Analytics Enabled Decision Making - An International Business Science Reference with Palgrave Macmillan

Chandan Maheshkar's picture
Call for Papers
September 1, 2021 to February 19, 2022
Subject Fields: 
Business History / Studies, Communication, Digital Humanities, Economic History / Studies, Research and Methodology

Call for Book Chapters

Analytics Enabled Decision Making

An International Business Science Reference with Palgrave Macmillan

Proposal Submission Deadline: October 20, 2021

Full Chapters Submission: February 19, 2022


"Have the courage to follow your heart and intuition; they somehow already know what you want to become" if one was to go by this quotation by Steve Jobs, then managers could rely solely on their intuition while taking critical decisions. However, the fact is that businesses cannot be exclusively run on intuitions. Organizations need to base their decisions on a rationalistic approach rooted in scientific reasoning and data. Undoubtedly, intuition can offer direction, but only to those with a strong sense of business intricacies and rich experience. But even for such managers, data-based decisions helps to quantify, understand and verify their own decisions, thereby reducing uncertainty and the accompanying risk. Data-enabled organizations can pre-empt challenging scenarios and prepare in advance, making them strategically competent. The five most successful organizations of the last decade also referred to as 'FAANG' (Facebook, Amazon, Apple, Netflix, and Google), are all data-driven organizations.


Considering the volumes of big data businesses are churning, analytics-enabled decision making has become the 'go-to strategy' for success. Business analytics make business practices intelligent and equip practitioners with predictive capabilities. Thus, organizations rely more on people able to crunch numbers and scientifically predict what the customer is likely to buy, when and how much, what could trigger attrition when the inventory is expected to run out, and the competitor's next move. In this regard, this proposed book aims to bring together industry practitioners and academicians who hold expertise in data analytics and are willing to share their knowledge and experience and contribute to the existing body of knowledge. The book 'Analytics Enabled Decision Making' will provide multiple perspectives, cases, and methods that enable practitioners to critically examine the different components of business through data. The Scholar-Practitioner approach of this book will offer more conceptual clarity and practice-based analytical thinking and methodologies.  


Tentative Content

Topics include, but are not limited to the following:

  1. Next-generation smart manufacturing and service systems using big data analytics
  2. Elements of decision making under uncertainty
  3. Data, Inference, and Marketing Decisions
  4. Competitor and competition Analysis through analytics
  5. Influence of big data analytics on business intelligence
  6. Improved price alignment to the perceived value of product/service using data analytics
  7. Changing the landscape of retailing using pricing analytics
  8. Enhancing efficiency and effectiveness in supply chain management through Business Intelligence
  9. Quantifying thoughts and feelings about a company from big data to improve brand strength
  10. Enabling achievement of organizational/corporate goals through HR analytics
  11. Workforce Analytics facilitates Human Resource Demand Forecasting
  12. Ascertainment of Employee Competencies and measurement with greater precision using T&D Analytics
  13. Analytics to Measure Employees' Behavioural Traits and predict employee performance
  14. Using predictive analytics alongside psychometric assessments and other measures to identify the candidates with exemplary performance and behavioural criteria
  15. Designing competitive yet cost-effective compensation packages using analytics to reduce attrition
  16. Mitigating Compliance Failure Risk using Analytics (gender-equal pay, overtime payments, appropriate number of each category of employees)
  17. Predictive analytics to aid employee alignment with the culture of the organization
  18. Analyzing the impact of Employees' Satisfaction and Frustration on their and organizations' performance
  19. Assessing and Controlling Political Behaviour of Groups in Organizations
  20. Measuring Organizational/Industrial Citizenship Behaviour
  21. Psychological Framework and Methodology for Analyzing Decision Risk
  22. Analyzing Challenging Behaviours of Two Individuals with Intellectual Differences/Disability
  23. Measuring the effectiveness of data analytics in higher education to improve student outcomes
  24. Building an industry 4.0 analytics platform with a proven example and proof of concept
  25. Gaining competitive advantage through business analytics



This book is proposed to be published by Palgrave Macmillan (an imprint of Springer Nature), an academic publisher of world repute in the humanities and social sciences. Please visit and for more details regarding the publisher and this publication.


Chapter Proposal Submission

Please submit the chapter proposal on or before October 20, 2021. It should be a brief outline of the chapter clearly explaining how the proposal fits into the book's scope and objective and the author's institutional affiliation, position, and contact details. All submitted chapters will be accepted based on a double-blind peer review editorial process. Thus, contributors may also be requested to serve as reviewers for this project.


Note: There are no submission or acceptance fees for manuscripts submitted to this book publication. Please use the subject line: "Analytics Enabled Decision Making"


Submissions and inquiries should be submitted to:

Vinod Sharma:,

Chandan Maheshkar:

Jeanne Poulose:,


Important Dates

  • Proposal Submission Deadline: October 20, 2021
  • Full Chapters Submission: February 19, 2022
  • Peer Review Results Returned to Authors: March 20, 2022     
  • Revised Chapter Submission: May 15, 2022



Dr. Vinod Sharma

Christ University, Delhi-NCR, India;


Dr. Chandan Maheshkar

M. P. Bhoj (Open) University, Bhopal, India


Dr. Jeanne Poulose

Christ University, Delhi-NCR, India;