UWProjectHandoffReport

Project Handoff Report: Secure Service Route Assess A Risk Evaluation Tool for High-Security Transcontinental Freight Forwarding in the U.S.

Sponsored by the University of Washington Information School and Expeditors International

Andrew Caldwell: [email protected]

Victor Li: [email protected]

Maulik Mishra: [email protected]

Jill Schulze: [email protected]

May 31, 2015

TABLE OF CONTENTS

Executive Summary

Specifications (In-Scope and Out-of-Scope Deliverables)

In-Scope

Out-of-Scope

Limitations

Data Sources

Yahoo Weather API (https://developer.yahoo.com/weather/)

FBI Crime Statistics for 2013 (http://www.fbi.gov/stats-services/crimestats)

Freightwatch International (http://www.freightwatchintl.com/)

“Sandbox” Expeditors’ Insurance Claims

Expeditors’ Mitigation Offerings

Route Assess Guide

Main Menu Spreadsheet

Step 1) Select the states and cities along the shipment route

Step 2) Choose the type of commodity being shipped

Step 3) Request weather forecast

Weather: Step A

Weather: Step B

Weather: Step C

Weather: Step D

Step 4) Select mitigation products

Mapping a Route

Generating a Customer Report

Risk Scoring

Commodity Scoring

Crime Scoring & Weights

Mitigation Scoring & Weights

Weather Scoring

Overall Score

Data Maintenance and Additions

Hand-over of Project Ownership

Future Team Obligations

Intellectual Property Rights

Appendix

1 | Secure Service Route Assess

Executive Summary The partnership established during this 2015 capstone project between the University of Washington

Information School and Expeditors International of Washington has been focused on researching,

developing, and testing a methodology of risk as it applies to freight forwarding in the continental

United States. Over the span of 5 months, from January through May, industry and academic experts

have leveraged their knowledge and time towards the development of an internal assessment tool

described within this document. As the project draws to a close it is the intent of the UW Information

School and its graduate students who have worked on this project to transfer full knowledge and

disclosure of the resulting framework and tool to the corporate sponsor of Expeditors International.

Our initial project objectives were as follows:

● Create a framework for analysts to measure and communicate risk internally

● Bring greater visibility to supply chain risk for Expeditors’ customers

● Investigate what free data resources exist that can be applied to meet these goals

The purpose and objectives of this project have stemmed from the new Secure Service offering of

Expeditors, which aims to provide high-security transportation and delivery to its customers. In order

to do so, the company’s Security Analysts need the ability to review commodity and route information

to assess threats and vulnerabilities prior to moving freight, so risk mitigation strategies can be

tailored to each individual shipment, depending on a customer’s risk appetite. Knowing Expeditors’

Secure Service is rapidly evolving in terms of its product sophistication and customer base, it has been

the goal of project team members to build a framework and tool that is operating system agnostic

and requires no additional software or hardware purchases for the company.

Note: In light of NDA obligations and protection of the proprietary nature of the tool, the Excel

workbook containing actual Route Assess data is not included in this report. Sections of the tool have

been described where context is necessary, but it should be noted that neither the data set nor the

tool’s internal functioning are fully explained.

Specifications (In-Scope and Out-of-Scope Deliverables) While the project has been largely student-directed with limited company oversight, it has been a goal

of the capstone team to provide a relevant and useful end product to Secure Service. The project

charter agreed upon did not outline specific technology or software outcomes, however the

team--with the approval from Secure Service--has moved forward with constructing a risk assessment

framework in Microsoft Excel. The benefit of implementing a framework on this common business

software is multifaceted: 1) it requires no new software licenses for employees to use, 2) given the

current volume of data used for assessment, it can efficiently compute risk scores, 3) it can generate

customer-facing reports, 4) It is easy to transition a concept built in excel into an actual web based

tool that can be developed. Listed below are in scope and out of scope objectives and deliverables.


In-Scope

● Research risk management practices in logistics and supply chain management

○ Academic transportation experts, white papers, and the corporate sponsor were

consulted on current supply chain risk management practice.

