Do you think Money Grows on Trees?

SUSAN FORGETT RHEAM MARIE HAYES

EMPLOYEE THEFT SURVEY ANALYSISMBA 512

APRIL 28, 2010

Topic Overview

• It is no secret that employees routinely steal from their employers.

• Thefts of:– Money– Time– Supplies– Merchandise– Company Property

Constitute use or misuse of an employer’s assets or resources without permission to do so.

Employee Theft Information

• U.S. Chamber of Commerce reports:Thefts cost U.S. companies between an estimated

$20 and $40 billion each year.This translates into roughly $400 for every working

American.An estimated 75% of all employees steal at least

once, and that ½ of these steal again and again.One out of every three business failures are the

direct result of employee theft.

Why this topic?

• January 5, 2010 DailyFinance.com article:Koss Corp. Fires Auditor as Alleged Fraud Loss Widens to

$31 Million• The 17 year CFO was highly trusted and given a lot

of autonomy in her function as head of the finance team.

“Anyone conducting alleged transfers of this size would have to be awfully confident that no one else was looking at the bank records, as transfers so large typically would be noticed.”

Research Question

• Will enhanced monitoring discourage employee theft?

• Relevant factors:– Demographics– Employee theft– Perceptions of stealing– Awareness of employer monitoring– Sensitivity to employer monitoring

Research Hypothesis

When employees know that their activities are carefully monitored, they are less likely to commit theft on the job.

DATA COLLECTION & PREPARATION

• A 10 QUESTION SURVEY TO INVESTIGATE THE TOPIC WAS USED TO POLL RESPONDENTS

• A VARIETY OF QUESTION & ANSWER TYPES USED SUCH AS:• DEMOGRAPHIC- MULTIPLE CHOICE-SINGLE RESPONSE

& SIMPLE CATEGORY SCALE• BEHAVIORAL-SIMPLE CATEGORY SCALE, MULTIPLE

CHOICE-MULTIPLE RESPONSE & RATING RESPONSE STRATEGY

• OPINION- MULTIPLE CHOICE-SINGLE RESPONSE & MULTIPLE CHOICE-MULTIPLE RESPONSE

SURVEY DESCRIPTION• FIRST-DEMOGRAPHIC QUESTIONS TO CONFIRM

THAT WE REACHED OUR TARGET AUDIENCE

• INCLUDED QUESTIONS ON:• AGE• GENDER• EMPLOYMENT STATUS –HOURLY, SALARIED, SELF, NOT

WORKING• POSITION-- ENTRY, MID, SUPERVISORY, SENIOR &

EXECUTIVE

SURVEY DESCRIPTION• NEXT-BEHAVIORAL QUESTIONS TO GAUGE HOW

RESPONDENTS ACT IN CERTAIN SITUATIONS

• INCLUDED QUESTIONS DESIGNED TO GATHER INFORMATION:• ARE RESPONDENTS CURRENTLY BEING MONITORED AT

WORK?• WHAT ARE RESPONDENT’S REACTIONS TO CHANGES IN

MONITORING ACTIVITIES AT WORK?

SURVEY DESCRIPTION• NEXT-OPINION QUESTIONS TO OBTAIN

INFORMATION ON RESPONDENT’S PERCEPTIONS OF THEFT AND MONITORING

• INCLUDED QUESTIONS DESIGNED TO GAUGE SENSITIVITY:• PERCEPTIONS ON WHAT CONSTITUTES STEALING FROM

AN EMPLOYER• COMFORT LEVELS WITH MONITORING• IMPACT OF INCREASED LEVELS OF MONITORING ON THEFT

PREVENTION

DATA COLLECTION

TARGET AUDIENCE -PEOPLE OVER 18 WHO ARE (OR WERE) EMPLOYED• GOAL TO COLLECT SAMPLE OF GREATER THAN 50

RESPONDENTS

METHOD OF SURVEY ADMINISTRATIONSAMPLING PLAN USED:

• SNOWBALLING, RANDOM SAMPLING PLAN• ANONYMOUS = HONESTY

DELIVERY METHOD

• PHYSICAL DISTRIBUTION OF PRINTED SURVEYS– SURVEYS HANDED TO PEOPLE WE KNEW– RECRUITING FROM ACQUAINTANCES TO REACH

ADDITIONAL RANDOM INDIVIDUALS• DISTRIBUTED 167 SURVEYS:

