Syllabus for
Bachelor of Business Administration (Decision Science)
Academic Year  (2023)

Financial Management is an introductory core course that is offered with the intent to equip the students with the basic knowledge of finance theory and its application to develop relevant financial strategies pertinent to profit-seeking organisations. The theme of financial management is structured around three decision-making financial areas: Investment- long term as well as working capital, Financing and Dividend policy. This imbibes students with analytical and decision-making skills in managing finance through the application of theoretical questions and practical problems.

Course Objectives:

CO1: To understand the basics of the finance function and the concepts of financial management

CO2: To apply the knowledge in financial decisions

CO3: To develop analytical skills to identify financial management problems and solve them.

CO4: To analyse the relationship among capital structure, cost of capital, dividend decisions, and value of the business.

CO5: To assess a firm’s requirement for long-term assets by applying capital budgeting techniques.

Meaning of finance and financial management, Types of finance – public and private finance , classification of private finance – personal finance, business finance and finance of non-profit organization Importance and Scope of financial management, Approaches to finance function Relationship of finance with other business functions, Objectives of financial management – profit maximization and wealth maximization - merits and criticisms Financial decisions, Internal relation of financial decisions, Factors influencing financial decisions Functional areas of financial management, Functions of a finance manager.

Ownership securities – Equity shares, Preference shares, Deferred shares, No par stock/shares, Shares with differential rights, Sweat Equity Creditorship securities – Debentures – Zero coupon bonds, Callable bonds, Deep discount bonds Internal financing or ploughing back of profit – factors affecting ploughing back of profits – merits and demerits Loan financing – short term and long term sources. Meaning of capitalization – Theories of capitalization – cost theory and earnings theory. Over capitalization and under capitalization – causes – effects and remedies, Watered stock, Over trading and under trading

Meaning of capital structure and financial structure, principles of capital structure, optimum capital structure, determinants of capital structure, theories of capital structure and EPS – practical problems. Point of indifference, capital gearing

Meaning of cost of capital, significance of cost of capital, components of cost of capital – computation of cost of capital and Weighted Average Cost of Capital – practical problems. Meaning of leverage, types of leverages – operating, financial and combined leverage, risk and leverage – practical problems

Meaning of capital budgeting, Importance, Need, Time value of money (using Table Value), capital budgeting process, project appraisal by using traditional methods and modern methods Practical problems on payback period, Accounting rate of return, NPV method , Profitability index, IRR methods

Meaning, Kinds, Bonus shares – merits and demerits, theories of dividend decisions, determinants of dividend policy decisions. (Theory only)

Meaning of working capital, types of working capital, working capital cycle, adequate working capital, determinants of working capital, estimation of working capital. Management of cash –practical problems. Management of inventory and debtors – theory only.

Course Description: Human Resource Management course provides an overview of the HR function covering the entire gamut of operations related to the employee life cycle management. The course focuses on providing the basic understanding of HR processes and practices followed in a business organisation. It orient learners towards understanding of various HR functions such as recruitment and selection, training and development, performance management system, compensation management, contemporary issues and trends in human resource management.The course meets the national and local context of people management and enables students to have a global perspective on Human resource management practices

Course Objectives:

• To develop understanding of conceptual foundations of HRM
• To understand the processes and practices in HR functions
• To explain important labour laws and its implications
• To identify contemporary trends and challenges in the field of HRM
• To assess the application of appropriate HR intervention in conjunction with organization need.

Concept of HRM, Evolution of HRM, Role of Human Resource Manager, Functions of HRM, HR Structure and Concept of Strategic HRM.

Concept of Job Analysis, Importance and Benefits of Job Analysis, Job Analysis Process, Job Description, Job Specification and other Job-related concepts- Job Enrichment, Job Enlargement, Job Rotation, Flexi timing, Telecommuting and Ergonomics.     

Concept & Importance of HRP; Different stages of HR Planning Process; Action Plans in case of shortage and surplus of the workforce.

Concept of Recruitment, Factors affecting Recruitments, Sources of Recruitment; Definition and Importance of Selection, Stages involved in Selection Process, Types of Selection Tests and Types of Interviews. Meaning and Benefits of Induction, Content of an Induction Program

Meaning and Importance of Training and Development Programs, Stages involved in Training Process, On-the-Job and Off-the-Job Training & Development Methods. Career Management Process, Models of Career Management, Role & Challenges of Career Development, Career Development Initiatives, Stages in Career Planning, Internal and External Mobility of Employees.

Meaning of Industrial Relations, Theories of IR, Meaning and Sources of Employee Grievance, Grievance Handling Systems, Meaning & Process of Collective Bargaining, Indiscipline, Settlement Machinery of Industrial Conflicts. Labour laws related to social security measures

Gig workers, Work from home, Ethical Issues in HRM, E-HRM, Introduction to International HRM

CIA 2 – 50 Marks

CIA 3 – 20 Marks

ESE – 50 Marks 

Marketing is a particularly stimulating subject for learners since its practical application is visible every day. Old rules of marketing are no longer useful to those who want to influence these new consumers’ choices. This course will lead the exploration of the leading edge of this paradigm shift that is now underway. This course introduces students to the concepts and processes of marketing and takes them deeper into the world of marketing.

Meaning Definition marketing, scope of marketing, core marketing concepts, Delivering and Creating Customer Value. Marketing Ecosystem- contemporary roles and responsibilities of marketing managers.

Consumer behavior model (Black box) Factors affecting consumer Behavior, Types of Buying Decision Behavior, The Buyer Decision Process, Business Buyer Behavior, The Business Buyer Decision Process, Institutional and Government Market. Segmentation, targeting and positioning for competitive advantage.

Product Levels, Product Characteristics and Classifications, New product development stages, categories of new product, reasons for launching new products and its failure. Product life cycle strategies and its extension, Ansoff’s Matrix, meaning of services, unique characteristics of services, 7Ps of service marketing, Service delivery process

Pricing consideration and approaches, Types of pricing, Methods, Pricing strategies: new product pricing strategies, Product mix pricing strategies, Price adjustment strategies.

Marketing channels, structure, types and criteria of selecting a channel, wholesaling, retailing, and physical distribution, Channel Management channel (Channel design, channel conflict)

Significance of Integrated Marketing Communication, Advertising, sales promotion, personal selling, and sales management.  Public and customer relations, direct and online marketing, multilevel marketing-the new marketing model. Others promotional strategies (Buzz Marketing, Stealth Marketing, Guerrilla Marketing)

Sustainable Marketing, Social Criticisms of Marketing, Marketing’s Impact on Individual, Marketing’s Impact on Society as a Whole, Marketing’s Impact on Other Businesses, Actions to Promote Sustainable Marketing, Principles and Marketing Ethics

Course‌ ‌Description‌:

 ‌

This course is designed to give the students a stage to apply and understand all the concepts taught in Beginner Data Science, Data Engineering & Decision Science. It will help in providing the students with real world industry exposure by guiding them to solve real world problems that Mu Sigma has historically dealt with.

Course Objectives:

The objective of the course is:

1. To understand why simply solving problems is not enough and elaborate the art of problem solving
2. Understand how solving specific problems and the art of problem solving can co-exist harmoniously in the larger realm of problem solving
3. Understand the tenets of the Art of Problem-Solving framework
4. Understand the frameworks to analyse an industry vertical

Understand problems pertaining to specific industries

Problem Space II will occur once the students are familiar with the design thinking concepts in Decision Science topics. It will be a classroom activity on the problems given by the trainer. This subject will be covered during the second part of the semester.