● Defining data sources relevant to Expeditors’ Secure Service risk information

○ FBI annual crime statistics

○ Direct competitor crime information

○ Internal insurance claim data

○ Publically available weather forecast data

○ Type of commodity being shipped

○ Risk mitigation products offered by Expeditors

● Provide a risk classification and ranking system of threats

○ Data sources have been provided weighted averages in order of their influence on a

shipment. Please see scoring section for explicit breakdowns of weights.

● Give recommendations on how to mitigate risk types and levels

○ Mitigation products, their application, and importance was provided by Expeditors

and incorporated into the final tool.

Out-of-Scope

● Integration of risk tool into custom Secure Service operating system

● Developing any part of the operating system, including and not limited to a customer-facing

interface for route risk assessment

● Implementation of process changes to affected systems or workflows

● Creating risk assessment tool marketing material

Limitations

● The current tool, as of May 28, 2015, only provides risk assessment and mitigation measures

for ground transportation in the continental U.S. on a per city basis. Additional data and

model adjustments will be necessary to calculate risk for other countries or modes of

transportation.


● Internal employees and external parties utilizing the tool should be advised that risk scores

are subjectively based on academic and industry knowledge and do not represent adherence

to any industry standards.

● The tool cannot account for the “human factor” associated with risk, and the capstone team

recommends Expeditors thoroughly assesses its third party vendors and the service records of

vehicle operators prior to engaging with the route planning and risk assessment.

● The data sources used in the tool must be maintained, as outlined within this documentation,

in order to remain relevant to Expeditors and its customers.

Data Sources This tool uses multiple data sources in order to compute the risk scores. It was a priority of the project

sponsors to use free open-source data, and with exception of internal Expeditor-owned data this was

accomplished. Below are brief descriptions of the sources and the reasons why they were selected.

Yahoo Weather API (https://developer.yahoo.com/weather/) A current and 5-day weather forecast has been extracted from Yahoo Weather. The data is

extracted in the form of an RSS feed from the Yahoo weather API (application program

interface). It is derived in the form of XML mapped to Excel, which can be generated by

inputting a state and city in the Excel route assessment tool then automatically refreshed to

get an updated weather feed. The XML feed pulls in information such as current and future

temperatures, humidity measurements, wind speed, and visibility, as well as weather codes

indicating the type of weather conditions.

FBI Crime Statistics for 2013 (http://www.fbi.gov/stats-services/crimestats) The FBI produces annual reports on national crime incidents, focusing namely on generated

report violent and property offenses. The 2013 federal statistics were used as a primary data

source for this project because they contained the most comprehensive crime analysis. It should be noted the 2013 FBI data used provides a baseline for crime comparisons across the

nation, and is not specifically targeting cargo theft. Expeditors may find it useful to

incorporate more FBI data in future versions of Route Assess, as well as updating crime

statistics on an annual basis.

Freightwatch International (http://www.freightwatchintl.com/) Competitive data on U.S. cargo theft in 2013 and 2014 was obtained from FreightWatch and

provided to the UW capstone team for use during the project. The data included information

such as cargo theft per city, commodity type, and total cargo value of stolen shipments which

was used in scoring and weighing crime per city and commodity information (e.g. which


https://developer.yahoo.com/weather/

http://www.fbi.gov/stats-services/crimestats

http://www.freightwatchintl.com/

commodity type is stolen more often and which commodity shipments stolen have the

highest value). This data set was not exhaustive and did not provide complete coverage of the

U.S., so it could be greatly improved by fully representing U.S. cities, and following uniform

data entry standards so all fields contain consistent information. However, because this is a

competitor’s data it will be hard for Expeditors to control the quality and quantity of the data.

“Sandbox” Expeditors’ Insurance Claims Internal Expeditors’ insurance claims were anonymized and used as another source of crime

and theft statistics. Claims data provided rich detail about the exact location of theft, quantity

and type of product stolen, monetary value of loss, etc. This information, should its volume

grow, will be very useful in the future calculation of risk along a shipping lane.

