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)?
- 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.
- 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 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, firstname.lastname@example.org
- Jim Spohrer, IBM, email@example.com
- 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