Business Analytics for Senior Managers

With a passion for academic excellence, XLRI was founded in 1949. XLRI has the vision of nurturing responsible global leaders for the greater common good and a sustainable future. It is known to be one of the best B-Schools in India. The world-class amenities and faculty at XLRI spare no effort to make its curriculum the best and deliver it most effectively. It continuously scans the developments in business and society and proactively tries to meet the challenges. The characteristic that sets XLRI apart is magis – the zeal to do better, never to be satisfied with being mediocre and aspire to excel.

Since 2002, XLRI Virtual Interactive Learning, as a unique academic methodology, allows working professionals to undertake management education without taking a break from their careers. Around 7000 working
professionals have benefited from various programmes under XLRI-VIL.
 

VIL is a unique model of live online teaching where XLRI faculty teach students across the country.

Key Benefits

  • Have a managerial understanding of the tools & techniques used in Analytics, Data Science and Artificial Intelligence (AI).
  • Identify areas in their organisation where business analytics can be gainfully applied.
  • Develop skills and knowledge for productively managing data science and analytics teams.
  • Evaluate investment decisions for analytics projects in their organisations.
  • Help build a data-driven organisation and scale the data team.
  • Understand the ethical concerns on data privacy and how to mitigate them.

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Participant Profiles

All the key elements of the program – the faculty, the content, peer interactions and application exercises etc. are designed specifically for senior managers. The modules are crafted in a way that participants do not need prior knowledge of coding.

  • Graduation (10+2+3) in any discipline.
  • A minimum 6 years of work experience.
  • Decision-making role is preferred.
  • Confident fluency in written and spoken English.

Program Curriculum

  • Analytics as Strategic Lever

    • Data and data literacy in organisations
    • Types of analytics – descriptive,
      predictive and prescriptive
    • Application of different analytics in different use cases
    • Good and bad Analytics
    • Deriving organisation’s data science objectives from strategic business objectives
    • Building hypothesis for organisational
      decision making: use cases from
      different verticals
    • Limitation of analytics – where intuition still wins!
    • Case Study: Harvard article on “Data Science and Art of Persuasion”
  • Revisiting Statistics for Managers

    • Describing and presenting data
    • Applying measures of central tendency in business metrics
    • Probability and its application in business
    • Sampling theories and their application in
      business
    • Hypothesis testing, use cases in business
    • Analysis of variance, use cases in business
    • Correlation and regression, use cases in
      business
  • Decision-making using Algorithms & Machine Learning

    • Principal types of algorithms
    • Application of Bivariate and Multiple linear
      regression models
    • Classification algorithms –
      concept and use cases
    • Clustering algorithms – concept and use cases
    • Design of recommendation system
  • Spreadsheet Modeling for Business Decision

    • Modelling approach to decision-making
    • Linear Programming approach to solving a
      business problem, e.g.

      • a. Make-Buy decision
      • b. Investment decision
      • c. Blending problem
      • d. Production and inventory planning problem
      • e. Multi-period cash flow problem
    • Sensitivity Analysis and Simplex Method
  • Data Warehousing & Technology

    • Data management and querying
    • Data extraction, transformation and
      loading (ETL) techniques
    • Fundamentals of data warehouse
    • Overview of the technology stack to
      support analytics
  • Digital Media Analytics

    • Scope and benefits of digital media analytics
    • Types of digital media analytics
    • Consumer insights using the web and mobile
      app analytics
    • Social media analytics
    • Overview of Text mining and sentiment analysis
    • Online reputation management
  • Big Data

    • Understanding Big Data
    • Understanding the application of Big Data
    • Big Data application tools – Hadoop, MapReduce
    • Exploiting Big Data for business decision
    • Examples from Facebook & Google
  • Application of Deep Learning and Reinforcement Learning in Managerial Decision-making

    • Fundamentals of Deep Learning
    • Deep, Convolution and Recurrent
      Neural Network – concept
    • Use cases of Deep Learning in
      different industry verticals
    • Fundaments of Reinforcement Learning
    • Use cases of Reinforcement Learning
      in industry use cases
  • Data Visualisation and Story-telling

    • The art of story-telling with data
    • Data visualisation – concept and application
    • Using self-service data visualisation tools (e.g. Tableau) to generate management reports and dashboards
    • Visualising data using infographics
    • Evaluating an Analytics report
  • Managing a Large-Scale Data Science project

    • Data Science project management methods
      and governance
    • Application of Agile
    • Managing organisational change
    • Developing and managing a data science
      project contract
  • Developing a Business Case for Analytics Project

    • When is an investment in data science
      justified and when not
    • Identifying and quantifying the benefits
      of data science for an organisation
    • Estimating investments in a data science project
    • Estimating return on investment in a
      data science project
  • Building a Data-Driven Organisation

    • New organisation roles and governance for
      a data-driven organisation
    • Recruiting and retaining data science talent pool
    • Scaling a data team
    • Vendor eco-system for data science services
  • Data Privacy and Trust

    • Ethical Concern on data privacy and trust in Analytics
    • Methods to preserve the privacy of sensitive data
    • Legal issues on data privacy
    • Recent case studies
  • Capstone Project

    • The participants will be asked to work on a Capstone Project for an industry domain of their preference. It is expected that the participants will work on live data set from their own organisation.
Note: The list of topics is not exhaustive and is subject to change.

  • Dr. Abhishek Chakraborty

    Dr. Abhishek Chakraborty

    Productions, Operations and Decision Sciences

    Dr. Chakraborty has a MSc. – Applied Mathematics; Fellow-IIM Calcutta.
     
    He has worked with TCS and JDA Software. His research interests include Inventory Management; Supply Chain Coordination; Game Theory in Supply Chain; Operations Research in Sports.

  • Dr. Supriya Kumar De

    Dr. Supriya Kumar De

    Productions, Operations and Decision Sciences and Information Systems

    Dr. Supriya Kumar De has a MSc and Ph.D from IIT Kharagpur.
     
    He has worked with IDRBT and XLRI. His research interests include Product Design and Development, Business Intelligence, Data Warehouse and Data and Knowledge Engineering etc.

  • Prof. Atanu Ghosh

    Prof. Atanu Ghosh

    PGDM (IIM Bangalore), BE (Jadavpur University)

    He is the Visiting Faculty at XLRI Jamshedpur since 2008. He is also Adjunct/ Visiting Faculty with other leading Business Schools including IIM Calcutta, IIM Udaipur, XIM Bhubaneswar, and UPH Jakarta. He is also the Promoter, Founder and CEO – Salt n Soap, Medinook and Bluebeaks Solutions. Before his entrepreneurial stint, Atanu was a Director with IBM and, prior to that, a Principal with PwC. With IBM and PwC Atanu has worked extensively in India, USA, UK, SE Asia and China. Working for IBM and PwC Atanu has consulted leading Fortune 100 Companies on their SAP and ERP deployment. Atanu also headed IBM’s SAP Practice for Bangalore and China.

Dates & Fees

Dates Length Location Tuition Fees
3rd Nov, 2019 7 months Live-Online Teaching and Campus Immersion- 1 visit – 3 days at XLRI campus, Jamshedpur. INR 1,38,000 + Taxes
Deadline Application Fees
Instalment I At the time of application INR 2,500 (Registration Fees) + INR 10,000 (Programme Fees) + INR 12,000 (Campus Visit Accommodation Fees) + Taxes
Instalment II 20th Oct, 2019 INR 64,000 (Programme Fees) + Taxes
Instalment III 20th Jan, 2020 INR 64,000 (Programme Fees) + Taxes