Data Driven Approaches For Effective Managerial Decision Making

Author : Anubha,Sharma, Himanshu
Publisher : IGI Global
Page : 354 pages
File Size : 40,5 Mb
Release : 2023-05-08
Category : Business & Economics
ISBN : 9781668475706

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Data-Driven Approaches for Effective Managerial Decision Making by Anubha,Sharma, Himanshu Pdf

In today’s competitive market, a manager must be able to look at data, understand it, analyze it, and then interpret it to design a smart business strategy. Big data is also a valuable source of information on how customers interact with firms through various mediums such as social media platforms, online reviews, and many more. The applications and uses of business analytics are numerous and must be further studied to ensure they are utilized appropriately. Data-Driven Approaches for Effective Managerial Decision Making investigates management concepts and applications using data analytics and outlines future research directions. The book also addresses contemporary advancements and innovations in the field of management. Covering key topics such as big data, business intelligence, and artificial intelligence, this reference work is ideal for managers, business owners, industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.

Author : Mario Vanhoucke
Publisher : Apress
Page : 164 pages
File Size : 45,5 Mb
Release : 2018-03-27
Category : Business & Economics
ISBN : 9781484234983

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The Data-Driven Project Manager by Mario Vanhoucke Pdf

Discover solutions to common obstacles faced by project managers. Written as a business novel, the book is highly interactive, allowing readers to participate and consider options at each stage of a project. The book is based on years of experience, both through the author's research projects as well as his teaching lectures at business schools. The book tells the story of Emily Reed and her colleagues who are in charge of the management of a new tennis stadium project. The CEO of the company, Jacob Mitchell, is planning to install a new data-driven project management methodology as a decision support tool for all upcoming projects. He challenges Emily and her team to start a journey in exploring project data to fight against unexpected project obstacles. Data-driven project management is known in the academic literature as “dynamic scheduling” or “integrated project management and control.” It is a project management methodology to plan, monitor, and control projects in progress in order to deliver them on time and within budget to the client. Its main focus is on the integration of three crucial aspects, as follows: Baseline Scheduling: Plan the project activities to create a project timetable with time and budget restrictions. Determine start and finish times of each project activity within the activity network and resource constraints. Know the expected timing of the work to be done as well as an expected impact on the project’s time and budget objectives. Schedule Risk Analysis: Analyze the risk of the baseline schedule and its impact on the project’s time and budget. Use Monte Carlo simulations to assess the risk of the baseline schedule and to forecast the impact of time and budget deviations on the project objectives. Project Control: Measure and analyze the project’s performance data and take actions to bring the project on track. Monitor deviations from the expected project progress and control performance in order to facilitate the decision-making process in case corrective actions are needed to bring projects back on track. Both traditional Earned Value Management (EVM) and the novel Earned Schedule (ES) methods are used. What You'll Learn Implement a data-driven project management methodology (also known as "dynamic scheduling") which allows project managers to plan, monitor, and control projects while delivering them on time and within budget Study different project management tools and techniques, such as PERT/CPM, schedule risk analysis (SRA), resource buffering, and earned value management (EVM) Understand the three aspects of dynamic scheduling: baseline scheduling, schedule risk analysis, and project control Who This Book Is For Project managers looking to learn data-driven project management (or "dynamic scheduling") via a novel, demonstrating real-time simulations of how project managers can solve common project obstacles

Author : Harjit Singh
Publisher : FT Press
Page : 412 pages
File Size : 45,7 Mb
Release : 2015-11-12
Category : Business & Economics
ISBN : 9780134190495

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Project Management Analytics by Harjit Singh Pdf

To manage projects, you must not only control schedules and costs: you must also manage growing operational uncertainty. Today’s powerful analytics tools and methods can help you do all of this far more successfully. In Project Management Analytics, Harjit Singh shows how to bring greater evidence-based clarity and rationality to all your key decisions throughout the full project lifecycle. Singh identifies the components and characteristics of a good project decision and shows how to improve decisions by using predictive, prescriptive, statistical, and other methods. You’ll learn how to mitigate risks by identifying meaningful historical patterns and trends; optimize allocation and use of scarce resources within project constraints; automate data-driven decision-making processes based on huge data sets; and effectively handle multiple interrelated decision criteria. Singh also helps you integrate analytics into the project management methods you already use, combining today’s best analytical techniques with proven approaches such as PMI PMBOK® and Lean Six Sigma. Project managers can no longer rely on vague impressions or seat-of-the-pants intuition. Fortunately, you don’t have to. With Project Management Analytics, you can use facts, evidence, and knowledge—and get far better results. Achieve efficient, reliable, consistent, and fact-based project decision-making Systematically bring data and objective analysis to key project decisions Avoid “garbage in, garbage out” Properly collect, store, analyze, and interpret your project-related data Optimize multi-criteria decisions in large group environments Use the Analytic Hierarchy Process (AHP) to improve complex real-world decisions Streamline projects the way you streamline other business processes Leverage data-driven Lean Six Sigma to manage projects more effectively

