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Chapter 1 Intro to Business Analytics questions and answers.
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Chapter 1 Intro to Business Analytics questions and answers.
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Chapter 1 Intro to Business Analyticsquestions and answers.
Business analytics is the use of: ANS - -Data
-Information Technology
-Statistical Analysis
-Quantitative methods
-Math/Computer-based methods
*to help managers gain insight about their business operations and make better, fact-based decisions.
Applications of Business Analytics ANS - pricing, customer segmentation, merchandising, location,
supply chain design, staffing, health care
Pricing ANS - setting prices for consumer and industrial goods, government contracts, and maintenance
contracts.
Customer Segmentation ANS - identifying and targeting key customer groups in retail, insurance, credit
card industries, etc.
Merchandising ANS - determining brands to buy, quantities, and allocations
Location ANS - finding the best spot for branches or where to service equipment.
Supply Chain Design ANS - determining the best sourcing and transportation options and finding the
best delivery routes.
Staffing ANS - ensuring appropriate staffing levels and capabilities, and hiring the right people.
, Health Care ANS - scheduling operating rooms to improve utilization, improving patient flow and
waiting times, purchasing supplies, and predicting health risk factors.
Benefits of Analytics ANS - reduced costs, better risk management, faster decisions, better productivity
and enhanced bottom-line performance such as profitability and customer satisfaction.
Challenges of Analytics ANS - lack of understanding of how to use analytics, competing business
priorities, insufficient analytical skills, difficulty in getting good data and sharing information, and not
understanding the benefits versus perceived costs of analytics studies.
Commercial Software ANS - -IBM Cognos Express
-SAS Analytics
-Tableau
Spreadsheets ANS - -Widely used
-Effective for manipulating data and developing and solving models
-Support powerful commercial add-ons
-Facilitate communication of results
Descriptive Analytics ANS - the use of data to understand past and current business performance and
make informed decisions.
Predictive Analytics ANS - predict the future by examining historical data, detecting patterns or
relationships in these data, and then extrapolating these relationships forward in time.
Prescriptive Analytics ANS - identify the best alternatives to minimize or maximize some objective.
Retail Markdown Example: Descriptive ANS - examine historical data for similar products (prices, units
sold, advertising)
Retail Markdown Example: Predictive ANS - predict sales based on price
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