Designing a Business Analytics Culture in Organizations in India

2021 ◽  
pp. 670-678
Author(s):  
Tanushri Banerjee ◽  
Arindam Banerjee
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Data Organization ◽  
Business Analytics ◽  
Domain Specific ◽  
Consumer Lending ◽  
Effective Decision ◽  
Effective Decision Making

There are several challenges faced by decision makers while deploying Business Analytics in their organization. There may not be one resolution approach that is suitable for creating a Business Analytics culture in all organizations. However, it is easy to perceive that most India-based organizations may have similar issues of data organization that may be impeding their progression in the field of Analytics. Based on their research, the authors have proposed a framework for adoption of Analytics in Indian firms in their book “Weaving Analytics for Effective Decision Making” by SAGE. They propose to use that model for explaining certain domain specific adoption of Business Analytics in organizations in India. They have used a case study of a Global Bank which is in the process of establishing its consumer lending USA operations, an offshore captive operation, in India to describe the process of building an Analytics team in an organization in India. Data processed using R has been added as screenshots for supporting the findings.

A descriptive case study of effective decision-making of a local government organization in the United States of America

2020 ◽  
Vol 16 (3) ◽  
pp. 279-297
Author(s):  
Jennifer Capler
Keyword(s):  
United States ◽  
Decision Making ◽  
Local Government ◽  
United States Of America ◽  
The United States ◽  
Content Type ◽  
Government Organizations ◽  
Effective Decision ◽  
Effective Decision Making

PurposeThis article details a qualitative descriptive case study of affective factors of effective decision-making of one local government organization in the United States of America. The specific problem was that many elected American local government representatives lack effective decision-making strategies. This research focus indicated a lack of qualitative research on the real-world experience of factors that were taken into consideration during decision-making within American local government organizations.Design/methodology/approachUsing a local government organization in southwest Illinois, elected representatives were interviewed and observed. The interviews and observations surfaced how the representatives made decisions. Data were analyzed using manual coding and theming to determine themes and patterns.FindingsThe results produced six themes about factors, including emotional intelligence, which impacted decision-making. They are: (1) remembering the past, (2) communication and respect, (3) spurring economic growth and development, (4) fairness, (5) recognizing and removing emotions and bias and (6) accountability.Research limitations/implicationsBeing a single case study, this research is limited in generalization. The research was limited to the identification of current, real-world experience of elected local government representatives.Practical implicationsThe findings of this research can be used to create more effective decision-making practices for local government organizations of similar size.Originality/valueThis is the first study to review, in-depth, the decision-making and emotional intelligence factors of local government organizations in the United States of America. The conceptual background, discussion, implications to local government organizations, limitations and recommendations for future studies are discussed.

scholarly journals Scenario Development and Foresight Analysis: Exploring Options to Inform Choices

2018 ◽  
Vol 43 (1) ◽  
pp. 545-570 ◽  
Author(s):  
Keith Wiebe ◽  
Monika Zurek ◽  
Steven Lord ◽  
Natalia Brzezina ◽  
Gnel Gabrielyan ◽  
...  
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Scenario Development ◽  
Environmental Challenges ◽  
Socioeconomic Analysis ◽  
Effective Decision ◽  
Social And Environmental Change ◽  
Effective Decision Making ◽  
Policies And Programs ◽  
The Many

In an increasingly globalized and interconnected world, where social and environmental change occur ever more rapidly, careful futures-oriented thinking becomes crucial for effective decision making. Foresight activities, including scenario development, quantitative modeling, and scenario-guided design of policies and programs, play a key role in exploring options to address socioeconomic and environmental challenges across many sectors and decision-making levels. We take stock of recent methodological developments in scenario and foresight exercises, seek to provide greater clarity on the many diverse approaches employed, and examine their use by decision makers in different fields and at different geographic, administrative, and temporal scales. Experience shows the importance of clearly formulated questions, structured dialog, carefully designed scenarios, sophisticated biophysical and socioeconomic analysis, and iteration as needed to more effectively link the growing scenarios and foresight community with today's decision makers and to better address the social, economic, and environmental challenges of tomorrow.

scholarly journals Decision-Making Enhancement in a Big Data Environment: Application of the K-Means Algorithm to Mixed Data

