Defining and Identifying a Research Agenda for Evidence Based Management Framework- Tutorsindia.com

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DEFINING AND IDENTIFYING A RESEARCH AGENDA FOR AN EVIDENCE BASED MANAGEMENT FRAMEWORK An Academic presentation by Dr. Nancy Agens, Head, Technical Operations, Tutors India Group www.tutorsindia.com Email: [email protected] BUSINESS ANALYTICS DISSERTATION HELP:

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Transcript of Defining and Identifying a Research Agenda for Evidence Based Management Framework- Tutorsindia.com

Page 1: Defining and Identifying a Research Agenda for Evidence Based Management Framework- Tutorsindia.com

DEFINING AND IDENTIFYING A RESEARCH AGENDA FOR AN EVIDENCE BASED MANAGEMENT FRAMEWORKAn Academic presentation byDr. Nancy Agens, Head, Technical Operations, Tutors India Group www.tutorsindia.comEmail: [email protected]

BUSINESS ANALYTICS DISSERTATION HELP:

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In Brief Introduction Business AnalyticsCategories of Business AnalyticsCreating an Evidence-based Management Framework Decision Support Systems (DSS)Six A's Conclusion

OUTLINE

Today's Discussion

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In BriefYou will find the best dissertation research areas/topics for future researchers

enrolled in Engineering and Technology. In order to identify future research topics, we have reviewed the technical conventions. (recent peer-reviewed studies).

Business analytics refers to the systematic use of data collected from a variety of sources, quantitative and statistical analysis, predictive and explanatory models and evidence-based management to direct actions and decisions towards the

appropriate stakeholders. Writing a business analytics dissertations, it is important for the researchers to have strong knowledge related to the approaches

used and in the data science and machine learning which will help in writing business analytics dissertation.

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Introduction

Organizations employ business analytics to make intelligent decisions, which can be made quicker and better in order to enhance the value of the business.

Until today, academicians and industrialists have focused mainly on descriptive and predictive analytics.

Prescriptive analytics is gaining huge interest in terms of research in the business analytics area as it is considered as the best course of action for future businesses.

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Business analytics refers to the systematic use of data collected from a variety of sources, quantitative and statistical analysis, predictive and explanatory models and evidence-based management to direct actions and decisions towards the appropriate stakeholders.

Business analytics incorporates the use of approaches such as data science, operational research, machine learning and information systems fields.

Business analytics deal not only with descriptive models but also with models that can offer valuable insights and support business performance decisions.

To this end, business analysis has developed beyond a simple raw data analysis on large datasets with the goal of creating a competitive advantage for organizations.

Business Analytics

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(i) Descriptive analytics, answering the questions “What has happened?”, “Why did it happen?”, but also “What is happening now?”;

(ii) Predictive analytics, answering the questions “What will happen?” and “Why will it happen?” in the future;

(iii)Prescriptive analytics, answering the questions “What should I do?” and “Why should I do it?”.

While writing a business analytics dissertations, it is important for the researchers to have strong knowledge related to the approaches used and in the data science and machine learning.

Categories of Business Analytics

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An Evidence-Based Management (EBMgt) methodology addresses highly important business issues using effective methodologies and implementations.

EBMgt is a data and theory-driven approach to decision-making, arguing that while managers cannot have full knowledge in ever-changing environments, the consistency of decisions is usually enhanced by taking data-driven facts into consideration.

Creatingan Evidence- based Management Framework

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The classical concept of decision support systems (DSS) is a computer-based information system leveraging data and/or models to support decision-makers solve semi-structured or unstructured problems.

The classical what-if analysis of DSS is to take a question, apply a data-driven model to evaluate an outcome and compare that outcome with alternative interventions.

This concept of data-driven decision making is an integral part of the Business Analytics System (BAF) of Holsapple, Lee-Post and Pakath.

DSS research has lasted for almost half a century, but interest in DSS techniques, methods, and implementation has recently increased.

Contd..

Decision Support Systems (DSS)

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Fig 1. Four Elements of EBMgt

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1. Asking: transforming a real-world problem into an answerable question.

2. Acquiring: the systematic search and gathering of proof.

3. Appraising: to objectively evaluate the quality and validity of the evidence.

4. Aggregating: weighing proof and putting it all together.

5. Applying: Inclusion of evidence in the process of decision-making.

6. Assessing: Evaluation of the outcomes of the decision adopted.

Six A's

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