Instructor’s Solutions For Introduction to Business Analytics,
2nd Edition (Richardson & Watson)Chapter 1 End-of-Chapter
Assignment Solutions
Multiple Choice Questions
1. (LO 1.1) A coordinated, standardized set of activities conducted by both people and equipment to accomplish a
specific business task is called .
a. business processes
b. business analysis
c. business procedure
d. business value
2. (LO 1.2) According to the information value chain, data combined with context is
a. Information.
b. Knowledge.
c. Insight.
d. Value.
3. (LO 1.5) Which phase of the SOAR analytics model addresses the proper way to communicate results to the
decision maker?
a. Specify the question
b. Obtain the data
c. Analyze the data
d. Report the results
4. (LO 1.5) Which phase of the SOAR analytics model involves finding the most appropriate data needed to address
the business question?
a. Specify the question
b. Obtain the data
c. Analyze the data
d. Report the results
5. (LO 1.5) Which questions seek information about Tesla’s sales in the next quarter?
a. What happened? What is happening?
b. Why did it happen? What are the causes of past results?
c. Will it happen in the future? What is the probability something will happen? Can we forecast what
will happen?
d. What should we do, based on what we expect will happen? How do we optimize our performance based
on potential constraints?
6. (LO 1.5) Which questions seek information on the routing of products from Queretaro, Mexico to Chicago,
United States in the last quarter?
a. What happened? What is happening?
b. Why did it happen? What are the causes of past results?
c. Will it happen in the future? What is the probability something will happen? Can we forecast what will
happen?
1|Page
, d. What should we do, based on what we expect will happen? How do we optimize our performance based
on potential constraints?
7. (LO 1.5) Which questions ask why net income is increasing when revenues are decreasing, counter
to expectations?
a. What happened? What is happening?
b. Why did it happen? What are the causes of past results?
c. Will it happen in the future? What is the probability something will happen? Can we forecast what will
happen?
d. What should we do, based on what we expect will happen? How do we optimize our performance based
on potential constraints?
8. (LO 1.5) Which questions help managers understand how to organize future shipments based on expected
demand?
a. What happened? What is happening?
b. Why did it happen? What are the causes of past results?
c. Will it happen in the future? What is the probability something will happen? Can we forecast what will
happen?
d. What should we do, based on what we expect will happen? How do we optimize our performance
based on potential constraints?
9. (LO 1.5) Which term refers to the combined accuracy, validity, and consistency of data stored and used over
time?
a. Data integrity
b. Data overload
c. Data value
d. Information value
10. (LO 1.3) A specialist who knows how to work with, manipulate, and statistically test data is a
a. decision maker.
b. data scientist.
c. data analyst.
d. decision scientist.
11. (LO 1.4) Which type of analysts predicts the amount of money that a company will receive from its customers to
help management evaluate future investments based on expected investment performance, such as
investments in equipment or employee training?
a. Marketing analyst
b. Operations analyst
c. Financial analyst
d. Accounting analyst
12. (LO 1.4) Which type of analyst addresses questions regarding tax and auditing?
a. Marketing analyst
b. Operations analyst
c. Financial analyst
d. Accounting analyst
13. (LO 1.5) Suppose a company has timely product reviews that are available when needed, but the reviews are
biased. These product reviews are which type of data?
a. Reliable
b. Relevant
c. Curated
d. Consistent
2|Page
,14. (LO 1.6) Which common visualization type shows trends in values over time?
a. Line graph
b. Scatterplot
c. Pie chart
d. Bar chart
15. (LO 1.6) Which common visualization type shows the composition of values over time?
a. Line graph
b. Scatterplot
c. Pie chart
d. Bar chart
Discussion Questions
1. (LO 1.1) Give five examples of business processes at Tesla. How do they create business value for Tesla and its
shareholders?
Suggested Solution:
Answers will vary,
1. Tesla procures automobile parts from auto suppliers – Because of Tesla’s unique styling, getting quality
parts from its suppliers on a timely basis will support its manufacturing business.
2. Tesla manufactures batteries for its electric vehicle at its desired specifications – The quantity and quality
of its batteries are of critical importance to Tesla.
3. Accepting and processing preorders from its customers – Tesla receives some indication of the demand for
each of its products, that helps with planning.
4. Tesla markets its products – Tesla works to get Tesla products in the front of mind for its customers.
5. Tesla car and truck design – Tesla designs its automobiles in a way that will appeal to its customers (for
example, Cybertruck).
2. (LO 1.2) Explain the information value chain by summarizing how data are transformed into knowledge insights
for decision-making. Use the example of a book review on Amazon and how it might lead Amazon to decide how
many of those books to stock at its warehouses.
Suggested Solution:
Amazon allows those who purchase books and other products at its website to give product reviews and assign
product ratings. The product reviews may provide text which textual analytics could use to understand the
general sentiment about the specific book. The product rating could also be used to understand how well the
book is liked by verified buyers. Statistical correlations could be run among product review sentiment, product
ratings and product sales to help forecast demand for the product. This will help Amazon determine how many
books to keep in its warehouse ready for delivery.
