Ch -5 Information Gathering Unobtrusive Methods

Unobtrusive Methods

• Less disruptive

• Insufficient when used alone

• Multiple methods approach

  • Combination of unobtrusive methods and more interactive methods

• Used in conjunction with interactive methods

Unobtrusive Methods

• Sampling

• Quantitative document analysis

• Qualitative document analysis

• STROBE

• Applying STROBE

Define what is meant by Sampling

• A process of systematically selecting representative elements of a population

• Involves two key decisions:

  • What to examine

  • Which people or entities to consider

The Need for Sampling

• Containing costs

• Speeding up the data gathering

• Improving effectiveness

• Reducing bias

Sampling Design

1. Determining the Data to Be Collected or Described

2. Determining the Population to Be Sampled

3. Choosing the Type of Sample

   1. Convenience samples: Unrestricted and non probability samples

   2. Purposive sample: based on judgement

   3. Simple random sample: the same must come from a numbered list of the population

   4. Complex random samples: Most appropriate for a systems analysts (Systematic sampling) (Stratified sampling) (Cluster Sampling)

4. Deciding on the Sample Size

Four main types of samples the analyst has available

Convenience

• Not based on probability

• Sample elements are selected directly w/out restrictions

Purposive

• Not based on probability

• Sample elements are selected according to specific criteria

• Not wholistic

Simple random

• Based on probability

• Sample elements are selected directly w/out restrictions

• Not good for being comprehensive

Complex random (systematic, stratified [categories & randomize], and cluster[geography & location])

• Based on probability

• Sample elements are selected according to specific criteria

• Should use a complex random if possible

What are the three approaches to complex random sampling?

Systematic sampling

• Choose to interview every kth person on a list of company employees

Stratified samples

• Stratification is the process of identifying subpopulations or strata and then selecting objects or people for sampling in these subpopulations

• Essential to gath data efficiently

Cluster sampling

• Select a group of people or documents to study

Define what is meant by stratification of sampless?

researchers divide subjects into subgroups called strata based on characteristics that they share

The Sample Size Decision

1. Determine the attribute (the type of errors to look for)

2. Locate the database or reports in which the attribute can be found

3. Examine the attribute (Estimate p, the proportion of the population having the attribute)

4. Make the subjective decision regarding the acceptable interval estimate, i.

5. Choose the confidence level and look up confidence coefficient (z value) in a table

6. Calculate the standard error

   1. standard error = i/z

7. Determine the sample size

   1. n = p(1-p)/standard error²p + 1

What effect on sample size does using a greater confidence level have when sampling attribute data?

Confidence level

• Desired degree of certainty, such as 95%. Once confidence is chose,, the confidence coefficient (also called a z value) can be looked up in a table similar to the one found in this chapter)

Calculate the Standard Error of the Proporrtion

• sp= i/z

• i = interval estimate

• z = confidence coefficient found in the confidence level lookup table

Determine the sample size

standard error = i/z

n = p(1-p)/standard error²p + 1

1) Determine which attribute to sample

2) Find where data in stored

3) estimate p (proportion of population to set appropriate sample size)

4) interval estimate ±0.10 means analyst willing to accept an error of no more than 0.10 in either direction from the actual proportion,p

5) Confidence level is desired degree of certainty, such as 95%. Once chose, confidence coefficient (z value) can be looked up in a table

6)Take the parameters found or set in steps 3 through 5

7) Enter them into two equatios to eventually solve the required sample size

Example: Area Under Curve to find the necessary sample size

1. Determine that you will be looking for orders that contain mistakes in names, addresses, quantities, or model numbers.

2. Locate copies of order forms from the past six months.

3. Examine some of the order forms and conclude that only about 5 percent contain errors.

4. Make a subjective decision that the acceptable interval estimate will be

5. Choose a confidence level of 95 percent. Look up the confidence coefficient ( value) in Figure 5.2. The value equals .

A table of area under a normal curve can be used to look up a value once the systems analyst decides on the confidence level

What is the overriding variable that determines how many people a systems analyst should interview in depth?

The time an interview takes

• A good rule of thumb is to interview at least 3 people at every level of the org and at least one from each of the org’s functional areas

Practice (1)

8%

CL = 99%

i = 0.02

Z = 2.58

How large a sample size should Leigh use to be 99% certain the interval estimate will be with + or 0.02?

8%

CL = 99%

i = 0.02

Z = 2.58

standard error = i/z = 0.02/2.58 = 0.00775

n(sample size) 0.08 × 0.92/(0.00775)² + 1. = 1,226

n = 1,226

How large a sample size should Leigh use to be 90 percent certaint he interval estimate will be with or 0.02

CL = 90%

i - 0.02?