Students will be taught:

1. To develop an understanding of Promotion & campaign management in general
2. Examples of real-life applications of Promotion & campaign management& its impact
3. Techniques to arrive at a solution, their uses & application
4. How to work on an exercise on Promotion & campaign management

Output expected from students:                                                                                                          

1. Create an Empathy Map, Org Chart and a Vertical writeup on the Industry and the business in question
2. Access the problem statement using Design Thinking
3. Break down the problem statement using Problem Definition & Design
4. Arrive at a solution thinking on the lines of Transformation Roadmap                                                                                                              
5. Submit a Jupyter Notebook with the solution

Mu Sigma internal documents and case studies

Mu Sigma internal documents and case studies

Course‌ ‌Description‌: ‌ ‌ ‌

This course covers HTML which provides the basic structure of sites, which is enhanced and modified by other technologies like CSS and JavaScript. CSS is used to control presentation, formatting, and layout. JavaScript is used to control the behavior of different elements. The course also includes Node.js which is an open-source, cross-platform, back-end JavaScript runtime environment that executes JavaScript code outside a web browser. Node.js allows the developers to use JavaScript to write command line tools and for server-side scripting. 

Course Objectives:

The objective of the course is to:

1. Understand the structure of web content and how it is created
2. Learn the basics of HTML
3. Learn the basics of CSS and JavaScript
4. Learn the Node.js framework for developing web applications

Understand the interactions between Node.js applications and various database systems

‌Beginner's guide, tags, elements and attributes, tables, lists and blocks, formatting and image, links, frames and background, multimedia, HTML semantics, storage

Beginner's guide, page design, textual formatting, embedding links and images, tables and dimensions, media queries, CSS grid, flexboxes

Introduction to JS, JavaScript variable, JavaScript data type, JavaScript array methods, For, While and Do-While loops in JavaScript, JavaScript conditional statements, JavaScript Define and Call functions, cookies in JavaScript, JavaScript DOM, Object Oriented JavaScript (OOJS), internal and external JavaScript, call-backs, promises, Async, Await, ES6 introduction.

‌Introduction to Node.js, Node.js module system, file system and command line Args, debugging Node.js, asynchronous Node basic

Creating a web server, accessing API from browser, deployment of web application, MongoDB and promises, Mongoose and Rest API, API authentication and security                                                        

1. Duckett, J (2011). HTML and CSS: Design and Build Websites. Wiley
2. Duckett, J (2014). JavaScript and jQuery: Interactive Front-end Development. Wiley
3. Robbins, J, N (2016). Learning Web Design: A Beginner’s Guide to HTML, CSS, JavaScript, and Web Graphics. O’Reilly
4. Kiessling, M (2011). The Node Beginner Book. Leanpub
5. Kiessling, M (2017). The Node Craftsman Book. Packt Publishing
6. Dayley, B (2018). Node.js, MongoDB, and AngularJS Web Development (2^nd Edition). Addison-Wesley

1. Duckett, J (2011). HTML and CSS: Design and Build Websites. Wiley
2. Duckett, J (2014). JavaScript and jQuery: Interactive Front-end Development. Wiley
3. Robbins, J, N (2016). Learning Web Design: A Beginner’s Guide to HTML, CSS, JavaScript, and Web Graphics. O’Reilly
4. Kiessling, M (2011). The Node Beginner Book. Leanpub
5. Kiessling, M (2017). The Node Craftsman Book. Packt Publishing
6. Dayley, B (2018). Node.js, MongoDB, and AngularJS Web Development (2^nd Edition). Addison-Wesley

1. Duckett, J (2011). HTML and CSS: Design and Build Websites. Wiley
2. Duckett, J (2014). JavaScript and jQuery: Interactive Front-end Development. Wiley
3. Robbins, J, N (2016). Learning Web Design: A Beginner’s Guide to HTML, CSS, JavaScript, and Web Graphics. O’Reilly
4. Kiessling, M (2011). The Node Beginner Book. Leanpub
5. Kiessling, M (2017). The Node Craftsman Book. Packt Publishing
6. Dayley, B (2018). Node.js, MongoDB, and AngularJS Web Development (2^nd Edition). Addison-Wesley

Course‌ ‌Description‌: ‌ ‌ ‌

The Course gives an introduction and dwells in-depth into the working and functions of Data Science. Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. The course also covers the application of analytics in various industries.

Course Objectives:

The objective of the course is to:

1. Familiarize in working with the Python workspace
2. Understand the basic functionality of Python and to be able to write structured code
3. Familiarize with specific data science libraries and packages
4. Become familiar with how the Retail & Insurance industries works

Understand how the Healthcare & Pharmaceutical industries work

Concepts and motivation: What is programming, programming paradigms (procedural, object oriented, functional), compiled vs. interpreted languages, popular IDEs (IDLE, Spyder, IPython/Jupyter, Komodo), Print statement, variables in Python, lists and sets, functions and function calls, conditional statements, iterative statements, BREAK and CONTINUE, classes and objects, importing libraries, importing your own code, installing a new package using PIP, memory management by the Python virtual machine

NumPy, SciPy, Pandas, Scikit-Learn, Nltk, Matplotlib, Bokeh, connecting to data sources and fetching data, reading datasets of various types and storing in relevant structures, reading and writing files of any time, DICT data structure, JSON, list comprehensions and its use, string manipulation, text cleansing, date-time handling

Histograms, bar-plot, scatter plots, line plots, pie-charts, box-whisker plots, using gg plot to improve aesthetics, EDA using Python

Fundamentals of the insurance industry: Entities in the insurance industry, insurance products – home, health, life, vehicle, disaster, group insurance, commercial insurance; regulations in the insurance industry – difference across countries, reinsurance

Overview of Strategic Retail Management and Situation Analysis: An introduction to retailing, building and sustaining relationships in retailing, strategic planning in retailing, retail Institutions by ownership, retail institutions by store-based strategy, web, non-store-based and other forms of non-traditional retailing

Fundamentals of pharmaceuticals and pharmacy retail R&D – drug development and trials, product launches, regulatory compliance, pharmacy retail – in-pharmacy marketing, pharmacy services, filling process and prescriptions, customer outreach and retention

Fundamentals of the healthcare industry, healthcare ecosystem and various entities – manufacturers, PBMs, KOLs, retailers, insurers, hospitals, patients and doctors, interactions between these entities, difference in healthcare ecosystem across countries, healthcare regulation across countries

1. McKinney, W. Python for Data Analysis (2^nd edition). O’Reilly Media

2. Mu Sigma Internal Training Documents

Mu Sigma Case studies

1. McKinney, W. Python for Data Analysis (2^nd edition). O’Reilly Media

2. Mu Sigma Internal Training Documents

Mu Sigma Case studies

Course‌ ‌Description‌:

The course covers Power BI – How it is used for making better business decisions. Students will learn how to fetch relevant information from the data in a lucid manner. Microsoft Power BI suite is designed to quickly turn the data into useful information. The course also looks to incorporate the muOBI tenet of the Art of Problem-Solving framework of Mu Sigma. The course will also help in understanding the client environment and the steps to complete work using Business Process Flow & Client Context. It also entails to teach the art of dashboarding & deck making

Course Objectives:

The objective of the course is:

1. To prepare the data, data discovery, interactive dashboards, and rich visualizations in one solution
2. Students will learn an intuitive tool for interacting with data and turning it into insights more easily
3. They will understand the tenets of the art of problem-solving framework
4. They will discover why standardizing business process flows is important and valuable to an organization

They will understand customer context and understand dashboarding and deck-making

What is Power BI, why is it important, processes in Power BI, starting with Power BI, connecting data sciences, data transformations, introduction to DAX

Charts, maps, gauge, data card, slicers, tables & matrices, using related functions, optimizing data models, waterfall charts, funnels, tree map, decomposition tree, formatting, conditional formatting

What is muOBI, planning for outcomes, planning for transformation, harmonizing top-down planning and bottom-up execution, how to traverse the muOBI. (Examples of muOBI)

Steps to create a Business Process Flow (BPF), steps to create client context

Best practices to storyboard, make decks and apply them in presentations, introduction to dashboarding, nuances of dashboarding, gauging dashboard requirements

1.      Powell, B (2018). Mastering Microsoft Power BI: Expert techniques for effective data analytics and business intelligence, Packt

2. Mu Sigma internal documents

1.      Powell, B (2018). Mastering Microsoft Power BI: Expert techniques for effective data analytics and business intelligence, Packt

2. Mu Sigma internal documents

This course covers the fundamental concepts and various aspects in and of cost as well as management accounting. This course discusses how to prepare cost sheet, costing for materials, labour cost and overheads. This course also talks about financial statement analysis using various tools like comparative and common size Income Statements and Balance Sheet, Trend Analysis, Ratio Analysis, Cash Flow Statement, Budgets and Budgetary Control. It also throws some light on Management Reporting in general. And thus this course as a part of Business administration programme provides fundamental knowledge and basic understanding on various methods, tools and techniques of cost and management accounting helpful for financial decision making required for a budding professional in the domain of accounting and finance.

