescriptive analytics taking organizations to a higher degree of intelligence and competitive advantage. While predictive analytics, such as forecasting, emphasize the future, prescriptive analytics, such as optimization, enable organizations to choose the best course of action. The combination of predictive and prescriptive analytics can help organizations achieve both efficiency and effectiveness.

The principal objective of Decision Analytics is to establish a forum amongst academic researchers, policy-makers, and practitioners concerned with the development of new methodologies to formulate and solve organizational problems by applying decision analytics methods. The journal provides a publication vehicle for theoretical, empirical, and analytical research as well as real-world applications and case studies. Papers published in Decision Analytics should not only meet high standards of research rigor and originality in decision analysis, but they should also embrace predictive and prescriptive analytics.

I am very pleased to be able to call on a highly-regarded and well-respected international editorial board consisting of members with considerable expertise in the field of decision analytics. The editors and editorial board guarantee that peer-reviewed articles will be of exceptional quality. I look forward to the long journey that lies ahead and hope that Decision Analytics will become the ultimate source of new findings in analytical decision making and problem-solving.

Authors’ Affiliations

(1)
Business Systems and Analytics Department Lindback Distinguished Chair of Information Systems and Decision Sciences La Salle University

Copyright

© Tavana; licensee Springer. 2014

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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