Expeditors’ Mitigation Offerings An internal document containing a list of mitigation services was used by the capstone team

to create the mitigation offerings used in the route assessment tool. The tool limits mitigation

products to trucking services only, and focuses on “Core” and “Additional” product levels. It

was determined by the capstone team and those overseeing the project that “Standard” level

products, which are already a part of every Expeditor shipment, served as the baseline for risk

mitigation and would not affect the overall risk score of any shipment.

Route Assess Guide As noted previously, the existing risk assessment framework has been built into an Excel workbook.

The purpose of this documentation section is to outline the sections of Route Assess, explaining the

concepts and data in each spreadsheet in-depth.

Main Menu Spreadsheet This is the first spreadsheet of the Excel workbook, and the page with which most analysts will

interact. It was designed to accept specific inputs about a particular freight shipment then compute

and return a score associated with those inputs.


Main Menu of Excel spreadsheet for Route Assess

Step 1) Select the states and cities along the shipment route After identifying the route for a given shipment, analysts can choose from a drop down menu the

corresponding states and urban areas through which a truck will pass. State must be selected first

before the menu of corresponding cities will be populated. Analyst must fill in both state and city to

calculate a City Risk Score. The model has no maximum threshold of states and cities that it will

accept. City Risk Score will be between 0.0 to 5.0, with 0.0 being very little crime risk to 5.0 being the

highest crime risk. More information on cities and crime data can be found in the Crime Data tab.

Step 1 on the Main Menu: Selecting the States & Cities of a Route to receive a Total Crime Score


Step 2) Choose the type of commodity being shipped Analysts can select from a dropdown menu the category of commodity being shipped, which will

populate the Commodity Score, which is a number between 1 to 5, with 1 being low risk and 5 being

high risk. The details behind this score can be found in the Commodity Data tab.

Step 2 on the Main Menu: select what type of commodity is being shipped

from the drop-down menu to receive an Asset Score

Step 3) Request weather forecast The 5-day forecast for a route can be generated from Yahoo! Weather after an analyst has entered

the states and cities for the given route. In the current state of the weather tab, the analyst is

required to manually drag XML elements into cells and refreshing in order to generate a weather

score for the route. See Weather Data and WeatherCodes tabs for more information.

To generate 5-day forecast, follow these steps in order:

Weather: Step A Go to the Developer Tab and click on Source. If there is no Developer tab visible, it can be enable by

selecting the File tab, clicking on Options, then clicking Customize Ribbon and selecting the Developer

check box.

XML Source Window


Weather: Step B Scroll down to the forecast element. Drag and drop the element into the Weather tab on Cell A1

Excel Mapping for XML

Weather: Step C Repeat Step 2 for each city by selecting the cities in the Dropdown in the Source section and dragging

them into the weather tab under column A.

A view of all XML weather records on the spreadsheet prior to refreshing

the RSS feed to populate the 5-day forecast for each city along the route.

Weather: Step D Select the refresh all option under Refresh to populate the weather data from the Yahoo RSS feed in

order to calculate the score.


XML Mapping to Cells for Cities

**Once Steps 1 - 4 are calculated, an initial Total Risk Score will show on the Input Tab. This is the

level of risk associated with a shipment PRIOR to applying any Secure Service mitigation products.

To adjust the Total Risk Score, proceed to Step 4 - Select Mitigation Products.

Step 4) Select mitigation products Analysts can work with customers to identify and address risk tolerance associated with a shipment.

Once States/Cities, Commodity, and Weather information have been selected, analysts will be able to

navigate to the Mitigation Products tab. This tab displays Secure Service products that customers can

add to their shipment for additional security. Each product addition will influence the risk score as it is

checked or unchecked in column A of the spreadsheet. The more mitigation measures taken, the

lower the final risk score. After selecting the most appropriate Mitigation Products for a customer,

the analyst may return to the Main Menu using the back arrow .

