Decision Analysis

3574 words - 15 pages

Decision Analysis Model and Report

JaKaiser Smith
Southern New Hampshire University
Date: 07/09/2015

Abstract
In this report following resources have been utilized to establish a relationship between Retail Salesperson’s salaries and their intent to shoplift at their own workplace:

* The Larceny theft data from Federal Bureau of Investigation’s official website for the years 2011, 2012 and 2013;
* 25th and 26th Annual Retail Theft Surveys by Hayes International for the years 2011, 2012 and 2013;
* National Conference of State Legislatures website for Labor and employment data for the years 2011, 2012 and 2013.

‘Shoplifting’ is undoubtedly a psychological issue ...view middle of the document...

e., shoplifting instances per 10,000 Retail salesperson.

Table 1 Research Analysis Synopsis (Year: 2013)
The Table 1 above summarizes the findings from this project. Here A_PCT10, A_PCT25, A_MEDIAN represents average 10th percentile, 25th percentile and Median salaries of Retail Salesperson for the year 2013 respectively. There is a small yet clear disparity between the salaries where shoplifting instances are less than or equal to 378 and that where the same is greater than 378. When the salaries are at the extreme low end of the spectrum even a difference of $100 makes a lot of difference in the life of an individual!

Table of Contents
Introduction 4
Research Question 4
Data Appraisal 5
Techniques 6
Evaluation 7
Model 8
Results 10
Limitations 11
References 12
Annexures 13

Figure 1 Decision Tree (Scenario#1) Year: 2013 8
Figure 2 Decision Tree (Scenario#2) Year: 2013 9
Figure 3 Colour key for Decision Tree (Scenario#2) Year: 2013 9
Figure 4 Resultant values from the two Decision Trees 10
Figure 5 Sensitivity Analysis (as per A_PCT10 in Decision Tree#2) 10
Figure 6 Shoplifting rate graph 13

Table 1 Research Analysis Synopsis (Year: 2013) 2
Table 2 Core Values used for plotting Decision Trees (Year: 2013) 7
Table 3 Core Values used for plotting Decision Trees (Year: 2012) 7
Table 4 Master Data-set 14

Introduction

‘Shoplifting’ is a major crime in the USA today. According to the data sets used in this project, it has been estimated that the annual shoplifting losses in the USA amounts to be greater than $13,000,000,000! On an average an employee shoplifts products worth $715 dollars whereas the average amount shoplifted by an External customer is around $129. This is confirmed by the fact that Employee theft contributes 43% and shoplifting contributes 37% to the overall Retail shrink in the USA. The overall Retail shrink in USA is measured at around 1.48% of the total Retail sales. For example, the Retail sales in the USA for the year 2014 was around $4.732 trillion, therefore, the Retail Shrink during that year would have been $70,033,600,000! Even though technologies like Smart Tagging, Entry sensors, and Source tagging have been deployed but still the numbers don’t cease to proliferate.
This analysis is specific to Retail Salesperson, the front-end force of people who drives the sales in the stores. The intended population for this analysis is that of the Retailers who always have a hard time in figuring out the ways to minimize the store shrinkage. As the Store management team are reasonably well paid, well-educated and need to set an example for these Sale-force, the personnel responsible for store shrink have solely been considered to be Retail Salesperson (OCC Code: 41-2031). All the data pertaining to ‘Retail Salesperson’ is used in this research (e.g., number of employees and their current pay for the year 2011-13). The latest available data are that of the year 2013, therefore,...

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