SELF-ADDRESSED STAMPED ENVELOPE TO A P.O. BOX

• GOAL TO COVER OUR GENERAL DEMOGRAPHIC AREA: WILKES BARRE - HAZLETON – BLOOMSBURG -

SELINSGOVE

SUMMARY OF RESPONDENTS

• DETERMINE GEOGRAPHIC LOCATION BY POSTMARK ON RETURNED ENVELOPES

• POTENTIAL RESPONDENTS OUTSIDE OF TARGET AREA A RESULT OF USING SNOWBALL SAMPLING METHOD

• 66 RESPONDENTS OF 167 ≈ 39.5%**IF ALL 167 WERE DISTRIBUTED

Geographic Location

Wilkes-Barre

Scranton

Harrisburg

Lehigh Valley

Syracuse

Reading

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00

Number of Respondents

Post

mar

k

Potential Sources of Error• FULL DISTRIBUTION OF SURVEYS BY

ACQUAINTANCES UNKNOWN• CERTAIN RESPONDENTS LEFT QUESTIONS

BLANK• WORDING OF CERTAIN QUESTIONS OR

QUESTION RESPONSE OPTIONS MAY HAVE BEEN CONFUSING TO RESPONDENTS

Descriptive Statistical Analysis

• Demographics of respondents:– Gender and age– Employment status and position– Geographic location

• Behavior of respondents:– Admissions of theft

• Perceptions of respondents:– Theft considerations– Monitoring awareness and sensitivity

Survey Respondents: 66 Total

32%

52%

17%

Gender

Male

Female

(Blank)

20%

12%

23%

23%

23%

AGE

18-26 yrs

27-35 yrs

36-43 yrs

44-52 yrs

52-up yrs

Employment Status

Not currently working

Employee paid hourly

Salaried employee

Self-employed0

5

10

15

20

25

30

35

40

2

20

38

6

Num

ber o

f Res

pond

ents

Position at Work

Entry level Mid-level Supervisory Senior mgmt Executive mgmt

0

5

10

15

20

25

30

Total 4Num

ber o

f Res

pond

ents

Theft of Office Supplies

National survey of 2,137 employed adults reported 19% of workers stealing office supplies (May, 2008) Our survey respondent’s admission of taking home company office supplies for personal use: 15 / 66 = 23%

Entry-le

vel

Mid-le

vel

Supervi

sory

Senior m

gmt

Execu

tive m

gmt

0.00

0.10

0.20

0.30

0.40

0.50

0.60

Total 0.50

Employee Position

% o

f res

pond

ents

Perceptions: Stealing?

Entry-le

vel

Mid-le

vel

Supervi

sory

Senior m

gmt

Execu

tive m

gmt

0%10%20%30%40%50%60%70%80%90%

Personal callsUse of softwareComputer fun workingComputer fun lunch

% o

f Res

pond

ents

Monitoring Awareness & Sensitivity

No39%

Yes45%

Don't

know

15%

Are you currently being monitored at work?

Con-cerned

14% Don't care18%

Un-con-

cerned68%

Reaction to increased monitoring at work

Respondent Interpretation

• 51% female, 32% male• Very equal cross-section of age categories• Majority salaried employees in mid-level positions• Geographic concentration in Central PA• 23% taken home company office supplies• Over 45% felt stealing included theft of time and

personal use of company software• 46% are currently being monitored at work• 68% unconcerned about increased monitoring

Hypothesis Testing:Monitoring Concerns

• Are workers who are not currently monitored on the job as unconcerned about increased monitoring as workers who are already being monitored?