Author : Simone Gressel,David J. Pauleen,Nazim Taskin
Publisher : SAGE
Page : 354 pages
File Size : 50,5 Mb
Release : 2020-10-12
Category : Business & Economics
ISBN : 9781529738285

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Management Decision-Making, Big Data and Analytics by Simone Gressel,David J. Pauleen,Nazim Taskin Pdf

Accessible and concise, this exciting new textbook examines data analytics from a managerial and organizational perspective and looks at how they can help managers become more effective decision-makers. The book successfully combines theory with practical application, featuring case studies, examples and a ‘critical incidents’ feature that make these topics engaging and relevant for students of business and management. The book features chapters on cutting-edge topics, including: • Big data • Analytics • Managing emerging technologies and decision-making • Managing the ethics, security, privacy and legal aspects of data-driven decision-making The book is accompanied by an Instructor’s Manual, PowerPoint slides and access to journal articles. Suitable for management students studying business analytics and decision-making at undergraduate, postgraduate and MBA levels.

Author : Amar Sahay
Publisher : Unknown
Page : 0 pages
File Size : 54,8 Mb
Release : 2018-08-23
Category : Business & Economics
ISBN : 1637423268

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Business Analytics, Volume I by Amar Sahay Pdf

This book deals with Business Analytics (BA) - an emerging area in modern business decision making. Business analytics is a data driven decision making approach that uses statistical and quantitative analysis along with data mining, management science, and fact-based data to measure past business performance to guide an organization in business planning and effective decision making. Business Analytics tools are also used to predict future business outcomes with the help of forecasting and predictive modeling.In this age of technology, massive amount of data are collected by companies. Successful companies use their data as an asset and use them for competitive advantage. Business Analytics is helping businesses in making informed business decisions and automating and optimizing business processes.Successful business analytics depends on the quality of data. Skilled analysts, who understand the technologies and their business, use business analytics tools as an organizational commitment to data-driven decision making.

Author : Singh, Sonia,Rajest, S. Suman,Hadoussa, Slim,Obaid, Ahmed J.,Regin, R.
Publisher : IGI Global
Page : 515 pages
File Size : 48,9 Mb
Release : 2023-12-21
Category : Business & Economics
ISBN : 9798369321942

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Data-Driven Decision Making for Long-Term Business Success by Singh, Sonia,Rajest, S. Suman,Hadoussa, Slim,Obaid, Ahmed J.,Regin, R. Pdf

In today's academic environment, the challenge of ensuring lasting commercial and economic success for organizations has become more daunting than ever before. The relentless surge in data-driven decision-making, based on innovative technologies such as blockchain, IoT, and AI, has created a digital frontier filled with complexity. Maintaining a healthy firm that can continually provide innovative products and services to the public while fueling economic growth has become a formidable puzzle. Moreover, this digital transformation has ushered in new risks, from pervasive cybersecurity threats to the ethical challenges surrounding artificial intelligence. In this evolving landscape, academic scholars face the pressing challenge of deciphering the path to long-term organizational prosperity in an era dominated by data. Data-Driven Decision Making for Long-Term Business Success serves as guidance and insights amidst this academic challenge. It is the definitive solution for scholars seeking to uncover the complexities of data-driven decision-making and its profound impact on organizational success. Each meticulously curated chapter delves into a specific facet of this transformative journey, from the implications of modern technologies and pricing optimization to the ethics underpinning data-driven strategies and the metaverse's influence on decision-making.