Mapping a Route A map of the crime severity along a route can generated using Excel’s Power Map add-in. Please make

sure your version of Excel has this add-in installed before proceeding.

To generate a Power Map for the route, enter all states and cities. Click the “Generate Map” button

on the Main Menu. Power Map will appear on input screen and can be copied to the Customer Report

spreadsheet for printing.


An example of an Excel Power Map, which can be generated in Route Assess.

The example is a visualization of crime severity travelling between Seattle, WA to Dallas, TX.

Generating a Customer Report A Customer Report template has been created in Route Assess. Crime, weather, commodity, and

mitigation product scores will automatically populate in the report once the Main Menu inputs have

been completed. Any additional material, such as Power Maps and analyst notes, will need to be

manually imported onto the report spreadsheet.

Example Customer Report generated in Route Assess. Map has been created using Tableau, and was manually

inserted into report. All other risk scores automatically populate in the report.


Risk Scoring The following section outlines the mathematical methods behind the scoring for crime, weather,

commodity, and mitigation products.

Commodity Scoring Commodity categories were based off of data collected from FreightWatch and internal Expeditors’

insurance claims. It is important to note that not every reported incident of theft contained asset

information, so commodity scores are based off a subset of the FreightWatch and Expeditors’ data.

Expeditors’ Secure Service management was presented the frequency, percentage, sum and average

value of stolen shipments computed from the reported incidents, then management selected the

Likert Value score based on what type of asset they deemed most important. Likert Values were used

to convey a 5 point scale of low to high (1 being low, and 5 being high). In this version of the tool a

Likert Value of 5 denotes the highest importance--the asset is at the greatest risk of theft--whereas a

value of 1 would indicate an asset is at lowest risk of theft. Because Expeditor Secure Service

management believes all categories of commodities to be at reasonably high risk, a 3 was the lowest

Likert value agreed upon.

Commodity Score spreadsheet in the Route Assess Excel workbook

Crime Scoring & Weights I. Foundational Layer - Crime per city

● Two parts comprise the data that underlies the crime score


○ FBI Data data set

■ Cities start with a base layer of data from the FBI Crime By City data set.

■ Percentage of crime to population is used to determine the the score in the

FBI data set.

■ The scale for scores is 1 to 5 in order to maintain simplicity in the model.

○ FreightWatch data set

■ Cities that have FreightWatch data have an additional FreightWatch score.

■ This score is calculated from the frequency of FreightWatch data points per

city.

■ This score is also on a 1 to 5 scale to match FBI.

○ Weights

■ We applied weights to each data set to reflect the significance the

FreightWatch data set has to freight at risk.

■ FBI - 0.5

■ FreightWatch - 0.75

■ Weights have been arbitrarily set, and analysts may choose to score with

weights out of 100%.

■ Possible new weights

■ FBI - 0.40

■ FW - 0.60

○ Calculation for Individual City Crime Score

■ Weighted Average Formula for each city

■ ((FBI Score x FBI Weight) + (FreightWatch Score x FreightWatch

Weight) ) / (FBI Score + FreightWatch Weight)

II. Additional Layer - Route Crime Score

● Route Crime score is calculated by using a weighted average of Individual City Scores.

○ Weighted Average formula for route crime score

■ (Sum of cities -> (Individual City Score * Crime Score Weight) ) / (Sum of

Weights)

○ Weights

■ Additional weights are applied to each crime score.

■ The scale for the weights from 0.1 to 0.5 are applied to a risk score scale of

0.4 to 5

■ Weight Scale Range: Weight

■ 0.4 - 1 : 0.1

■ 1.1 to 2: 0.2

■ 2.1 to 3: 0.3

■ 3.1 to 4: 0.4

■ 4.1 to 5: 0.5

■ The reasoning is that per a single route, weights should be applied to a city's

crime score to indicate a bias toward higher crime cities.

■ The result of the route weighted average formula is the Final Crime Score.