This is an example of how data turns into information, knowledge and ultimately helps with decision making.
3. (LO 1.3) Explain the information value chain by summarizing how data are transformed into knowledge insights
for decision-making. Use the example of a book review of this book on Amazon and how it might help the
publisher, McGraw Hill, determine whether to revise this book for a new, updated edition as the discipline of
data analytics evolves.
.
3|Page
, Suggested Solution:
McGraw Hill will use many determinants to determine how well each one of its textbooks are performing.
They’ll look at overall sales of the book, compared to competitors. But they may also survey users to determine
how well the book is liked, what is deficient in the book, what new topics should be considered, etc. All told, all
of the data will be put together, analyzed, knowledge will be gained, and a decision will be made.
4. (LO 1.3) Explain the difference between a decision-maker, a data scientist, and a business analyst. What is the
role of each?
Suggested Solution:
While there are not always definitive distinctions between these three positions, the decision maker needs
questions answered before they can make data-informed decisions. The data scientist is most familiar with the
data, as that is their specialty, collecting and maintaining data in databases, manipulating, transforming and
analyzing data. The business analyst generally understands the business and the information needs of the
decision maker, but also understands the data. The business analyst can serve as a go between, between the
decision maker and the data scientist, all working together to make data-informed decisions.
5. (LO1.4) Compare and contrast marketing analytics with accounting analytics. How are they similar? How are
they different?
Suggested Solution:
Both marketing and accounting analytics address management questions using appropriate data and analytics.
But they also differ from each other. For example, marketing analytics are used to address the needs of the
marketing department, the business of promoting and selling products and services. Marketing analytics is
often involved in providing insights into customer preferences and trends. In contrast, accounting analytics uses
business analytics to help measure accounting performance and address accounting questions, such as analyzing
whether a company committed fraud or predicting future sales or earnings of a company.
6. (LO1.4) Compare and contrast financial analytics with operations analytics. . How are they similar? How are
they different?
Suggested Solution:
Both financial analytics and operations analytics address management questions using appropriate data and
analytics. But they also differ from each other. For example, financial analytics uses business analytics to help a
company measure and evaluate its financial performance, from predicting receivables collection from its
customers to helping management evaluate future investments based on expected investment performance. In
contrast, operations analytics uses business analytics to measure and improve the efficiency and effectiveness of
the company’s operations, since operations is all actions needed to run the company and generate income.
7. (LO 1.5) Identify the four steps in the SOAR analytics model. Explain how marketing analysts might use the SOAR
model to help Netflix better understand its customers.
.
4|Page
2nd Edition (Richardson & Watson)Chapter 1 End-of-Chapter
Assignment Solutions
Multiple Choice Questions
1. (LO 1.1) A coordinated, standardized set of activities conducted by both people and equipment to accomplish a
specific business task is called .
a. business processes
b. business analysis
c. business procedure
d. business value
2. (LO 1.2) According to the information value chain, data combined with context is
a. Information.
b. Knowledge.
c. Insight.
d. Value.
3. (LO 1.5) Which phase of the SOAR analytics model addresses the proper way to communicate results to the
decision maker?
a. Specify the question
b. Obtain the data
c. Analyze the data
d. Report the results
4. (LO 1.5) Which phase of the SOAR analytics model involves finding the most appropriate data needed to address
the business question?
a. Specify the question
b. Obtain the data
c. Analyze the data
d. Report the results
5. (LO 1.5) Which questions seek information about Tesla’s sales in the next quarter?
a. What happened? What is happening?
b. Why did it happen? What are the causes of past results?
c. Will it happen in the future? What is the probability something will happen? Can we forecast what
will happen?
d. What should we do, based on what we expect will happen? How do we optimize our performance based
on potential constraints?
6. (LO 1.5) Which questions seek information on the routing of products from Queretaro, Mexico to Chicago,
United States in the last quarter?
a. What happened? What is happening?
b. Why did it happen? What are the causes of past results?
c. Will it happen in the future? What is the probability something will happen? Can we forecast what will
happen?
1|Page
, d. What should we do, based on what we expect will happen? How do we optimize our performance based
on potential constraints?
7. (LO 1.5) Which questions ask why net income is increasing when revenues are decreasing, counter
to expectations?
a. What happened? What is happening?
b. Why did it happen? What are the causes of past results?
c. Will it happen in the future? What is the probability something will happen? Can we forecast what will
happen?
d. What should we do, based on what we expect will happen? How do we optimize our performance based
on potential constraints?
8. (LO 1.5) Which questions help managers understand how to organize future shipments based on expected
demand?
a. What happened? What is happening?
b. Why did it happen? What are the causes of past results?
c. Will it happen in the future? What is the probability something will happen? Can we forecast what will
happen?
d. What should we do, based on what we expect will happen? How do we optimize our performance
based on potential constraints?
9. (LO 1.5) Which term refers to the combined accuracy, validity, and consistency of data stored and used over
time?
a. Data integrity
b. Data overload
c. Data value
d. Information value
10. (LO 1.3) A specialist who knows how to work with, manipulate, and statistically test data is a
a. decision maker.
b. data scientist.
c. data analyst.
d. decision scientist.