Author : Jenny Dearborn,David Swanson
Publisher : John Wiley & Sons
Page : 272 pages
File Size : 52,6 Mb
Release : 2017-11-06
Category : Business & Economics
ISBN : 9781119382201

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The Data Driven Leader by Jenny Dearborn,David Swanson Pdf

Data is your most valuable leadership asset—here's how to use it The Data Driven Leader presents a clear, accessible guide to solving important leadership challenges through human resources-focused and other data analytics. This engaging book shows you how to transform the HR function and overall organizational effectiveness by using data to make decisions grounded in facts vs. opinions, identify root causes behind your company’s thorniest problems and move toward a winning, future-focused business strategy. Realistic and actionable, this book tells the story of a successful sales executive who, after leading an analytics-driven turnaround (in Data Driven, this book’s predecessor), faces a new turnaround challenge as chief human resources officer. Each chapter features insightful commentary and practical notes on the points the story raises, guiding you to put HR analytics into action in your organization. HR and other leaders cannot afford to overlook the power and competitive advantages of data-driven decision-making and strategies. This book reflects the growing trend of CEOs choosing analytics-minded business leaders to head HR, at a time when workplaces everywhere face game-changing forces including automation, robotics and artificial intelligence. It is urgent that human resources leaders embrace analytics, not only to remain professionally relevant but also to help their organizations successfully navigate this digital transformation. HR professionals can and must: Understand essential data science principles and corporate analytics models Identify and execute effective data analytics initiatives Boost HR and company productivity and performance with metrics that matter Shape an analytics-centric culture that generates data driven leaders Most organizations capture and report data, but data is useless without analysis that leads to action. The Data Driven Leader shows you how to use this tremendous asset to lead your organization higher.

Author : Anthony G. Picciano
Publisher : Prentice Hall
Page : 260 pages
File Size : 53,6 Mb
Release : 2006
Category : Education
ISBN : UVA:X004903184

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Data-driven Decision Making for Effective School Leadership by Anthony G. Picciano Pdf

Brief ContentsPrefacePrologue Concepts and Foundations of Data-Driven Decision Making Introduction to Data-Driven Decision Making Planning and Developing Information Resources Hardware, Software, and People Educational Research Methods and Tools Teachers and Administrators as Researchers Basic Applications Student Data, Demographics, and Enrollments School and the Community Financial Management and Budgeting Supporting Teaching and Learning Supporting Teachers and Their Professional Development Technical Support Review of Statistical Routines Used in this Book Introduction to Spreadsheet Software Introduction to the Statistical Package for the Social Sciences (SPSS) Database Management Terms and Sample Outline Internet Resources for Data-Driven Decision MakingGlossaryIndex Contents PrefacePrologue Concepts and Foundations of Data-Driven Decision Making Introduction to Data-Driven Decision Making Rationale for Adopting Data-Driven Decision Making Purpose of This Book Defining Data-Driven Decision Making An Old Idea: Knowledge Is Power Need for Planning The Systems Approach Organization of This Book SummaryReferences Planning and Developing Information Resources School Districts Take the Lead Defining Information Needs Database Management Systems Long-Term and Short-Term Data Resources SummaryCase StudyReferences Hardware, Software, and People A Brief Look at Infrastructure Hardware for Effective Data Management and Access Client-Server Architecture Software for Data Analysis Developing People Resources The Data Analyst SummaryCase StudyReferences Educational Research Methods and Tools The Scientific Method and Educational Research Educational Research Methods Ethnographic Research Historical Research Descriptive Research Correlational Research Causal Comparative Research Experimental Research Action Research Data Collection Tools Direct Observation Structured Interviews Document Analysis Surveys Test Instruments SummaryCase StudyReferences Teachers and Administrators as Researchers Learning Communities Action Research in Action Trial Testing a Peer Tutoring Program Multiple Intelligences in a Foreign Language Program Advancing to an Inclusion Program SummaryActivitiesReferences Basic Applications Student Data, Demographics, and Enrollments Student Data Enrollment Projections at the District Level Attendance Zones and Individual Schools Taking a Census Special Student Populations SummaryActivitiesReferences School and the Community Partnering with the Community: Broad-Based Surveys Anatomy of a Survey Who Will Participate in the Survey? What Data Will Be Collected? Data Analysis Is the Sample Representative of the High School Population? Do Students Have Access to the Internet? The Committee's Next Steps SummaryActivitiesReferences Financial Management and Budgeting Basic Terminology School District Budget School Budget The Canton Alternative School Budget Emergency SummaryActivitiesReferences Supporting Teaching and Learning States, Cities, Districts, Schools, Classes, Teachers, Students Improving Teaching and Learning Jefferson Middle School Developing a Plan Information Overload: A Caution SummaryActivitiesReferences Supporting Teachers and Their Professional Development Summative and Formative Evaluation Collecting Personnel Data Kingsland School District Case Study Keeping Track of Professional Development SummaryActivitiesReferences Technical Support Review of Statistical Routines Used in this Book Key Terms Descriptive Statistical Procedures Frequency Distributions Contingency Tables (Crosstabulations) Measures of Central Tendency Measures of Dispersion Measures of Relationship Correlational Coefficient Linear Regression Caution Introduction to Spreadsheet Software Overview and Key Terms Spreadsheet Structure Data Types and Data Manipulation Charts and Graphics Introduction to the Statistical Package for the Social Sciences (SPSS) Overview The Data Editor Creating a Data Set Defining Variables Transforming Data Options Data Analysis Procedures and the Output Viewer Graphs and Charts Database Management Terms and Sample Outline Internet Resources for Data-Driven Decision MakingGlossaryIndex.