·       To familiarize the learners with the basic concepts and processes used to determine product costs.

·        To make known the students in ascertaining Material, Labour and Overhead cost

·       To enrich the knowledge of the learners in knowing and applying various tools like ratio analyis, cash flow statemet, marginal costing for analysing the financial statements for managerial information

·       To provide with the basic understanding of budgetary control

Definitions, features, objectives, functions, scope, advantages and limitations. Relationship and differences between Cost accounting, Management accounting and Financial accounting.  Cost Concepts-Cost classification – Elements of cost - Preparation of cost sheet and quotation

Material Cost: direct and indirect material cost, Inventory control techniques-stock levels, EOQ, ABC analysis. Issue of materials to production- pricing methods-FIFO, LIFO and Average methods

Labor cost: direct and indirect labour cost-methods of payment of wages including incentive plans -Halsey and Rowan plans, Taylor's Piece Rate method.

Overheads: features, classification, methods of allocation and apportionment of overheads, primary and secondary distributions (Repeated & step ladder method only)

Meaning - Importance - Marginal Cost Equation - Difference between Marginal costing and Absorption costing - Applications of Marginal costing

Meaning and importance - Types of Budgets, practical problems- Flexible Budget  and cash Budget

Comparative Income Statements and Balance Sheets, Common size Income Statements and Balance Sheet Trend Analysis,

Ratio Analysis  Introduction, Classification and Interpretation of Ratios, Problems on ratio analysis 

Introduction, Concept of Cash, Sources of cash flow Cash from operation, cash from Financing and cash from investment, Inflow and outflow of cash Preparation of cash flow statements- practical problems 

Procedures and Utility, Sample Reports

Course Description: From the perspective of a country's economic development, entrepreneurship is a

necessary ingredient for stimulating economic growth and employment opportunities. In the developing

world, successful small businesses are the primary engines of job creation & income growth. In this

direction, this course on entrepreneurship development, educates an individual about the efforts taken by

the government broadly to encourage entrepreneurship.From the perspective of development of an individual’s entrepreneurial ability, entrepreneurship education becomes critical as the goal of the course is to help the youth start to think about what dreams or

ideas they have and how they can develop and fulfil them. It is also a way to learn how to interact and

cooperate with other people, be creative and find tools for how to develop themselves and their ideas. The

course aims to motivate an individual to take up an entrepreneurship to attain self-reliance and growth.

Course Objective:

To demonstrate an understanding of the need for entrepreneurship development.

2. To identify critical success factors for taking up entrepreneurship

3. To evaluate factors influencing the entrepreneurial activities in different contexts.

4. To analyze functional strategies required for entrepreneurial success

5. To develop business plans for entrepreneurial opportunities

CLO1. Demonstrate an understanding of the need entrepreneurship development

CLO2. Identify Critical success for taking up entrepreneurship

CLO3. Evaluate factors influencing   the entrepreneurial activities in different contexts

CLO.4 Analyze functional strategies required for entrepreneurial success

CLO5. Develop business plans for entrepreneurial opportunities

 Evolution of the Concept of Entrepreneurship; Theories of Entrepreneurship- Innovation Theory, Harvard

School Theory, Theory of High Achievement, Theory of Profits, Theory of Adjustment of Price-

Entrepreneurship Today; Difference Between a Manager and an Entrepreneur; Models of Entrepreneurial

Development; Types of Entrepreneurs; Intrapreneurship; Women Entrepreneurship-Women Enterprises-

Challenges Faced by Women Entrepreneurs; Entrepreneurial Competencies-Types and importance;

Mobility of Entrepreneurs; Geographical Mobility of Entrepreneurs; Occupational Mobility; Entrepreneurship

in Family Owned Businesses and Non Family Owned Businesses; Challenges & Obstacles faced by

Entrepreneurs; Factors influencing Entrepreneurship-Socio-Cultural, Economic, Political Technological &

Global factors; Business Climate in India for entrepreneurship; Creating Favorable Conditions for the

growth of entrepreneurship in India; Capacity Building for Entrepreneurs.

 Opportunity sensing & Idea Generation; The creativity & innovation; Techniques of Idea Generation-Brain

storming, Reverse Brain storming, Brain writing, Attribute Listing, Free Association, Forced Relationship,

Gordon Method & Parameter Analysis; Selection of Product/Service, Invention, Innovation & Imitation;

Product innovation; Identification of Business Opportunities; Business Opportunities in India; Models for

Opportunity Evaluation & Screening.

 Definition, Role and Importance of Micro, Small, and Medium Enterprises (MSMEs); Problems Faced by

MSME Sector; Government Policy for MSME Sector; Rural Entrepreneurship- Cottage, Khadi and Village

Industries. Make in India Initiatives & Skill Development; Entrepreneurship Development Programs (EDP),

An overview of UNCTAD’s Entrepreneurship Policy Framework.

 Business Planning-Financial Planning, Marketing Planning- Production & Operational Planning and Human

Resource Planning; Importance of a Business Plans; Contents of a Business Plan- Management Summary;Financial Feasibility, Marketing Feasibility and Technological Viability of Business Plans. Business Incubation and Development.

Procedure for Setting Up an Enterprise; Selection of a Project; Decide on the Constitution Obtain

Registration; Obtain Clearances from Departments as Applicable; Arrange for Land/Shed; Arrange for Plant

and Machinery; Arrange for Infrastructure; Prepare Project Report; Apply for and Obtain Finance;

Implement the Project and Obtain Final Clearances. Project Life Cycle , Project Scheduling -Gantt Charts,

Network Techniques ; Project Management Software; Capital Budgeting; Generating an Investment Project

Proposal; Project Analysis; Market Analysis, Technical Analysis, Financial Analysis, Economic Analysis,

Project Evaluation and Selection ; The Payback Period; ; Benefit-Cost Ratio (BCR) Project Financing Equity

Financing; Angel Investing ; Debt Financing ; Miscellaneous Sources; Project Implementation Phase;

Capital Structure and Cost of Capital; Detailed Project Report; Ecological Analysis.

Institutions Supporting Business Enterprises; Central-level Institutions; National Board for Micro, Small, and

Medium Enterprises (NBMSME) The Khadi and Village Industries Commission (KVIC) The Coir Board

MSME-DO; National Small Industries Corporation (NSIC); National Science and Technology

Entrepreneurship Development Board (NSTEDB) National Productivity Council (NPC) Entrepreneurship

Development Institute of India (EDII) National Research Development Corporation of India (NRDCI)

National Entrepreneurship Development Institutes; Other Institutions National Bank for Agriculture and

Rural Development (NABARD) Housing and Urban Development Corporation (HUDCO); Technical

Consultancy Organization (TCO); Small Industries Development Bank of India (SIDBI) ; Export Promotion

Councils (EPCs).