11. (LO 1.4) Which type of analysts predicts the amount of money that a company will receive from its customers to
help management evaluate future investments based on expected investment performance, such as
investments in equipment or employee training?
a. Marketing analyst
b. Operations analyst
c. Financial analyst
d. Accounting analyst
12. (LO 1.4) Which type of analyst addresses questions regarding tax and auditing?
a. Marketing analyst
b. Operations analyst
c. Financial analyst
d. Accounting analyst
13. (LO 1.5) Suppose a company has timely product reviews that are available when needed, but the reviews are
biased. These product reviews are which type of data?
a. Reliable
b. Relevant
c. Curated
d. Consistent
2|Page
,14. (LO 1.6) Which common visualization type shows trends in values over time?
a. Line graph
b. Scatterplot
c. Pie chart
d. Bar chart
15. (LO 1.6) Which common visualization type shows the composition of values over time?
a. Line graph
b. Scatterplot
c. Pie chart
d. Bar chart
Discussion Questions
1. (LO 1.1) Give five examples of business processes at Tesla. How do they create business value for Tesla and its
shareholders?
Suggested Solution:
Answers will vary,
1. Tesla procures automobile parts from auto suppliers – Because of Tesla’s unique styling, getting quality
parts from its suppliers on a timely basis will support its manufacturing business.
2. Tesla manufactures batteries for its electric vehicle at its desired specifications – The quantity and quality
of its batteries are of critical importance to Tesla.
3. Accepting and processing preorders from its customers – Tesla receives some indication of the demand for
each of its products, that helps with planning.
4. Tesla markets its products – Tesla works to get Tesla products in the front of mind for its customers.
5. Tesla car and truck design – Tesla designs its automobiles in a way that will appeal to its customers (for
example, Cybertruck).
2. (LO 1.2) Explain the information value chain by summarizing how data are transformed into knowledge insights
for decision-making. Use the example of a book review on Amazon and how it might lead Amazon to decide how
many of those books to stock at its warehouses.
Suggested Solution:
Amazon allows those who purchase books and other products at its website to give product reviews and assign
product ratings. The product reviews may provide text which textual analytics could use to understand the
general sentiment about the specific book. The product rating could also be used to understand how well the
book is liked by verified buyers. Statistical correlations could be run among product review sentiment, product
ratings and product sales to help forecast demand for the product. This will help Amazon determine how many
books to keep in its warehouse ready for delivery.
This is an example of how data turns into information, knowledge and ultimately helps with decision making.
3. (LO 1.3) Explain the information value chain by summarizing how data are transformed into knowledge insights
for decision-making. Use the example of a book review of this book on Amazon and how it might help the
publisher, McGraw Hill, determine whether to revise this book for a new, updated edition as the discipline of
data analytics evolves.
.
3|Page
, Suggested Solution:
McGraw Hill will use many determinants to determine how well each one of its textbooks are performing.
They’ll look at overall sales of the book, compared to competitors. But they may also survey users to determine
how well the book is liked, what is deficient in the book, what new topics should be considered, etc. All told, all
of the data will be put together, analyzed, knowledge will be gained, and a decision will be made.
4. (LO 1.3) Explain the difference between a decision-maker, a data scientist, and a business analyst. What is the
role of each?
Suggested Solution:
While there are not always definitive distinctions between these three positions, the decision maker needs
questions answered before they can make data-informed decisions. The data scientist is most familiar with the
data, as that is their specialty, collecting and maintaining data in databases, manipulating, transforming and
analyzing data. The business analyst generally understands the business and the information needs of the
decision maker, but also understands the data. The business analyst can serve as a go between, between the
decision maker and the data scientist, all working together to make data-informed decisions.
5. (LO1.4) Compare and contrast marketing analytics with accounting analytics. How are they similar? How are
they different?
Suggested Solution:
Both marketing and accounting analytics address management questions using appropriate data and analytics.
But they also differ from each other. For example, marketing analytics are used to address the needs of the
marketing department, the business of promoting and selling products and services. Marketing analytics is
often involved in providing insights into customer preferences and trends. In contrast, accounting analytics uses
business analytics to help measure accounting performance and address accounting questions, such as analyzing
whether a company committed fraud or predicting future sales or earnings of a company.
6. (LO1.4) Compare and contrast financial analytics with operations analytics. . How are they similar? How are
they different?
Suggested Solution:
Both financial analytics and operations analytics address management questions using appropriate data and
analytics. But they also differ from each other. For example, financial analytics uses business analytics to help a
company measure and evaluate its financial performance, from predicting receivables collection from its
customers to helping management evaluate future investments based on expected investment performance. In
contrast, operations analytics uses business analytics to measure and improve the efficiency and effectiveness of
the company’s operations, since operations is all actions needed to run the company and generate income.
7. (LO 1.5) Identify the four steps in the SOAR analytics model. Explain how marketing analysts might use the SOAR
model to help Netflix better understand its customers.
.
4|Page
