chapter 4 (information gathering: unobstructive methods)

Question 1

Unobtrusive Methods

Answer 1

• Less disruptive
• Text analytics to analyze qualitative data
• Insufficient when used alone
• Multiple methods approach
• Used in conjunction with interactive methods

Question 2

Sampling

Answer 2

A process of systematically selecting representative
elements of a population

Question 3

Involves two key decisions:

Answer 3

– What to examine
– Which people to consider

Question 4

The reasons systems analysts do sampling are to

Answer 4

– Contain costs
– Speed up data gathering
– Improve effectiveness
– Data gathering bias can be reduced by sampling

Question 5

Too costly to

Answer 5

– Examine every scrap of paper
– Talk with everyone
– Read every Web page from the organization

Question 6

Sampling

Answer 6

• Sampling helps accelerate the process by gathering
  selected data rather than all data for the entire population
• The systems analyst is spared the burden of analyzing
  data from the entire population

Question 7

Sampling Effectiveness

Answer 7

• Sampling can help improve effectiveness if information
  that is more accurate can be obtained
• This is accomplished by talking to fewer employees but
  asking them questions that are more detailed
• If fewer people are interviewed, the systems analyst has
  more time to follow up on missing or incomplete data

Question 8

Sampling Bias

Answer 8

• Data gathering bias can be reduced by sampling
• When the systems analyst asks for an opinion about a
  permanent feature of the installed information system, the
  executive interviewed may provide a biased evaluation
  because there is little possibility of changing it

Question 9

To design a good sample, a systems analyst must follow
four steps:

Answer 9

– Determining the data to be collected or described
– Determining the population to be sampled
– Choosing the type of sample
– Deciding on the sample size

Question 10

Four Main Types of Samples

Answer 10

• Convenience
• Purposive
• Simple random
• Complex random

Question 11

Convenience Samples

Answer 11

• Convenience samples are unrestricted, nonprobability
  samples
• This sample is the easiest to arrange
• The most unreliable

Question 12

Purposive Sample

Answer 12

• A purposive sample is based on judgment
• Choose a group of individuals who appear
  knowledgeable and are interested in the new information
  system
• A nonprobability sample
• Only moderately reliable

Question 13

Complex Random Samples

Answer 13

• The complex random samples that are most appropriate
  for a systems analyst are
  – Systematic sampling
  – Stratified sampling
  – Cluster sampling

Question 14

The Sample Size Decision

Answer 14

• Determine the attribute
• Locate the database or reports in which the attribute can
  be found
• Examine the attribute
• Make the subjective decision regarding the acceptable
  interval estimate
• Choose the confidence level
• Calculate the standard error
• Determine the sample size

Question 15

Investigation

Answer 15

• The act of discovery and analysis of data
• Hard data
  – Quantitative
  – Qualitative

Question 16

Analyzing Quantitative Documents

Answer 16

• Reports used for decision making
• Performance reports
• Records
• Data capture forms
• Ecommerce and other transactions

Question 17

Reports Used for Decision Making

Answer 17

• Sales reports
• Production reports
• Summary reports

Question 18

Records

Answer 18

Records provide periodic updates of what is occurring in
the business

Question 19

There are several ways to inspect a record:

Answer 19

– Checking for errors in amounts and totals
– Looking for opportunities for improving the recording
form design
– Observing the number and type of transactions
– Watching for instances in which the computer can
simplify the work (calculations and other data
manipulation)

Question 20

Data Capture Forms

Answer 20

• Collect examples of all the forms in use
• Note the type of form
• Document the intended distribution pattern
• Compare the intended distribution pattern with who
  actually receives the form

Question 21

Analyzing Qualitative Documents

Answer 21

• Key or guiding metaphors
• Insiders vs. outsiders mentality
• What is considered good vs. evil
• Graphics, logos, and icons in common areas or web
  pages
• A sense of humor
• Email messages
• Memos
• Signs or posters on bulletin boards
• Corporate Web sites (note the interactivity of Web sites)
• Manuals
• Policy handbooks

Question 22

Text Analytics
Software that can analyze unstructured qualitative data
from any source including:

Answer 22

– Transcripts of interviews
– Written reports
– Customers’ communication collected through email,
wikis, blogs, chat rooms, and other social networking
sites

Question 23

Text Analytics
Unstructured, qualitative, or “soft” data are generated
through:

Answer 23

– Blogs
– Chat rooms
– Questionnaires using open-ended questions
– Online discussions conducted on the Web
– Exchanges occurring on social media

Question 24

Text analytics can realize valuable insights into

Answer 24

– What customers are thinking about the organization,
the values and actions of the company
– Customer or vendor motivations for beginning,
maintaining, improving, or discontinuing a relationship

Question 25

Text Analytics

Answer 25

* Text analytics provide insights for an organization’s members who want to have a rapid and visual yet decidedly qualitative approach to analyzing text data * An important element is to design the human activities surrounding the use of text analytics software

Question 26

Observation

Answer 26

* Observation provides insight on what organizational members actually do * See firsthand the relationships that exist between decision makers and other organizational members * Can also reveal important clues regarding HCI concerns

Question 27

Analyst’s Playscript

Answer 27

Involves observing the decision-makers behavior and recording their actions using a series of action verbs

Question 28

Examples Analyst’s Playscript

Answer 28

– Talking – Sampling – Corresponding – Deciding

Question 29

STROBE

Answer 29

STRuctured OBservation of the Environment—a technique for observing the decision-maker’s physical environment Often it is possible to observe the particulars of the surroundings that will confirm or negate the organizational narrative – Also called stories or dialogue – Information that is found through interviews or questionnaires

Question 30

STROBE elements

Answer 30

* Office location * Desk placement * Stationary equipment * Props * External information sources * Office lighting and color * Clothing worn by decision makers

Question 31

Office Location

Answer 31

* Who has the corner office? * Are the key decision makers dispersed over separate floors?

Question 32

Desk Placement

Answer 32

* Does the placement of the desk encourage communication? * Does the placement demonstrate power?

Question 33

Stationary Office Equipment

Answer 33

* Does the decision maker prefer to gather and store information personally? * Is the storage area large or small?

Question 34

Props

Answer 34

* Is there evidence that the decision maker uses a PC, smart phone, or tablet computer in the office?

Question 35

External Information Sources

Answer 35

Does the decision maker get much information from external sources such as trade journals or the Web?

Question 36

Office Lighting and Color

Answer 36

* Is the lighting set up to do detailed work or more appropriate for casual communication? * Are the colors warm and inviting?

Question 37

Clothing

Answer 37

* Does the decision maker show authority by wearing conservative suits? * Are employees required to wear uniforms?

Question 38

The five symbols used to evaluate how observation of the elements of STROBE compared with interview results are:

Answer 38

– A checkmark means the narrative is confirmed – An “X” means the narrative is reversed – An oval or eye-shaped symbol serves as a cue to look further – A square means observation modifies the narrative – A circle means narrative is supplemented by observation