Mitigation Scoring & Weights We only focused on trucking mitigation offerings in the core and additional baseline. Check boxes are

added to the side to indicate which mitigation offering is selected. To calculate the scoring, we

created ranges based on the sum of the offerings selected and assigned a percentage to those ranges.

The percentage is then multiplied against the original risk score and the product is subtracted from

the original risk score, resulting in a new risk score. The ranges are constructed so that selecting even

one offering should increase the mitigation percentage. Mitigation can affect up to 57% of the total

risk score. These numbers were constructed and assigned based on feedback from Stakeholders

within Secure Service in Expeditors.

Weather Scoring Weather is calculated by first translating the Yahoo weather codes into the assigned likert scores and

multiplying that score by the preset weights. The resulting value is summed for each instance along

with the weights, and the total final sum is divided by the sum of the weights for the weather score.

1) Weather codes are received from Yahoo Weather through an RSS feed which give an

indication of weather conditions for a particular city through a five day forecast. Each

Weather Code is then assigned a Likert Value which can range from 1 to 5, depending on the

severity of the weather code.

2) Each Likert Score is then assigned a weight for aggregating purposes. Where the more severe

scores are assigned a higher weight.

Weather Weight Table

3) A score is assigned to each city for each day of the 5 day forecast from Yahoo Weather based

on the corresponding weather code. The score is then assigned a weight based on the weight

table.


Weather Score Calculation

4) Finally the weight and Score*weight columns are totalled in order to calculate a weighted

average weather score for the entire route.

Final Weather Score

(Currently calculating score based on entire 5 day forecast rather than specific days. We would need

shipment information about when the shipment would be passing through specific cities to create a

more accurate score. )

Overall Score

The overall score is calculated by doing a weighted average of the Crime, Weather and Commodity

Scores calculated previously.

The components of the score are weighted dynamically, changing depending on the scenario. In the

default scenario we assume normal weather conditions (Lower Weather score) results in a lower

weight being assigned to weather and higher weights for commodity and crime.

Alternate Scenario: In the case of Severe Weather conditions (Higher weather score) the weight for

weather goes up, while the weight for the commodity score goes down and crime remains the same.

This system ensures that weather is only considered as a significant factor if there is severe weather

along the route, at the cost of the commodity score. Weights can be adjusted for different scenarios

as needed but the weights must add up to 1 for the tool to work.


Final risk score weight table

Data Maintenance and Additions FBI crime data can be updated on an annual basis, as federal reports are released. Updating any

data--whether FreightWatch, internal claims data, FBI, or data from another source--requires new

data be formatted in the current data format. Data additions need to be added to the same

spreadsheet.

Recommendations for Future Work ● Continue increasing the quantity as well as quality of data. Current data heavily favors some

states/cities and neglects others introducing some bias into the scoring system. Our capstone

team believes internal claims data to be the most valuable crime data source and would

recommend further use of this type of data whenever available. Claims data can also be

weighted higher provided that it is present in large enough quantities.

● Establish data quality standards for each data type. For example, define and set a minimum

number of variables for crime, weather, commodity, and mitigation. Ensure these variables

are present for each data addition, and be cautious to include the data if it is deficient in these

standards.

● Consider adding a time element to risk scoring. Feature versions of risk scoring could

calculate weather for a specific period of time, rather than listing the 5-day forecast for each

city. In this case a weather score would be calculated based on the time the shipment would

be passing through a particular city versus considering the entire 5-day forecast.

● Use a web-based tool or system to automate weather forecasts. In its current form, Route

Assess uses XML mappings and depends on an analyst to correctly generate those mappings in

Excel and leaves room for potential user error. To make weather more scalable and

automated in the future, the weather API being used (Yahoo Weather, in this case) should be


directly plugged into the web-based tool or system in order to eliminate the need for XML

mappings from RSS feeds into Excel.

● Adding more Mitigation Products to the scoring. In order to include more mitigation products

in the scoring, the products need to be added to the list on the mitigation products tab,

assigned a likert value from 1 to 5, included in the formula for the mitigation calculation and

assigned a checkbox.