2019 ◽  
Vol 9 (4) ◽  
pp. 293-302
Author(s):  
Oded Koren ◽  
Carina Antonia Hallin ◽  
Nir Perel ◽  
Dror Bendet
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Mixed Data ◽  
Systems Research ◽  
Information Systems Research ◽  
Effective Decision ◽  
Data Ecosystem ◽  
Effective Decision Making ◽  
Business Requirements

Abstract Big data research has become an important discipline in information systems research. However, the flood of data being generated on the Internet is increasingly unstructured and non-numeric in the form of images and texts. Thus, research indicates that there is an increasing need to develop more efficient algorithms for treating mixed data in big data for effective decision making. In this paper, we apply the classical K-means algorithm to both numeric and categorical attributes in big data platforms. We first present an algorithm that handles the problem of mixed data. We then use big data platforms to implement the algorithm, demonstrating its functionalities by applying the algorithm in a detailed case study. This provides us with a solid basis for performing more targeted profiling for decision making and research using big data. Consequently, the decision makers will be able to treat mixed data, numerical and categorical data, to explain and predict phenomena in the big data ecosystem. Our research includes a detailed end-to-end case study that presents an implementation of the suggested procedure. This demonstrates its capabilities and the advantages that allow it to improve the decision-making process by targeting organizations’ business requirements to a specific cluster[s]/profiles[s] based on the enhancement outcomes.

Integration of Fuzzy Logic Techniques into DSS for Profitability Quantification in a Manufacturing Environment

2012 ◽  
pp. 242-261 ◽  
Author(s):  
Irraivan Elamvazuthi ◽  
Pandian Vasant ◽  
Timothy Ganesan
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Production Control ◽  
Future Research ◽  
Manufacturing Environment ◽  
Planning And Scheduling ◽  
Future Research Directions ◽  
Effective Decision ◽  
Effective Decision Making

Production control, planning, and scheduling are forms of decision making, which play a crucial role in manufacturing industries. In the current competitive environment, effective decision-making has become a necessity for survival in the marketplace. This chapter provides insight into the issues relating to integration of fuzzy logic techniques into decision support systems for profitability quantification in a manufacturing environment. The chapter is divided into five sections with a general introduction of the topic, followed by a thorough literature review on the existing techniques. Thereafter, fuzzy logic algorithms using logistic membership functions and resource variables for decision making aiming at quality improvement are discussed. A case study involving a textile firm is then described with the computational results and findings, and finally, future research directions are presented.

Integration of Fuzzy Logic Techniques into DSS for Profitability Quantification in a Manufacturing Environment

2012 ◽  
pp. 171-192 ◽  
Author(s):  
Irraivan Elamvazuthi ◽  
Pandian Vasant ◽  
Timothy Ganesan
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Production Control ◽  
Future Research ◽  
Manufacturing Environment ◽  
Planning And Scheduling ◽  
Future Research Directions ◽  
Effective Decision ◽  
Effective Decision Making

Production control, planning, and scheduling are forms of decision making, which play a crucial role in manufacturing industries. In the current competitive environment, effective decision-making has become a necessity for survival in the marketplace. This chapter provides insight into the issues relating to integration of fuzzy logic techniques into decision support systems for profitability quantification in a manufacturing environment. The chapter is divided into five sections with a general introduction of the topic, followed by a thorough literature review on the existing techniques. Thereafter, fuzzy logic algorithms using logistic membership functions and resource variables for decision making aiming at quality improvement are discussed. A case study involving a textile firm is then described with the computational results and findings, and finally, future research directions are presented.

scholarly journals Exploring Multicriteria Elicitation Model Based on Pairwise Comparisons: Building an Interactive Preference Adjustment Algorithm

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Giancarllo Ribeiro Vasconcelos ◽  
Caroline Maria de Miranda Mota
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Decision Makers ◽  
Pairwise Comparisons ◽  
Decision Making Process ◽  
Priority Vector ◽  
Effective Decision ◽  
Low Levels ◽  
Effective Decision Making ◽  
Decision Making Tool