Z = 1.65

Standard error = 0.02/1.65 = 0.01212

n = p(1-p)/standard error²p + 1

0.08(0.92)/0.0001468944 + 1 = 0.0736/0.0001468944 = 501.04 + 1 = 502

n = 502

Analyzing Quantitative Documents

• Reports used for decision making

  • Sales reports

  • Production reports

  • Summary reports

• Performance reports

  • Shows goals and trends

• Records

  • Provides periodic updates of what is occurring in the business

  • Manually completed payment records

    • 1. Check for errors in amounts and totals

    • 2. Looking for opportunities fo riproving the recording form design

    • 3. Observing the number and type of transactions

    • 4. Watching for instances in which the computer can simplify the work through calculations and other data manipulation

• Data capture forms

  • 1. Collect examples of all type of forms in use

  • 2. Note the type of form

  • 3. Document the intended distribution pattern

  • 4. Compare the intended distribution pattern with who actually receives the form

• E-commerce and other transactions

Systematically Examining Quantitative Documents

Performance Reports

• Indicate what’s going wrong and opportunities to improve

Records

• Provides periodic updates of what is occurring in the business

• Manually completed payment records

  • 1. Check for errors in amounts and totals

  • 2. Looking for opportunities fo riproving the recording form design

  • 3. Observing the number and type of transactions

  • 4. Watching for instances in which the computer can simplify the work through calculations and other data manipulation

Data Capture Forms

scanning paper forms, capturing information from invoices or insurance claims, extracting text from ID cards, and automatically recognizing handwritten characters. Technologies such as barcode scanners, document scanners, or OCR scanners enable such data capture.

Analyzing Qualitative Documents

• 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 and memos

• Signs or posters on bulletin board

• Corporate Web sites

• Manuals

• Policy handbooks

Systematically Examining Qualitative Documents

1. Examine documents for key or guiding metaphors

2. Look for insiders versus outsiders or an “us against them” mentality

3. List terms that characterize good or evil and appear repeatedly in documents

4. Look for the use of meaningful messages and graphics posted on common areas or on web pages

5. Recognize a sense of humor if present

Memos

• Analysis of memos provides insight into the metaphors that guid the organizations thinking

  • Values, attitudes, and beliefs

Signs or Posters on Bulletin Boards or in Work Areas

• Posted signs reveal the official organizational culture

Corporate Websites

• Must provide context required to go to next stage in process

• Technical, Aesthetics, Managerial

• Business to consumer ecommerce (B2C) as well as those used for business-to-business ecommerce (B2B) examine the contents for metaphors, humor, use of design features (color, graphics, animation, and hyperlinks)and the meaning and clarity of any messages provided

Manuals

Analyze manuals following the five guidelines spelled out previously. Remember that manuals present the “ideal” the way machines and people are expected to behave

Policy Handbooks

Address policies about computer servics, use, access, security, and charges

Using Text Analytics

Software that can analyze qualitative data from any unstructured written source including transcripts of interviews, written reports, or customers’ communication collected through email, wikis, blogs, chat rooms, etc.

• Leximancer

  • performs keyword count, shows ranked cocnepts for Open Source Communities project

Process Mining

Unobtrusively and automatically gather data about processes from enterprise systems like SAP and others.

• Record all activities, which are the data used in process mining

Steps to process mining:

1. Discover

   1. Process mining appreads the data colllected from enter. systems and creates an event log

2. Optimize/Automate

   1. Improvement takes place

3. Monitor

   1. Systems anlayst needs to observe and determine what effect the optimize/automate phase had on the path

4. Act

   1. Incentives to move forward with any changes that are needed based on previous steps

Workforce Analytics

1. Ensure the right workers are in the right place

2. Balancing the workload among the staff

3. Comparing workers’ or team’s performance

4. Realizing where bottlenecks in workflows occur

5. Determining which apps are used more than others

6. Realizing which apps deliver more productvity

Understanding application usage and website visits

Possible to identify what activities are consuming the most amount of time

• Identify distractions

• determine redundant functions

Identifying When and Why Workers Lose Focus

• Useful in increasing future productivity and improve performance

Comparing the Performance of Teams

• See how teams can improve for comparison

Observing a Decision Maker’s Behavior

• Can see firsthand the relationships that exist between decision makers and other members of the org

Observing a Typical Manager’s Decision-Making Activities

Observation allows the analyst to see firsthand how managers gather, process, share and use info and tech to get work done

• analyst playscript

  • actor [ decision maker

Observing The Physical Environment

• Reveals their human info requirements

• offices, workplace, HCI concerns

Structured Observation of the Environment

• STROBE Method

Applying STROBE

Requrest an analys texplicitly observe seven concrete elements ocmmonly found in offices

STROBE

Structured

Observation of the

Business Environment

Text Mining

• Leximancer

• NVivo

  • Removes conjuncted words

Process Mining

• Solutions

  • SAP

  • Salesforce

  • Oracle

  • Celonis

• Steps

  • Discover

  • Optimize/Automate

  • Monitor

Other Decision Making Activities

Task mining

An unobtrusive desktop capture of the tasks performed by an organization’s employees