Advanced analytics – from big data, to machine learning, to cognitive computing -- is poised to and, in many cases, already is transforming enterprises in fundamental ways.  Analytics is both an enabler and driver of enterprise transformation.  The objective of this special issue is twofold – (i) to publish rigorous and innovative research on the role that analytics plays in enabling enterprises to transform by adopting these capabilities at scale in the digital era, and (ii) to gauge the pace of adoption of advanced analytics (e.g. big data, machine learning, cognitive computing etc.) to the above end.

We welcome papers that explore how analytics, in all its forms, is being adopted to transform processes across functions or entire organizations.  Analytics can take many forms including data visualization, descriptive analysis, predictive alerts/ recommendations, dashboards, machine learning algorithms, cognitive computing etc.  Analytics can occur at many levels of an organization from the boardroom to the shop floor.  Of particular interest are not the specific applications or technical solutions but rather the adoption of these capabilities across the organization to transform decision making processes at scale, while the organizations themselves are being disrupted in the digital era.  We encourage submissions that draw from diverse theoretical backgrounds such as engineering, computer science, decision science, creative visual design, organizational design and behavioral economics. We are open to a wide set of methodological approaches including empirical research, case-based research, field studies, behavioral decision making experiments, among others.  We encourage collaboration between academia and industry and welcome diverse submissions by both industry and geography.  

Some prospective topics include:

Value of Analytics 

• Where is the value?  Targeting, focusing, measuring and realizing the value from analytics while anticipating disruptive threats in their industry.
• Optimizing the business you have while planning with agility for the business you want to become in a dynamic uncertain market.

The Data Economy

• Migrating to the Data Economy by taking advantage of the wealth of data being generated both internally and externally to provide more effective decision support.
• Leveraging cloud-based digital platforms to enable speed to capability, address latency challenges and provide right-time insights.
• Striking the right balance between this natural migration and tradeoffs around data security, data privacy and compliance.

Adoption of Advanced Analytics

• Adoption of advanced analytics and machine learning to solve problems in new ways.
• Cognitive is coming – adoption is slower than you think and the use case universe is sparse.
• When will we reach the tipping point from over-hyped and inflated expectations to wide scale adoption of advanced analytics methods (e.g. explainable AI)?

Decision Science

• Embedded analytics in decision making (e.g. fully automated, predictive alerts, role-based decision cockpits etc.).
• Adoption of evidence-based decision making – the convergence of technology, behavioral science and organization design.
• Impacts of interactive visualizations on acceptance and use of analytics.
• The cusp of a new wave in the fields of management and decision science.

Organization Design

• Organizing for success – bridging the gap between the business decision makers, the data science community and the information technology organization.  What are the tradeoffs between agility and industrialization?
• Adapting the culture of the organization to be insight driven, especially when the insights challenge established and accepted norms.

Submission Instructions

• Submission Deadline: September 1, 2017
• First Round Review: November 1, 2017
• Second Round Review (if needed): January 1, 2018
• Publication: Summer 2018

For further information regarding this special issue, please email the Special Issue Editors:

• William B. Rouse, Stevens Institute of Technology, rouse@stevens.edu
• Jim Spohrer, IBM, spohrer@us.ibm.com

Editorial information

• Guest Editor: John Casti, X-Center, Vienna
• Guest Editor: Tim Chou, Stanford University
• Guest Editor: Alex Kass, Accenture
• Guest Editor: Richard Larson, MIT
• Guest Editor: Paul Maglio, University of California, Merced
• Guest Editor: Harold Sorenson, University of California, San Diego
• Guest Editor: James Tien, University of Miami

http://explore.tandfonline.com/pages/cfp/ujet-cfp-analytics-2q2017

Listen to the podcast

By Bala R. Iyer, Rahul C. Basole 
Communications of the ACM, Vol. 59 No. 11, Pages 27-30
10.1145/3000610

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The Geisinger Health System Seed Grant Program funded $600-thousand jointly for the following research projects:

Dr. Jim Rehg (Georgia Tech), Dr. Jimeng Sun (Georgia Tech), Dr. Brandon Fornwalt (Geisinger Health System): "Heart Track: Software to predict diagnosis, therapy and outcomes from heart images"

Dr. Turgay Ayer (ISyE, Georgia Tech), Dr. Seth Hostetler (Geisinger Health System): "Development of an Operational Decision Support Tool for Biologic Pharmaceutical Use in Chronic Disease Management"

Dr. Annalise Paaby (Georgia Tech), Dr. Sarah Pendergrass (Geisinger Health System): "Identification of genes and diseases associated with developmental robustness"

Source: CIO

WATCH

• Innovative approaches to understand and improve healthcare workflow and processes, e.g.  visualizing data for better clinical and management decision making
• Information systems and tools that improve clinical quality, workflow and processes
• The potential impact of emerging technologies on healthcare delivery and enterprise management

Improved Care Delivery

• The role of information and communication technologies for coordination among all care-givers, patients, and other elements of the care delivery system
• Data-driven methods for personalized and predictive medicine
• Informatics platforms and techniques for jointly improving clinical and managerial decision support
• Informatics tools that enable new models of care delivery, including improved access to healthcare
• Innovative approaches and evaluation of informatics approaches that improve diagnosis as well as detect and prevent clinical errors
• Novel approaches that integrate personal care with public and population health and vice versa

Informatics Challenges

• More facile approaches to managing data privacy, security and patient choices while improving secure access to data for sharing and system improvement
• New models for adoption and use of information and communications technologies in healthcare settings for and among key stakeholders
• Challenges of, initiatives in, and impact of data standards on healthcare delivery
• The role and challenges of using Internet and Web 2.0 technologies to create, access and share healthcare data

Policy

• Developing and implementing new economic models of financing of healthcare services through informatics-enabled mechanisms
• Support of patients and communities to evaluate, choose, and manage healthcare options
• Models that engage an evolving ‘user-friendly’ data ecosystem of key data elements essential to an integrated learning healthcare system

Timeline:

• Submission Deadline: March 1, 2016
• First Round Review Due: May 1, 2016
• Second Round Review (if needed): July 1, 2016
• Publication: Fall 2016

Manuscript Submission

Journal of Enterprise Transformation receives all manuscript submissions electronically via their ScholarOne Manuscripts website.

For further information, contact the Senior Guest Editors:

Don Detmer, University of Virginia, detmer@virginia.edu
Mark Braunstein, Georgia Institute of Technology, mark.braunstein@cc.gatech.edu

For more information click here.