State-level Institutions; State Directorate of Industries and Commerce; District Industries Centers (DIC) ;

State Financial Corporation (SFC); State Industrial Development Corporation (SIDC); State Industrial Area

Development Board (SIADB).

Meaning &; importance Social Entrepreneurship; Sustainable Development Goals (SDG,2030); Social and

Environmental Dimension of Entrepreneurship; Social Enterprises and their Goals; Need & Importance of

Social Enterprise Establishment and Management of Non-Government Organizations; Government Policy

for Social Enterprises.

Hisrich, Robert D, Manimala, J. Mathew, Peters, Michael P. and Shepard, Dean A, (2015).

Entrepreneurship. New Delhi: Tata-McGraw-Hill.

● Gupta, C.B., & Srinivasan, N.D. (2012) Entrepreneurship Development, New Delhi:Sultan Chand & Sons.

Research in common parlance refers to a search for knowledge in any stream or discipline, finding solutions or inputs for questions raised.  Students will be provided with basic concepts of research and its process. The course focuses on inculcating research culture among students through hands-on learning experiences. This course will equip the students with the required skill sets for identifying, analysing and interpreting business problems. This process will help in informed business decision-making. The course is designed to provide experiential learning in all the modules.

Course Objectives:

• To understand the concepts, tools and terminologies used in the research world.
• To identify the methods best suited for investigating different types of problems and questions.
• To demonstrate hands-on experience with different tools used in research
• To construct research questions that are based on and build upon a critical appraisal of existing research;
• To develop a research design and analysis of the results, to provide suggestions based on research findings.

Meaning, Objectives, purpose, types, scope and significance of research in business and industry.  Criteria for Good research, Ethics in Research.

Research Process - Steps in research, identification and formulation of research problem, extensive literature review, Research gap, statement of the problem, need for the study, Variables- meaning and types.  Theoretical framework, research questions. Deductive and inductive logic

Identifying and formulating research problem, Diagnosis of symptoms and problem. Setting research objectives. Doing a review of literature – purpose, methods.  Hypothesis – Meaning, Purpose, Sources, characteristics of hypotheses, types of hypothesis, Formulation of hypothesis.

Sample design, steps in sampling process, sampling methods – probability Sampling and non-probability sampling, sampling error, Criteria for good sample, determining sample size (infinite and finite). Measurement – Types of Scales, Scaling techniques. 

Data sources - primary and secondary data, Data Collection methods- Survey, observation, Interview, focus group technique. Data collection instruments, construction of Questionnaire, schedule, characteristics of good instrument, and errors in measurement, Reliability and validity of research instruments.

Data processing – Editing, coding, tabulation, normality and stationary test, pictorial and graphical presentation of Data, Parametric and non-parametric hypothesis testing, hypothesis testing using statistical tools such as descriptive, Chi–square, t-test, ANOVA, Correlation and Regression. 

Classification and tabulation, research presentation, types of report - Research proposal, research report. Format of a report-Layout, Precautions. Citation and referencing (APA, 6th edition)

2.Chawla, D., &Sondhi, N. (2011). Research Methodology: Concepts and cases. New Delhi: Vikas Publishing House 

3.Gupta, S. L and Gupta, Hitesh (2012), Business Research Methods, McGraw Hill Education (India) Private Limited, New Delhi

4.Krishnaswamy, K.N., Sivakumar, A.I., Mathirajan, M (2007), Management Research Methodology, Pearson, New Delhi 

5.Kothari, C. R. (2009). Research Methodology Methods & Techniques (2 ed.). New Delhi: VishwaPrakashan.

6.Krishnaswami, O., &Ranganatham, M. (2013). Methodology of Research in Social Sciences. Mumbai: Himalaya Publishing House.

7.Majhi, P. R., &Khatua, P. K. (2013). Research Methodology (Concepts, Methods, Techniques and SPSS). Mumbai: Himalaya Publishing House.

8.Srivastava. T. N and RegoShailaja (2012), Business Research Methodology, Tata McGraw Hill Education Private Limited, New Delhi.

9.Bajpal, N. (2017). Business research methods. New Delhi: Pearson.

Course‌ ‌Description‌: ‌ ‌ ‌

This course is designed to give the students a stage to apply and understand all the concepts taught in Intermediate Data Science, Data Engineering & Decision Science. It will help in providing the students with real world industry exposure by guiding them to solve real world problems that Mu Sigma has historically dealt with

Course Objectives:

The objective of the course is to:

1. Understand why simply solving problems is not sufficient and why a more elaborate art of problem solving is in order
2. Understand how solving specific problems and the art of problem solving can co-exist harmoniously in the larger realm of problem solving
3. Understand the tenets of the Art of Problem-Solving framework
4. Understand the frameworks to analyze an industry vertical

Understand problems pertaining to specific industries

Problem Space I will occur once the students are familiar with the design thinking concepts in Decision Science topics. It will be a classroom activity on the problems given by the trainer. This subject will be covered during the second part of the semester.

Students will be taught:

1. To develop an understanding of Demand forecasting in general
2. Examples of real-life applications of Demand forecasting& its impact
3. Techniques to arrive at a solution, their uses & application
4. How to work on an exercise on Demand forecasting

Output expected from students:                                                                                                          

1. Create an Empathy Map, Org Chart and a Vertical writeup on the Industry and the business in question
2. Break down the problem statement using Problem Definition & Design
3. Identify the right sampling technique and performed clustering
4. Performing Hypothesis testing and Exploratory data analysis
5. Arrive at a solution thinking on the lines of Transformation Roadmap                                                                                                             
6. Submit a Jupyter Notebook with the solution

Test the applications of Data Science, Data Engineering & Decision making in the real world

Test the applications of Data Science, Data Engineering & Decision making in the real world

Course‌ ‌Description‌:

‌ ‌ ‌

This course covers Apache Hadoop project which develops an open source software for reliable, scalable, and distributed computing. The course seeks to equip the learners with the framework, libraries, computation, and the usage of big data using Apache Hadoop which is designed to scale up from single servers to thousands of machines. It also allows the users to store all forms of data, that is, both structured data and unstructured data. Hadoop also provides modules like Hive for analysis of large-scale data which will also be covered under this course.

Course Objectives:

The objective of the course is to:

1. Understand how to solve problems that require massive datasets and computation power
2. Understand the storage, access, and the manipulation of large structured and unstructured data
3. Learn about distributed storage of data and the process of working with such systems
4. Use the processes and systems for handling and utilizing such data, including for the purposes of retrieval, accumulation, and computation

Understand Hive Query Language and its uses

‌Distributed file system, reference links, basic shell commands

Common, distributed file system, YARN, MapReduce, references

‌Operators & user-defined functions, operators, built-in questions, date functions, conditional functions, string functions, miscellaneous functions

‌Create/Drop/Alter/Use Database, storage formats, row formats &SerDe, tables and operations on tables, tables – Views & partitioning, permanent functions

Inserting data into Hive tables, dynamic partition inserts, write data into filesystem, Insert/Update/Delete/Merge

1.      White, T (2012). Hadoop: The Definitive Guide. O’Reilly

2. Grover, M (2015). Hadoop Application Architectures. O’Reilly

3. Apache.org – Official documentation for Apache applications

4. Mu Sigma internal training material

1.      White, T (2012). Hadoop: The Definitive Guide. O’Reilly

2. Grover, M (2015). Hadoop Application Architectures. O’Reilly

3. Apache.org – Official documentation for Apache applications

4. Mu Sigma internal training material

Course‌ ‌Description‌:

 ‌The course introduces learners to univariate descriptive statistics, its importance in daily life and application areas, it is designed to equip learners to evaluate and describe any given variable based on its summary statistics. It also covers Machine Learning, which is a subset of Artificial Intelligence, that provides systems the ability to automatically learn and improve through experience. It is an upcoming branch of applied mathematics. The course also enables the learners to understand various components of Time-Series and how it is used to generate a forecast

Course Objectives:

The objective of the course is to:

1. Teach how to summarize large quantities of numerical data and reveal patterns in the raw data
2. Understand how to present the information in a more organized format
3. Become familiar with how to determine whether there is enough statistical evidence in favor of a certain belief and to examine data for distribution
4. Equip to extract features from raw data via data mining techniques and use it to improve the performance of machine learning algorithms

Familiarize to predict or estimate a future event or trend in a business

Data cleaning & treatment, outlier detection & treatment, univariate analysis, multivariate analysis. Introduction to missing value treatment and outlier treatment using ML techniques.