Author : Barbosa, Belem
Publisher : IGI Global
Page : 413 pages
File Size : 48,9 Mb
Release : 2024-02-19
Category : Business & Economics
ISBN : 9798369312322

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Contemporary Trends in Innovative Marketing Strategies by Barbosa, Belem Pdf

In global commerce, marked by the relentless advance of digital technology, businesses find themselves constantly challenged to devise innovative and disruptive marketing strategies. Adapting to these changes is no longer a choice but a necessity. To thrive, companies must remain vigilant, updating their resources and adopting emerging trends with unwavering agility. Contemporary Trends in Innovative Marketing Strategies explores the demands and dynamics of modern marketing. This book is tailored to meet the needs of students, educators, and managers seeking a profound understanding of today's marketing trends. Firstly, the book delves deep into the current trends steering marketing innovation. It dissects the latest developments that are reshaping the marketing landscape, identifies pivotal trends, and elucidates their ramifications for businesses. Secondly, the book embarks on a journey to explore innovative marketing strategies engineered to confront contemporary business challenges and seize emerging opportunities. It unlocks novel approaches that adeptly cater to the market, providing insights into strategic frameworks, methodologies, and practices. Lastly, the book illustrates these concepts with real-world case studies, offering proof of innovative marketing's successful applications across diverse business sectors. These cases serve to inspire and demonstrate how innovative marketing strategies can be put into action, resulting in tangible outcomes. This book is designed for a diverse audience, including academics and students keen on exploring the latest trends in innovative marketing, educators searching for compelling case studies to enhance their teaching materials, and practitioners eager to bridge the gap between research and practical application in innovative marketing.

Author : Parul Gandhi,Surbhi Bhatia,Kapal Dev
Publisher : CRC Press
Page : 150 pages
File Size : 53,6 Mb
Release : 2021-12-21
Category : Computers
ISBN : 9781000506433

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Data Driven Decision Making using Analytics by Parul Gandhi,Surbhi Bhatia,Kapal Dev Pdf

This book aims to explain Data Analytics towards decision making in terms of models and algorithms, theoretical concepts, applications, experiments in relevant domains or focused on specific issues. It explores the concepts of database technology, machine learning, knowledge-based system, high performance computing, information retrieval, finding patterns hidden in large datasets and data visualization. Also, it presents various paradigms including pattern mining, clustering, classification, and data analysis. Overall aim is to provide technical solutions in the field of data analytics and data mining. Features: Covers descriptive statistics with respect to predictive analytics and business analytics. Discusses different data analytics platforms for real-time applications. Explain SMART business models. Includes algorithms in data sciences alongwith automated methods and models. Explores varied challenges encountered by researchers and businesses in the realm of real-time analytics. This book aims at researchers and graduate students in data analytics, data sciences, data mining, and signal processing.

Author : Harjit Singh
Publisher : Unknown
Page : 128 pages
File Size : 44,9 Mb
Release : 2016
Category : Data mining
ISBN : 0134190505

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Project Management Analytics by Harjit Singh Pdf

Author : Ajibesin, Adeyemi Abel,Vajjhala, Narasimha Rao
Publisher : IGI Global
Page : 413 pages
File Size : 52,9 Mb
Release : 2024-01-16
Category : Computers
ISBN : 9798369302576

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Data Envelopment Analysis (DEA) Methods for Maximizing Efficiency by Ajibesin, Adeyemi Abel,Vajjhala, Narasimha Rao Pdf