• Two-sample hypothesis test for the difference between proportions (sample size > 30):– NULL:p1 = p2– ALT: p1 <> p2

• Two-tail test

HYPOTHESIS TESTx-value sample

1 26x-value

sample 2 22

sample size 1 30 sample size 2 26pooled proportion 0.857 proportion 1 0.8667 proportion 2 0.8462

std error 0.094

NULL: 1 = 2p pThere is no difference in perception of increased monitoring between monitored and unmonitored workers

ALTERNATIVE: 1 < > 2p pThere is a difference in perception of increased monitoring between monitored and unmonitored workers

one-tailed or two tailed? 2

test statistic (obs)

0.219 CONCLUSION

critical measure

1.960 Do not reject the Null Hypothesis

|obs| > critical?? NO

People who are not currently monitored at work are just as comfortable with the idea of increasedmonitoring as people who are currently monitored at work.p-value

0.827

a-level

0.050 p-value < a-level?? NO

Hypothesis Testing:Personal Use of Work Computer

• Will most people stop using their company computer for personal fun during work time with increased monitoring?

• One-sample hypothesis test for the population proportion (sample size > 30):– NULL:p > = .5– ALT: p < .5

• One-tail test as direction implies

HYPOTHESIS TESThypothesized

valuesample

proportion xsample

size std error

for the proportion 0.5 0.60606 40 66 0.061545745

NULL : > = .50pMost people will not stop using their work computer for personal fun with increased monitoring

ALTERNATIVE: < .50p

Most people will stop using their work computer for personal fun with increased monitoring

test statistic (obs)

1.723

critical measure

1.645

one-tailed or two-tailed? 1

|obs| > critical? YES

p-value 0.0424188 CONCLUSION

a-level

0.050 Reject the Null Hypothesis

p-value < a-level? YES

Most people will stop using their work computer for personal fun with increased monitoring

Hypothesis Testing:More Frequent Monitoring

• Respondents asked what they thought the impact on theft prevention would be with more frequent monitoring of work activities:1. Have no impact on theft prevention2. Might help theft prevention3. Would greatly help theft prevention

Hypothesis Testing:More Frequent Monitoring

• One-sample hypothesis test for the population proportion (sample size > 30):– NULL:p > = .5– ALT: p < .5

• One-tail test as direction implies

HYPOTHESIS TESThypothesized

valuesample

proportion xsample

size std error

for the proportion 0.5 0.86364 57 66 0.061545745

NULL : > = .50pMost people feel frequent monitoring of work activities will not prevent theft

ALTERNATIVE: < .50pMost people feel frequent monitoring of work activities will prevent theft

test statistic (obs)

5.908

critical measure

1.645

one-tailed or two-tailed? 1

|obs| > critical? YES

p-value 0.0000000017 CONCLUSION

a-level

0.050 Reject the Null Hypothesis

Most people feel frequent monitoring of work activities will prevent theft

p-value < a-level? YES

Summary of Hypothesis Testing

• Majority of workers are not resistant to increased monitoring:Even if they are not currently being monitored.

• 56% of respondents felt that using the company computer for personal fun during work time was stealing from an employer:Most people will stop using their work computer for

personal fun with increased monitoring.• Most people feel that frequent monitoring of work

activities would greatly help theft prevention.

LINEAR REGRESSION ANALYSIS

GOAL IS TO FIND IF ANY RELATIONSHIPS EXIST BETWEEN VARIOUS THEFT VARIABLES VS. MONITORING OR CHECKING

The dependent variables in the following 3 scenarios are: #1 Theft of supplies-do they take home company supplies#2 Stop Theft-would they stop personal computer activity#3 During Lunch-would they only use the computer for personal

during lunch

The Independent variables used were:Checking-someone is checking work activitiesMonitoring-someone is monitoring work activities

HYPOTHESIS

SCENARIO #1

• NULL: THEFT OF SUPPLIES IS NOT AFFECTED BY CHECKING

• ALT: THEFT OF SUPPLIES IS AFFECTED BY

CHECKING

LINEAR REGRESSION-SCENARIO #1

SCENARIO #1 INTERPRETATION

THE VARIABLE THAT IS SIGNIFICANT:CHECKING IS A SIGNIFICANT VARIABLE IN

RELATION TO THEFT OF SUPPLIES BECAUSE THE p-value .02 <α .05

HOW DOES THEFT BEHAVIOR CHANGE WITH EACH OF THE RELEVANT VARIABLES?