Importing data into R from different formats, web scraping, string processing with regular expressions, text mining 

Importing libraries (R), functions, standardize the data, imputation, handling outliers, binning, one hot encoding, data transformation, factor analysis, principal component analysis, PCA

Smoothening methods, basic forecasting methods, Holt's method, Holt – Winters method, ARIMA

Dynamic time series model – ARIMAX, prophet model, DTW, hierarchical time series, ACF, PACF

1. Bishop, C. (2006). Pattern Recognition and Machine Learning. Berlin: Springer-Verlag.

Mu Sigma internal documents

1. Bishop, C. (2006). Pattern Recognition and Machine Learning. Berlin: Springer-Verlag.

Mu Sigma internal documents

Course‌ ‌Description‌: ‌ ‌ ‌

The course covers two powerful visualization tools Power BI Advanced level features and Tableau. Power BI bridges the gap between data and decision making by creating great data experiences. Tableau platform is known for taking any kind of data from almost any system and turning it into actionable insights with speed and ease. It’s as simple as dragging and dropping

Course Objectives:

The objective of the course is to:

1. Prepare data and data discovery, interactive dashboards, and rich visualizations in one solution
2. Learn an intuitive tool for interacting with data and turning it into insights more easily
3. Learn to create insightful and impactful visualizations in an interactive and colorful way
4. Provide essential skills to create reports and dashboards, statistical and analytical tools

Understand the basics of visualization solutions using Tableau

Summary of Power BI level 1, context in DAX, summarize function, summarize columns function, calculate table function, bidirectional cross filtering, circular dependencies in Power BI

Advanced DAX functions including Filter, CountX, etc., visualization and themes, report themes using JSON, drill through filtering, bookmarks and selection pane, additional functionalities, Python/R in Power BI, write-back functionality, dynamic row level security

Introduction, initial interface, workspace layout, data types, data Source connection and integration, managing data loads, data transformation – Joins & Blends, data schema preparation

Worksheets & Workbooks – Basic filtration, formatting & navigation, interactive filtration, basic visual charts.

Sets, grouping data, parameter creation, drill down & hierarchy

1.      Powell, B (2018). Mastering Microsoft Power BI: Expert techniques for effective data analytics and business intelligence, Packt

2. Guillevin, T. Getting Started with Tableau 2019.2 (Second Edition), Packt

3. Mu Sigma internal training material and case studies

1.      Powell, B (2018). Mastering Microsoft Power BI: Expert techniques for effective data analytics and business intelligence, Packt

2. Guillevin, T. Getting Started with Tableau 2019.2 (Second Edition), Packt

3. Mu Sigma internal training material and case studies

Course Description:

An Organization consists of different departments and processes. Managers at all level must understand how a company’s departments and processes “fit” together to achieve its goal. It focuses on all the functional areas of business and presents a cohesive strategic management model from a strategic perspective. The subject provides an insight on the strategy adopted by the companies in response to environmental change. The course provides a comprehensive and integrated presentation of current strategic management thinking in a clear and succinct format.

Course Objective:

·       To learn the fundamentals of strategic management using the case method.

·       To understand the fundamental principles & interrelationships among business functions such as: R & D, Production, Marketing, Customer Service, finance, human resources and Information Technology

·       To understand the interrelationships of business to individuals, other organizations, government and society.

Defining strategy- levels at which strategy operates- approaches to strategic decision making, the strategic management process- Strategic intent: Vision, mission and objectives

The organizations environment- External and internal environment, components of external and internal environment- Environment scanning- Organizations responses to the environment, A framework for industry analysis, Michael porter’s analysis- usefulness of Industry analysis- Competitive analysis: Forces shaping competition in an industry- interpreting the Five force models- Strategic group, and competitor analysis- Internal analysis: Resource based strategy- the resource based view, Resources- capabilities and competencies- approaches to internal analysis

Corporate level strategy: Introduction- The balanced scorecard- Grand strategies- Growth/Expansion strategy- Diversification Strategy- Stability strategy- Retrenchment strategy- combination strategy, BCG matrix, Global Strategies for corporates– Objective and modes of entry

The concept of corporate restructuring- the process of restructuring- mergers and acquisition- takeovers- cooperative strategies- Reasons for strategic alliances- risks and costs of strategic alliances

Issues in strategy implementation- Activating strategy and resource allocation- strategy-structure relationship- the functional structure- divisionalisation- Functional level strategies:

Operational strategy, financial strategy, marketing strategy and Human resource strategy 

Corporate governance and strategic management- strategic leadership- corporate culture and strategic management- corporate politics and power- personal values and business ethics

Importance, barriers- evaluation criteria- strategic control- operational control- evaluation techniques for operational control- characteristics of an effective control system

Designing a technology strategy- Technology forecasting and R & D Strategies- Strategies for acquisition and absorption of technology- Social audit

2.     Barney, J.B. &Hesterly, W.S.(2011).Strategic Management & Competitive Advantage: Concepts & Cases(4^th ed.). Prentice Hall.

3.     Dess, G., Eisner, A., Lumpkin, G.T., &Namara, G.M. (2011).Strategic Management: creating competitive advantages (6^thed.).McGraw Hill Education.

4.     Hill, C.W.L., & Jones, G.R. (2012). Strategic Management-An Integrated Approach (10^thed.).South Western: Cengage Learning.

·         To equip the students with proper understanding about law and practice of Income Tax in India

·         To impart the knowledge and understanding about law and practice of Goods and Service Tax in India.

·         To comprehend with tax laws and its application in taxation management

•   To connect the students with law and practice of Customs Duty in India

Legal enactments governing Income Tax in India, An overview of basic Concepts- Assessee, Person, Assessment Year, Previous Year, Agricultural Income, Income, GTI, Total Income, Average Rate Of Tax. Determination of residential status, Kinds of income, incidence of tax.

Tax free incomes. Capital and Revenue Expenditure. Comparison between Tax structure in India and other countries. (Self-study)

Chargeability, Treatment of Various Allowances, Perquisites, and their Valuation, Treatment of Provident Fund, profit in Lieu of salary, Deductions from Gross Salary (Practical Problems). Retirement Benefits Computation of taxable salary.

Chargeability, annual value and its determination, deemed ownership deductions from annual value, Computation of taxable income under the head house property (theory with problems)

Meaning of Business and Profession, Incomes Chargeable under this head

Computation of Taxable Income from business (Sole proprietorship firms) and profession.

Meaning of important terms, Short term and Long-term capital gain, cost of acquisition of capital assets, Computation of capital gains, exemptions from LTGC only deductions u/s 54, 54B, 54EC and 54F (theory with simple problems)

Incomes taxable under income from other sources, deductions allowed (applicable only to individuals) Section 80C to 80U, Computation of GTI

Overview of GST, Dual structure, GST council, Definition of Supply, Levy and Tax and Input tax credit. (Theory with simple problems)

Basic concepts, Types of customs duty, Assessable value and computation of total customs duty, Baggage and Courier.

·         Datey V S (2020), GST Laws and Practice with Customs and Foreign Tax Practice (FTP), New Delhi, Taxmann Publications.