Pairwise comparisons have been applied to several real decision making problems. As a result, this method has been recognized as an effective decision making tool by practitioners, experts, and researchers. Although methods based on pairwise comparisons are widespread, decision making problems with many alternatives and criteria may be challenging. This paper presents the results of an experiment used to verify the influence of a high number of preferences comparisons in the inconsistency of the comparisons matrix and identifies the influence of consistencies and inconsistencies in the assessment of the decision-making process. The findings indicate that it is difficult to predict the influence of inconsistencies and that the priority vector may or may not be influenced by low levels of inconsistencies, with a consistency ratio of less than 0.1. Finally, this work presents an interactive preference adjustment algorithm with the aim of reducing the number of pairwise comparisons while capturing effective information from the decision maker to approximate the results of the problem to their preferences. The presented approach ensures the consistency of a comparisons matrix and significantly reduces the time that decision makers need to devote to the pairwise comparisons process. An example application of the interactive preference adjustment algorithm is included.

scholarly journals DECISION MAKING: Sebuah Telaah Awal

2019 ◽  
Vol 2 (2) ◽  
pp. 208
Author(s):  
Ermi Sola
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Effective Decision ◽  
Effective Decision Making ◽  
And Control

AbstractIn general, decision making is a process of choosing alternatives conducted by a certain people in an organization. An accurate decision that solves or answers the problem, needs ...and creativity from the decision makers. The decision makers have to follow any steps of decision making itself. Generally, there many steps in decision making, starting from the clearness of problem it self, develop alternatives, assess the alternatives by determine certain criteria, choose the best alternatives to be a decision, implement it, and control the implementation especially to the decision that is not routine, rarely happens, and special. Judgement, intuition, and creativity is the key to a success and effective decision making.

Decision Making Support Model for the Incident Emergency Management of Migrant’s Group Based on CBR

2014 ◽  
Vol 989-994 ◽  
pp. 1704-1711
Author(s):  
Ding Hua Zhang ◽  
Liang Cheng ◽  
Ren Wei Wu ◽  
Jing Wang ◽  
Jing Yi Liu
Keyword(s):  
Decision Making ◽  
Emergency Management ◽  
Guangdong Province ◽  
Management Problem ◽  
Ahp Model ◽  
Factors Associated ◽  
Effective Decision ◽  
Effective Decision Making ◽  
Support Model

This paper presents the findings of a study on decision making models for the migrant’s worker group incident emergency management based on Analytic Hierarchic Process (AHP). Analytic Hierarchic Process (AHP) helps to quantitate and layer the complex migrant’s worker incident emergency management problem, the aim of the work is to improve the support for analysis and decision through the importance comparing of various factors associated layer by layer.A case study conduct in Wukan village Shantou city of Guangdong province revealed that AHP model can do effective decision making

scholarly journals Stakeholders’ perceptions towards non-native acacias and implications for their management in Portugal

2019 ◽  
Vol 93 (4) ◽  
pp. 557-566 ◽  
Author(s):  
Ana Sofia Vaz ◽  
Joana Ribeiro ◽  
João P Honrado ◽  
Joana R Vicente
Keyword(s):  
Decision Making ◽  
Native Species ◽  
Ecological Impacts ◽  
Decision Makers ◽  
Invasion History ◽  
Management Actions ◽  
Native Trees ◽  
Effective Decision ◽  
Negative Impacts ◽  
Effective Decision Making

Abstract Humans act as drivers for the introduction of non-native trees. Some non-native species may become invasive and cause undesirable impacts, thereby motivating targeted decision-making and management actions. Australian acacias (or wattles; genus Acacia subgenus Phyllodineae) have been introduced worldwide, offering both opportunities and risks for local communities. Understanding how stakeholders perceive invasive acacias is paramount to assist effective decision-making. We assessed stakeholders’ perceptions about these non-native acacias, their invasion process, social-ecological impacts and management. We conducted a questionnaire-based survey with experienced managers and decision-makers in Northern Portugal, where acacia invasions are widespread. We found that most stakeholders are not able to recognize non-native species, failing to identify the introduction period, drivers of dispersion and appropriate management methods of Australian acacias. We could also identify different stakeholder perceptions on the benefits and negative impacts provided by these species. We call for the implementation of technical training and information outreach strategies to address stakeholders’ lack of knowledge (and experience) on the recognition and identification of non-native trees, as well as on their introduction and invasion history, drivers of dispersion, costs and benefits, and effective management actions. Stakeholders’ engagement should be promoted in the design and implementation of biosecurity efforts to control (and/or adapt to) invasive acacias at relevant scales of invasion management.

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