In today's highly competitive and rapidly evolving global landscape, the quest for efficiency has become a crucial factor in determining the success of organizations across various industries. Data Envelopment Analysis (DEA) Methods for Maximizing Efficiency is a comprehensive guide that delves into the powerful mathematical tool of DEA, is designed to assess the relative efficiency of decision-making units (DMUs), and provides valuable insights for performance improvement. This book presents a systematic overview of DEA models and techniques, from fundamental concepts to advanced methods, showcasing their practical applications through real-world examples and case studies. Catering to a broad audience, this book is designed for students, researchers, consultants, decision-makers, and enthusiasts in the field of efficiency analysis and performance measurement. Consultants and practitioners will gain practical insights for applying DEA in various contexts, and decision-makers will be equipped to make informed decisions for maximizing efficiency. Additionally, individuals with a general interest in data analysis and performance measurement will find this book accessible and informative. This book covers a wide range of topics, including mathematical foundations of DEA, DEA models and variations, DEA efficiency and productivity measures, DEA applications in various industries such as healthcare, finance, supply chain management, environmental management, education management, and public sector management.

Author : Kim Schildkamp,Mei Kuin Lai,Lorna Earl
Publisher : Springer Science & Business Media
Page : 221 pages
File Size : 52,8 Mb
Release : 2012-09-18
Category : Education
ISBN : 9789400748156

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Data-based Decision Making in Education by Kim Schildkamp,Mei Kuin Lai,Lorna Earl Pdf

In a context where schools are held more and more accountable for the education they provide, data-based decision making has become increasingly important. This book brings together scholars from several countries to examine data-based decision making. Data-based decision making in this book refers to making decisions based on a broad range of evidence, such as scores on students’ assessments, classroom observations etc. This book supports policy-makers, people working with schools, researchers and school leaders and teachers in the use of data, by bringing together the current research conducted on data use across multiple countries into a single volume. Some of these studies are ‘best practice’ studies, where effective data use has led to improvements in student learning. Others provide insight into challenges in both policy and practice environments. Each of them draws on research and literature in the field.

Author : Bansal, Rohit,Ngah, Abdul Hafaz,Chakir, Aziza,Pruthi, Nishita
Publisher : IGI Global
Page : 370 pages
File Size : 44,5 Mb
Release : 2024-01-24
Category : Business & Economics
ISBN : 9798369308165

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Leveraging ChatGPT and Artificial Intelligence for Effective Customer Engagement by Bansal, Rohit,Ngah, Abdul Hafaz,Chakir, Aziza,Pruthi, Nishita Pdf

Academic scholars find themselves confronted with a formidable challenge: staying abreast of the ever-evolving landscape of Artificial Intelligence(AI). The intricate interplay between AI and its profound impact on various facets of society, including customer engagement, remains an enigma for many. This knowledge gap not only hampers their ability to contribute meaningfully to their fields but also leaves them trailing behind the dynamic developments taking place in industries worldwide. As AI continues to reshape the business environment, it becomes imperative for academia to bridge this chasm between theory and practice. Leveraging ChatGPT and Artificial Intelligence for Effective Customer Engagement is an effective solution to the pressing problem at hand. With meticulous clarity, it unravels the complexities of ChatGPT, an innovative AI technology, and its revolutionary potential in the realm of customer engagement. It offers a lifeline to academic scholars seeking to navigate the uncharted territory of AI, providing them with an in-depth understanding of how ChatGPT can reshape customer interactions.

Author : Russ, Meir
Publisher : IGI Global
Page : 390 pages
File Size : 48,7 Mb
Release : 2023-06-26
Category : Business & Economics
ISBN : 9781668458617

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Cases on Enhancing Business Sustainability Through Knowledge Management Systems by Russ, Meir Pdf

Artificial intelligence (AI) is becoming a reality for pioneering organizations while they are facing complex and multifaceted aspects of business sustainability with ambiguous and changing ethical norms and vague or nonexistent legislation. The first quarter of the 21st century was identified as the beginning of the continuous, ongoing, and accelerating wave of simultaneous general purpose technologies revolutions causing accelerated shrinkage of the half-life of knowledge. Cases on Enhancing Business Sustainability Through Knowledge Management Systems presents teaching case studies exploring the formulation and implementation of knowledge management systems (KMS) in organizations. Covering topics such as automation, machine learning, and socio-ecological innovation, this case book is an essential resource for business leaders and managers, IT managers, entrepreneurs, government officials, computer scientists, students and educators of higher education, librarians, researchers, and academicians.