2.Prasad, B. Income Tax Law and practice (2018).New Age Publications.

3. Singhania,(2018) Income tax law and practice , Taxman publishers, NewDelhi

Course‌ ‌Description‌: ‌ ‌ ‌

This course is designed to give the students a stage to apply and understand all the concepts taught in Advanced Data Science, Data Engineering & Decision Science. It will help in providing the students with real world industry exposure by guiding them to solve real world problems that Mu Sigma has historically dealt with

Course Objectives:

The objective of the course is to:

1. Understand why simply solving problems is not sufficient and why a more elaborate art of problem solving is in order
2. Understand how solving specific problems and the art of problem solving can co-exist harmoniously in the larger realm of problem solving
3. Understand the logic and calculation of customer lifetime value
4. Understand problems pertaining to specific industries
5. Examine classification techniques used to determine CLTV

Problem Space IV will occur once the students are familiar with the design thinking concepts in Decision Science topics. It will be a classroom activity on the problems given by the trainer. This subject will be covered during the second part of the semester.

Students will be taught:

1. To develop an understanding of CLTV in general
2. Examples of real-life applications of CLTV & its impact
3. Techniques to arrive at a solution, their uses & application
4. How to work on an exercise on CLTV

Output expected from students:                                                                                                          

1. Define and learn to interpret an Empathy Map, Org Chart, Vertical writeup on the Industry and the business in question
2. Make use of breakdown of the problem statement
3. Identify the flow of revenue and calculate CLTV
4. Take part in performing Hypothesis testing and Exploratory data analysis and conclude to a solution thinking on the lines of Transformation Roadmap                                                                                                            
5. Formulate and submit a Jupyter Notebook with the solution

Course‌ ‌Description‌:

‌ ‌

This course covers introduction to Big Data Spark, RDDs – Resilient distributed datasets, Spark and Big Data, built in libraries for Spark, The Spark Shell, Transformations and Actions. This course also covers arithmetic and numbers, values and variables, Boolean and comparison operators, Strings and basic RegEx , Tuples , Collections , Lists , Arrays , Sets , Maps , Flow Control for loops , While Loops and Functions

Course Objectives:

The objective of the course is to:

1. Understand the fundamental concepts of Spark
2. Understand the manipulating big data distributed over a cluster using functional concepts
3. Understand the syntax and usage of Spark and Scala for data access and manipulation
4. Understand the use of Spark and Scala in dealing with big data

Will learn how to launch spark application on a cluster

What is Spark – Introduction to RDDs – Resilient Distributed Datasets, Spark and Big Data, Built in libraries for Spark , The Spark Shell , Transformations and Actions  

Introduction to Spark Data Frames, Data Frames overview, Spark Dataframe Operations, Group By aggregate functions and Handling missing data 

Intro to RDBMS, MS SQL Server, IBM DB2, Oracle, MySQL. Coding in Spark for RDBMS. Packages in SPARK for data transformation.

Apache Spark RDD operations - Transformations and Actions. Linkage, map, filter, flatmap, Map partition, reduced by, groupby, sample, union, join, distinct, coalesce, collect, reduce, aggregate, saveas, countby

Linking, Initializing Streaming Context, Discretized Streams (DStreams), Caching /Persistence and Fault – tolerance Semantics

Course‌ ‌Description‌:

This course covers regression that is the most used Machine Learning paradigm and is often utilized for comparing or establishing the relationship between two or more variables. This course provides learners with an introduction to popular Regression algorithms. Clustering is an Unsupervised Machine Learning technique and is often utilized to differentiate between various levels of a variable. This course also enables the learners to understand the necessity and areas of application of linear statistical model techniques like factor analysis which is an integral part of Exploratory Data Analysis

Course Objectives:

The objective of the course is to:

1. Understand the generalized linear models (GLM) Framework
2. Understand various models under the GLM framework, specifically for cases of continuous outcomes, binary outcomes, and count outcomes
3. Understand data preparation, clustering techniques and cluster validation
4. Understand the Model Validation techniques are used to assess the accuracy of Machine Learning models

Learn techniques like factor analysis which is an integral part of exploratory data analysis

Responses and predictors, General Linear Hypothesis, Distribution of the response variable and link functions, Analysis of Deviance

Importing libraries, functions, standardize the data, imputation, handling outliers, binning, one hot encoding, data transformation, factor analysis, principal component analysis

Assumptions in Linear regression, OLS, Linear regression, Multiple linear regression, ANOVA in regression models, Testing the general linear hypothesis through F-tests, Main effects and interactions, Error analysis and residual plots.

Partitioning methods: k-means, expectation maximization (EM), Hierarchical methods: distance-based agglomerative and divisible clustering

Validation using silhouette score, Dunn Index

Maximum likelihood estimation, logit and probit models, Diagnostics for binary outcome models, likelihood ratio tests, interpretation of estimates under various binary outcome models, Main effects and interactions, confidence intervals of estimates, Prediction intervals for binary outcome models

McCullagh, P, &Nelder, J. A. Generalized Linear Models (2nd edition). Chapman & Hall/CRC Press.

1. McCullagh, P, &Nelder, J. A. Generalized Linear Models (2nd edition). Chapman & Hall/CRC Press.

2. Agresti, A. (2015). Foundations of Linear and Generalized Linear Models, Wiley

Course‌ ‌Description‌: ‌ ‌ ‌

The course covers various aspects of Art of Problem-Solving framework and covers complexity surrounding individual business problems, Mapping problem interconnections, Discovering and identifying the latent interconnection between problems with examples and introduction to D3 Stack

Course Objectives:

The objective of the course is to:

1. Understand the complexity surrounding individual business problems,
2. Mapping problem interconnections, discovering
3. Identifying the latent interconnection between the problems
4. Understand the tenets of the art of problem-solving framework
5. Instil a new approach in decision making

Summary of muPDNA & muOBI

Complexity surrounding individual business problems, Mapping problem interconnections, Discovering and identifying the latent interconnection between problems, Examples of muUniverse

Structural concepts of D3 Stack along with how it helps in creating business solution

Analogy between manufacturing supply chains and decision supply chains, understanding flow of decisions in organizations, role of muDSC in understanding flow and tracking of decisions, examples of muDSC

The DIPP index, flaws in conventional deciphering of the DIPP index, interdependency across D, I, P and P problems to yield greater RoI of the analytical process, examples of muIDA

Course‌ ‌Description: ‌ 

Today’s turbulent business environment has been characterized by ‘the knowledge era’ where competitive advantage is based upon the resource-based view of the firm and successful utilization of employee knowledge. It is the organization that can capture, manage, and apply the different forms of knowledge prevalent in the workplace that will grow and flourish. The purpose of the course is to explore the concept of knowledge and the means by which organizations seek to manage it through formal technological practices and informal social systems. The course looks at a theoretical and practitioner point of view and seeks to provide a 360degree overview of the domain of Knowledge Management.

The objectives of this course are:

●     Understand the key concepts, theories and models that enable knowledge management

●     To provide an outline about the importance of knowledge management in developing   people and organizations.

●     To enable the students to apply the concepts, principles and models of knowledge management in practical situations.

●     To evaluate the various process, approaches and strategies for managing knowledge in organizations

●     To provide solutions to the issues pertaining to managing knowledge

Level of Knowledge: Conceptual

Introduction to Knowledge Management; Multidisciplinary Nature of KM - The Two Major Types of Knowledge, The Concept Analysis Technique; History of Knowledge Management - From Physical Assets to Knowledge Assets Organizational Perspectives on Knowledge Management; Importance of KM - KM for Individuals, Communities, and Organizations

Level of Knowledge: Conceptual

Major Approaches to the KM Cycle - The Zack KM Cycle, The Bukowitz and Williams KM Cycle, The McElroy KM Cycle, The Wiig KM Cycle; An Integrated KM Cycle; Strategic Implications of the KM Cycle; Practical Considerations for Managing Knowledge.