FOR EACH ADDITIONAL UNIT OF CHECKING; THEFT DECREASES

SCENARIO #1 INTERPRETATION

RELEVANCE OF METHODS/DISCUSSION:

HOW RELIABLE IS YOUR MODEL? • IT IS 7.7% RELIABLE TO PREDICT DECREASE IN

THEFT

• MULTIPLE R: 0.277-Correlation Co-efficient Close to 1 =good

HYPOTHESIS

SCENARIO #2 & #3#2 HO1

NULL: STOPPING PERSONAL USE IS NOT AFFECTED BY MONITORING

ALT: STOPPING PERSONAL USE IS AFFECTED BY MONITORING

#3 HO2

NULL: USING A COMPUTER FOR PERSONAL USE DURING LUNCH IS NOT AFFECTED BY MONITORING

ALT: USING A COMPUTER FOR PERSONAL USE DURING LUNCH IS AFFECTED BY MONITORING

LINEAR REGRESSION-SCENARIO #2 & #3

SCENARIO #2 SCENARIO #3

SCENARIO #2 & #3 INTERPRETATION

THE VARIABLE THAT IS SIGNIFICANT:

#2 HO1

MONITORING IS NOT A SIGNIFICANT VARIABLE IN RELATION TO STOPPING PERSONAL USE BECAUSE THE p-value .77262 is NOT <α .05

#3 HO2

MONITORING IS NOT A SIGNIFICANT VARIABLE IN RELATION TO USING A COMPUTER FOR PERSONAL USE DURING LUNCH BECAUSE THE p-value .4037 is NOT <α .05

SCENARIO #2 & #3 INTERPRETATION

RELEVANCE OF METHODS/DISCUSSION:HOW RELIABLE IS YOUR MODEL?

#2 HO1

• IT IS 1.3% RELIABLE

#3 HO2

• IT IS 1.09% RELIABLE

GRAPHICAL REPRESENTATION

-1.5 -1 -0.5 0 0.5 1 1.50

0.20.40.60.8

11.2

Monitoring (1,0,-1) Line Fit Plot

# Stop (1,0)Predicted # Stop (1,0)

Monitoring (1,0,-1)

# St

op (1

,0)

#3 HO2

-1.5 -1 -0.5 0 0.5 1 1.50

0.20.40.60.8

11.2

Monitoring (1,0,-1) Line Fit Plot

# Lunch (1,0)Predicted # Lunch (1,0)

Monitoring (1,0,-1)

# Lu

nch

(1,0

)

#2 HO1

CONCLUSIONS

• RESPONDENTS WERE FAIRLY CONSISTENT IN THEIR PERCEPTIONS OF

WHAT CONSTITUTES THEFT

• MAJORITY OF WORKERS ARE NOT RESISTANT TO INCREASED

MONITORING

• USING A WORK COMPUTER FOR PERSONAL FUN IS EXPECTED TO DECLINE WITH INCREASED MONITORING

• FREQUENT MONITORING OF WORK ACTIVITIES APPEARS TO GREATLY

HELP THEFT PREVENTION

• THERE IS A RELATIONSHIP BETWEEN THEFT OF OFFICE SUPPLIES AND

SOMEONE CHECKING WORK ACTIVITIES

CONCLUSIONS

• Our prediction about what we expected to happen in the study as stated in our research hypothesis is supported by the data collected and tested.

When employees know that their activities are carefully monitored, they are less likely to commit theft on the job.

RECOMMENDATIONS

• REVISE SOME QUESTIONS TO BETTER ACHIEVE DATA COLLECTION FOR REGRESSION MODELS

• COLLECT MORE SPECIFIC DATA RELATED TO TIME THEFT• AMOUNT OF TIME SPENT ON PERSONAL CALLS,

FACEBOOK, ETC.

• EXPAND GEOGRAPHIC AREA BY DISTRIBUTING SURVEYS ONLINE

REFLECTIONS

SAMPLING PLAN WAS EFFECTIVE FOR SURVEY

RESPONSE

SAMPLE COLLECTED WAS SUITABLE FOR OUR

PURPOSES

DATA COLLECTED WAS OF GOOD QUALITYTHERE ARE MANY MORE ISSUES RELATING TO

THIS TOPIC THAT CAN BE RESEARCHED

The End

Questions?