BUSI 650 Summer 2019: Introductions, Business Analytics, Data Analytics, and Modeling

BUSI 650 SUMMER 2019 URVISH PANKAJKUMAR SUBODH 1 1 ST WEEK ? Introductions ? What are Business Analytics, Data Analytics, and Modeling? ? Descriptive v/s Inferential Analysis ? How are these used in business problem solving or decision making? ? Reference point v/s decision point ? Team Building 2 INTRODUCTIONS ? Why are you doing this course/what do you intend to achieve with it (on paper) ? About you 3 WHAT IS DATA? ? Fact or statistics related to an area of interest ? Example: Population stats or Stock prices ? How is data collected? ? Manually through submissions ? Benefits: Cheaper – Ease of use – Integrity of the Data – Good Data Privacy and protection – Reliable – Lack of Technology ? Limitation: Time consuming – Storage issues – Loss of Data – Interpretation Error – Time Lag ? Automatically through gadgets such as POS systems ? Benefits: More data points – Relatively less time lag – easy access – time savings – better accuracy ? Limitations: Data privacy/unanimous – over reliance on technology/infrastructure – cost of infrastructure/technology – potential error in data aggregation – Lack of integrity/Fake Data – Complex Technology ? Semi Automatic ? A mix of automated data along with manual adjustments ? Who collects data? ? Governments ? BI Companies ? Industry Associations or Boards 4 BUSINESS ANALYTICS, DATA ANALYTICS, AND MODELING ? Analytics is analyzing or breaking down the data to make decisions. ? Example is calculating mean income to understand average earnings. ? Data Analytics (non-business) ? Concept – analytics in the non business area ? Examples – environment ? Business Analytics ? Concept – analytics in the business area ? Examples – Average sales or consumer profiling or Correlation between inflation and interest rates ? Modeling is a function or math function (Sales = Price per unit X Units Sold) ? Concept to forecast using assumptions and math functions ? Examples – Sales forecast 5 DESCRIPTIVE VS INFERENTIAL ANALYSIS ? Descriptive Analysis – Analysis of the past – Examples is average oil prices from 1986 to 2020 ? Inferential Analysis – Forecasting the data using the past data or Generalizing the results of a sample to the population – Examples forecasting sales from past sales data or generalizing the quality of the product from a small sample test. 6 PROBLEM SOLVING V/S DECISION MAKING ? Problem solving: Chronological order or problem solving using data ? 1) Understanding the problem: Spend more time on the problem statement. Too often the problem statements are incorrect. Hint: spend more time here, understanding of the process helps too. ? 2) Find the data: Public or private sources. ? 3) research and analysis: Current trends and recent researches or news. ? 4) Possible solutions: List of possible solutions and its feasibility. ? Decision making: It is an art! ? Reference point: Take the analysis/analytics into consideration. ? Decision Point: Using the analysis/analytics to take a decision. ? Examples: ? Reference point – There is lack of complete data or lack of integrity in the data. If the average income of a project is higher than expectations. ? Decision point – When you have clarity in the data. – Net Present Value. 7 WHAT IT MEANS FOR BUSINESSES TODAY ? Data Strategy: Is a companies ability to create a framework that fits its overall mission, vision and strategy. ? Framework of what kind of data to collect, how to collect and how to use it. ? New Businesses: Spotify example about using the privacy policy as another version of data strategy. ? The Classic – Brick & Mortar’s: They do have the data, sometimes don’t know how to use it. ? Small businesses: Do have small pieces of data, it is disintegrated and lacks technical expertise to use it. Can ask their suppliers for market trends. ? Big businesses: Loyalty programs. AI’s. Online cookies. ? Consulting or Data Analytics firms: ? Scalability: Creating it once and repeating the hack out of it! ? Ad Hoc: Once in a while 8 TEAM BUILDING ? Find your expertise ? Share knowledge, ideas and inputs ? Build one block at a time ? Projects I and II 9