Level of Knowledge: Conceptual and Analytical

Major Theoretical KM Models - The von Krogh and Roos Model of Organizational Epistemology, The Nonaka and Takeuchi Knowledge Spiral Model, The Knowledge Creation Process, Knowledge Conversion, Knowledge Spiral.

Level of Knowledge: Conceptual and Analytical

Tacit Knowledge Capture - Tacit Knowledge Capture at Individual and Group Levels, Interviewing Experts, Structured Interviewing, Stories, Learning by Being Told, Learning by Observation; Tacit Knowledge Capture at the Organizational Level; Explicit Knowledge Codification - Cognitive Maps, Decision Trees, Knowledge Taxonomies.

Level of Knowledge: Conceptual and Analytical

The Social Nature of Knowledge; Sociograms and Social Network Analysis, Knowledge-Sharing Communities - Types of Communities, Roles and Responsibilities in CoPs, Knowledge Sharing in Virtual CoPs; Obstacles to Knowledge Sharing, The Undernet.

Level of Knowledge: Conceptual and Analytical

Knowledge Capture and Creation Tools - Content Creation Tools, Data Mining and Knowledge Discovery, Blogs, Content Management Tools; Knowledge Sharing and Dissemination Tools - Groupware and Collaboration Tools, Wikis, Networking Technologies; Knowledge Acquisition and Application Tools - Intelligent Filtering Tools, Adaptive Technologies.

Level of Knowledge: Conceptual and Analytical

Different Types of Cultures, Organizational Culture Analysis, Culture at the Foundation of KM, The Effects of Culture on Individuals; Cultural Transformation to a Knowledge-Sharing Culture; Organizational Maturity Models - KM Maturity Models, CoP Maturity Models. 

●     Leonard-Barton, D., Swap, W. C., & Barton, G. (2015). Critical knowledge transfer: Tools for managing your company's deep smarts. Boston, US: Harvard Business Review Press.

●     Horaguchi. (2014). Collective knowledge management: Foundations of international business in the age of .. [Place of publication not identified]: Edward Elgar Publishing Ltd.

●     Jay Liebowitz., & Liebowitz, J. (2012). Knowledge Management Handbook: Collaboration and social networking (2nd ed.). London: CRC Press.

●     Pugh, K. (2011). Sharing hidden know-how: How managers solve thorny problems with the knowledge jam. San Francisco, CA: Jossey-Bass.

Course Description: The course will make students understand the importance of managing cultural diversity in a globalized world. They will learn about the factors that influence a country’s culture and communication process. The course will help them to develop cultural sensitivity and improve their cultural awareness.

Course Objectives:

 To understand the concepts of cross cultures.

 To identify the difference and similarity in the cultural context of different countries.

 To develop cultural awareness and sensitivity about other cultures

Challenges of Globalization, Role of Global Manager- organizational context, culture and managerial roles- Evaluating cross cultural management studies

Features of Culture, Key cultural terminology, Cultural Differences, Culture and Social Group.

Kluckhohn & Strodbeck Framework, Hofstede Study, The GLOBE study, Trompenaars Dimensions, Cultural Distance.

Cultural factors in communication, Variables in communication process, International Body Language, Guidelines for English and foreign languages. The internet and intercultural Communication.

Understanding the characteristics and Cultural guidelines for: North American Work Culture – Pan American perspective, United States of America; Middle-East Work Culture- Middle East overview, Cultural Aspect of Arab, Egypt, Saudi Arabia.; Asian Work Culture- Cultural aspect of China, India, Japan, Pakistan, South Korea; European Work Culture- European Diversity and synergy, Western Europe, France, Italy.

●        Thomas, D. C. 1. (2018). Cross-cultural management: Essential concepts (Fourth edition.). London: Sage.

●        Abramson, N. R., & Harris, P. R. 1. (2018). Managing cultural differences (Tenth Edition.). New York: Routledge.

●        Ting-Toomey, S. (2019). Communicating across cultures (Second edition.). New York: The guilford press.

       ●    Ghemawat, P. (2018). Redefining global strategy: Crossing borders in a world where differences still matter. Boston: Harvard business review press.

Production and Operations Management (POM) is concerned with the management of resources and activities that produce and deliver goods and services for customers.  Efficient and effective operations can provide an organization with major competitive advantages since the ability to respond to customer and market requirements quickly, at a low cost, and with high quality, is vital to attaining profitability and growth through increased market share. The course focuses on the basic concepts, issues, and techniques for efficient and effective management of production and operations.

Introduction,‌ ‌Historical‌ ‌Development,‌ ‌Concept‌ ‌of‌ ‌Production,‌ ‌Production‌ ‌System,‌ ‌Classification‌ ‌of‌ Production‌ ‌System,‌ ‌Production‌ ‌Management.‌ ‌Objectives‌ ‌of‌ ‌Production‌ ‌Management,‌ ‌Concept‌ ‌of‌ ‌Operations.‌ ‌Distinction‌ ‌between‌ ‌Manufacturing‌ ‌Operations‌ ‌and‌ ‌Service‌ ‌Operations.‌ ‌Operations‌ ‌Management,‌ ‌A‌ ‌Framework‌ ‌for‌ ‌Managing‌ ‌Operations.‌ ‌Objectives‌ ‌of‌ ‌Operations‌ ‌Management,‌ ‌Managing‌ ‌Global‌ ‌Operations,‌ ‌Scope‌ ‌of‌ ‌Production‌ ‌and‌ ‌Operations‌ ‌Management.‌ ‌ ‌

Introduction‌ ‌and‌ ‌meaning‌, ‌Need‌ ‌for‌ ‌selecting‌ ‌a‌ ‌suitable‌ ‌location,‌ ‌Factors‌ ‌influencing‌ ‌plant‌ ‌location, Weber’s theory of location. General‌ ‌locational‌ ‌factors,‌ ‌and‌ ‌Specific‌ ‌locational‌ ‌factors‌ ‌for‌ manufacturing‌ ‌organization‌ ‌and‌ ‌for‌ ‌Service‌ ‌organization.‌ ‌Objectives,‌ ‌principles‌ ‌and‌ ‌Types‌ ‌of‌ ‌plant‌ ‌layout.‌ ‌Process‌ ‌layout,‌ ‌Product‌ ‌Layout,‌ ‌Combination‌ ‌layout,‌ ‌Fixed‌ ‌position‌ ‌layout,‌ ‌Group‌ ‌layout.‌ ‌Physical‌ ‌Facilities.‌ ‌

Introduction‌ ‌and‌ ‌Meaning,‌ ‌Scope‌ ‌or‌ ‌functions‌ ‌of‌ ‌Materials‌ ‌Management,‌ ‌Material‌ ‌planning‌ ‌and‌ ‌control,‌ ‌Purchasing and ‌Stores‌ ‌Management. EOQ, ‌Inventory‌ ‌control techniques (ABC Analysis, FSN, VED, HML, SOS, SDE, GOLF & XYZ Analysis), Vendor selection, development and‌ vendor rating, ‌Standardization,‌ ‌Simplification,‌ ‌Value‌ ‌analysis / Value Engineering, ‌Just‌ ‌in‌ ‌time and ‌Ergonomics.‌

Introduction‌ ‌and‌ ‌Meaning,‌ ‌Objectives‌ ‌and‌ ‌Principles‌ ‌of‌ ‌Material‌ ‌Handling,‌ ‌Selection‌ ‌of‌ ‌Material‌ ‌

Handling‌ ‌Equipment,‌ ‌Evaluation‌ ‌of‌ ‌Material‌ ‌Handling‌ ‌system,‌ ‌Material‌ ‌Handling‌ ‌equipment’s,‌ ‌