● Purchase access to an already available geographic database. Secure Service may intend to

scale the Route Assessment framework for global reach. In order to scale the tool in this

way--beyond U.S. boundaries--it would be advantageous for Expeditors to look for already

available online geographical databases that include information on all relevant countries and

cities instead of using locally sourced or manually generated geographic data.

● Adjust scoring to allow for more risk components. In order to scale the tool for use on a

global scale, the scoring system may need to be adjusted to consider other types of crime

such as terrorism, as well as other commodities, which might be region specific or be valued

differently abroad. Additional data sources for international crime and weather data would

also be required in order to give an accurate risk score. See “Data Maintenance and Additions”

for more information on adding new data to the model.

● Implement a visualization tool to communicate risk to customers. It is recommended that

Expeditors use a visualization tool that allows the analysts to easily generate visualizations for

inclusion in customer report and offering an easy way to visualize risk along a route. The two

tools that the capstone team experimented with were Tableau and PowerMap, both having

their pros and cons.

○ Tableau is a fairly intuitive BI visualization tool that allows users to create beautiful

looking visualizations quickly without much effort. It also allows users to create

custom interactive dashboards to manipulate and share data. However, Tableau

software licenses can be fairly expensive.

○ PowerMap is a tool by Microsoft that is built into Excel (However it does require Office

365 for a user to be able to create and view power maps). Power Map only allows for

the creation of maps based on the data you have. It is fairly easy to use and offers a

great deal of interactivity. However it is quite limited in functionality beyond creating

maps, its main advantage being the ability to use it with excel and being more readily

available than Tableau. However this should not be an issue once the tool is migrated

from excel and built on a web platform.

● It is recommended that Expeditors verify its scoring system through a rigorous post-analysis

of shipments, based on data, vendor, customer, and analyst input. A feedback process

should be developed to ascertain the accuracy and precision of scoring, providing an outlet for

recommendations and quick updates to the tool in order to preserve realistic estimates of any

components assessed in the total risk score.

● It is also recommended that Expeditors facilitate live disaster recovery operations, wherein

they practice a spectrum of risk scenarios and the recovery of freight from those scenarios.

Without practice and proof of recovery, the likelihood of successful mitigation of transit risk is

in jeopardy, as is the validity and purpose of the Route Assessment framework and process.


Hand-over of Project Ownership In exchange for the complete ownership and implementation of the framework and tool described

herein, Expeditors International recognizes there are certain limitations and inherent risks associated

with the use of Risk Assess, and assumes full liability for any resulting cost or harm to its business and

customers. Additionally, maintenance of the tool will be handled by Expeditors, which includes

inputting additional data sources and any framework adjustment.

Expeditors, in assuming ownership and use of the tool, acknowledges the scoring methods, as well as

the total risk score, are subjective and not absolute or definitive. While the creation of the tool was

well-informed and its purpose well-meaning, its use does not protect customers from supply chain

risk. The tool primarily serves as a framework to expose potential threats and vulnerabilities specific

to transcontinental freight forwarding, and encourages logistics professionals to communicate with

and consult their customers on how to best respond to those risks. The tool also does not take into

account the human factor of freight forwarding such as driver background and shipping company

reliability.

Future Team Obligations Once the handoff of the risk assessment tool is completed on or before June 5th, 2015, the project

team will not be providing additional support to Expeditors. Likewise, Expeditors is not expected to

provide the capstone team with any resources or ongoing support. The handoff will include training

documentation and final presentation given by the capstone team to the Secure Service its related

stakeholders.

Intellectual Property Rights A non-disclosure agreement was signed between the graduate students on the capstone team and

Expeditors to protect the company’s internal practices and data released to the team. The capstone

team, however, assumes the right to discuss the project in a general sense to others while upholding

NDA requirements.


Appendix Yahoo weather code and Likert value breakdown used in calculating a weather score.


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