Guidelines‌ ‌for‌ ‌Effective‌ ‌Utilization‌ ‌of‌ ‌Material‌ ‌Handling‌ ‌Equipment,‌ ‌Relationship‌ ‌between‌ ‌Plant‌ ‌

Layout‌ ‌and‌ ‌Material‌ ‌Handling. ‌

Introduction‌ ‌and‌ ‌Meaning,‌ ‌Need,‌ ‌Objectives,‌ ‌Phases‌ ‌of‌ ‌Production‌ ‌Planning‌ ‌and‌ ‌Control,‌ ‌Functions of‌ ‌Production‌ ‌Planning‌ ‌and‌ ‌Control,‌ ‌Operations‌ ‌Planning‌ ‌and‌ ‌Scheduling‌ ‌Systems,‌ ‌Aggregate‌ ‌Planning,‌ ‌Master‌ ‌Production‌ ‌Schedule‌ ‌(MPS),‌ ‌Material‌ ‌Requirement‌ ‌Planning‌ ‌(MRP),‌ ‌Capacity‌ ‌Planning,‌ ‌Routing,‌ ‌Scheduling.‌

 ‌

Introduction‌ ‌to‌ ‌Quality,‌ ‌Fundamental‌ ‌factors‌ ‌affecting‌ ‌quality,‌ ‌Control,‌ ‌need‌ ‌for‌ ‌controlling,‌ ‌Quality‌ ‌Inspection,‌ ‌Types‌ ‌of‌ ‌Quality‌ ‌Control,‌ ‌Steps‌ ‌in‌ ‌Quality‌ ‌control,‌ ‌Objectives‌ ‌of‌ ‌Quality‌ ‌Control,‌ ‌Benefits‌ ‌of‌ ‌Quality‌ ‌Control,‌ ‌Seven‌ ‌Tools‌ ‌for‌ ‌Quality‌ ‌Control,‌ ‌Causes‌ ‌of‌ ‌Variation‌ ‌in‌ ‌Quality,‌ ‌Statistical‌ ‌Process‌ ‌Control,‌ ‌Quality‌ ‌circles.‌ Concept of Quality Assurance and ‌Total‌ ‌Quality‌ ‌Management.‌

Introduction,‌ ‌Objective,‌ ‌types,‌ ‌maintenance‌ ‌planning‌ ‌and‌ ‌scheduling,‌ ‌Modern‌ ‌Scientific‌ ‌Maintenance‌ Methods-‌ ‌Six‌ ‌Sigma‌ ‌Maintenance,‌ ‌Enterprise‌ ‌Asset‌ ‌Management‌ ‌(EAM),‌ ‌Lean‌ ‌Maintenance,‌ ‌Computer‌ ‌Aided‌ ‌Maintenance

International publishers.

Management‌,‌ ‌Himalaya‌ ‌Publishers.‌ ‌

2.Khanna,‌ ‌R.B.‌ ‌(2016).‌ ‌Production‌ ‌and‌ ‌Operations‌ ‌Management,‌ PHI‌ ‌Learning‌ ‌Pvt.‌ ‌ Ltd., New Delhi

3. Krajewski,‌ ‌Lee‌ ‌J.,‌ ‌Ritzman,‌ ‌Larry‌ ‌P.,‌ ‌and‌ ‌Manoj‌ ‌K.‌ ‌Malhotra‌ ‌(2013).‌ ‌Operations‌ ‌Management:‌ ‌Processes‌ ‌and‌ ‌Value‌ ‌Chains,‌ ‌8/e;‌ ‌New‌ ‌Delhi:‌ ‌Pearson‌ ‌Education.‌ ‌ ‌Richard,‌ ‌B.‌ ‌Chase,‌ ‌

4.Ravi‌ ‌Shankar,‌ ‌F.‌ ‌Robert,‌ ‌Jacobs‌ ‌and‌ ‌Nicholas,‌ ‌J.‌ ‌Aquilano‌ ‌(2018).‌ ‌Operations‌ ‌and‌ ‌Supply‌ ‌Management‌ ‌12/e;‌ ‌New‌ ‌Delhi:‌ ‌Tata‌ ‌McGraw-Hill‌ ‌

5.Singh,‌ ‌S.P.‌ ‌(2014)‌ ‌Production‌ ‌and‌ ‌Operations‌ ‌Management,‌ ‌1/e,‌ ‌New‌ ‌Delhi:‌ ‌Vikas‌ ‌

      Publishing ‌House‌

6. Paneerselvam R (2016), Production and Operations Management, 3/e, PHI Learning, New Delhi

7. Richard Chase, Nicholas Acquilano et al (2015), Operations Management for Competitive Advantage, 11/e, The Mc Graw Hill Company

CIA 1: 20  (100%) : 20 marks

CIA 2: 50 (50%) 25 marks

CIA 3: 20 (100%) : 20 marks,

ESE : 50( 60%): 30 marks

Attendance: 5 marks.

CIA: ESE = 70:30

Total 100 marks

Course Description:  A law that governs the dealings regarding commercial matters, quietly known as business law. Business Law, a branch of civil law comprises governance of commercial and business transactions in both the public and private realms. Business law helps to resolve the business disputes, maintain order and build an acceptable  standards when it come close to the other business, government and customers. A better understanding of legal matters also provides a manager with a framework on which a decision can be made. This course covers important sub branches of Business Laws,  such as Contract Law, Intellectual Property Law, Consumer Protection Law, Competition Law, Law of Sale of Goods and Cyber Law etc.

Course Objectives:

●        To illustrate  the  legal provisions of  key aspects  of business laws

●        To outline the framework of Contract Law in India

●        To explain the legal provisions relating to Patents, Trade Marks and Copy Rights in India

●        To demonstrate an understanding of regulatory framework of Sale of Goods

      ●        To identify the  causes of the problem faced by consumers and competitors  and analyze the remedies provided for violations of legal provisions

Level of Knowledge: Conceptual

Meaning and Scope of Business Law – Sources of Indian Business Law. The Indian Contracts Act, 1872: Definition – types of contracts- Essentials of a Contracts. Discharge of a contract and remedies for breach of contract. Government Contracts: Article 299: Constitution of India. Concept of Equity, Fairness and Reasonableness, Doctrine of Promissory Estoppel vs. Executive Necessity, No person liability. E-Contracts: Meaning & need for Digital Goods, Unfair terms in E-contract. Indian Evidence Act: Basic Concepts.

Level of Knowledge: Conceptual: Distinction between Indemnity and Guarantee, Kinds of Guarantee, Rights of Surety, Liability of Surety, and Discharge of Surety. 

Level of Knowledge: Conceptual: Meaning and scope of intellectual properties – The Patent Act of 1970 and its amendments as per WTO agreement, background, objects, definition, inventions, patentee, true and first inventor, procedure for grant of process and product patents, WTO rules as to patents, rights to patentee – infringement– remedies. The Copyright Act, 1957- Meaning – Its uses and rights. The Trade Marks Act, 1999 - meaning, registration, procedures – infringement– Authorities concerned –Remedies.

Level of Knowledge: Conceptual: The Competition Act, 2002- Concept of Competition, Development of Competition Law, overview of MRTP Act 2002, Anticompetitive Agreements, Abuse of dominant position, combination, regulation of combinations, Competition Commission of India; Appearance before Commission, Compliance of Competition Law. Types of Offence and penalty. 

Level of Knowledge: Conceptual: The Sale of Goods Act, 1930- Definition of Goods, Sale and Agreement to Sell, Conditions and Warranties, Rights & Liabilities of a Buyer & Seller, Rights of an Unpaid Seller. The Negotiable Instruments Act, 1881- Statutory definitions, promissory note, bill of exchange or cheque payable. Dishonour of Negotiable Instrument. Types of Offences and Penalties.