My research is mainly in decision analysis, with recent applications in cybersecurity, military, and defense.  I also have experience with inventory, especially spare parts.  I help organizations make better decisions, which extends to many application areas.


My published research in cybersecurity primarily addresses metrics, best practices, and human behavior.  Working projects include a value model for cybersecurity metrics and insider threat risk management for voting processes, especially at polling places.  Visit my Media for a profile of my student team’s work in cybersecurity and for news articles related to my work in elections security.

Protecting Maryland’s Voting processes

Megan Price, Natalie M. Scala, Paul L. Goethals

Baltimore Business Review: A Maryland Journal, p. 36-39, 2019

This paper outlines two research projects that specifically address the security of Maryland’s voting processes.  The first is a preliminary risk model for cyber, physical, and insider threats to polling places.  The model evaluates vulnerabilities in the voting process and recommends how the State of Maryland should focus resources to combat threat.  The second project involves creating training modules for Election Judges so that they can identify and respond to cyber, physical, and insider threats. 

sources of risk in elections security

Hannah Locraft, Priya Gajendiran, Megan Price, Natalie M. Scala, Paul L. Goethals

Proceedings of the 2019 IISE Annual Conference

This research examines sources of risk in voting systems, identifies potential vulnerabilities in voting processes, and suggests a risk model framework to assess and mitigate vulnerabilities. We examine patterns and trends in a state’s elections security and the characteristics of its voting processes. We also present diagrams of sources of cyber, physical, and insider risk to voting processes and discuss an outline of a Markov model to assess evolving threat. Correlation Matrix Data

Risk and the Five hard problems of cybersecurity

Natalie M. Scala, Allison C. Reilly, Paul L. Goethals, Michel Cukier

Risk Analysis: An International Journal, article in advance, 2019

We consider the Five Hard Problems (5HP) as defined by Science of Security (SoS) initiative at the National Security Agency and encourage the application of risk analysis principles to cybersecurity research. The 5HP are (1) scalability and composability; (2) policy‐governed secure collaboration; (3) security‐metrics–driven evaluation, design, development, and deployment; (4) resilient architectures; and (5) understanding and accounting for human behavior. We show how risk analysis can be applied to each hard problem to enable growth and insight in both cybersecurity and risk research.

Values and Trends in Cybersecurity

Lorraine Black, Natalie M. Scala, Paul L. Goethals, James P. Howard, II

Proceedings of the 2018 Industrial and Systems Engineering Research Conference

We survey information technology professionals as well as small legal firms and solo practitioners to understand what they value in a secure cyber system.  We identify differences in values between the two populations as well as how a previous attack or breach can affect value.  Finally, we provide an inventory of values, as identified by the survey respondents, which can be inputs to a value model.


Best Practices in Cybersecurity: Processes and Metrics

Jasmin Farahani, Natalie M. Scala, Paul Goethals, Adam Tagert

Baltimore Business Review: A Maryland Journal, p. 28-32, 2016

This paper draws attention to the nature and severity of cyberattacks, especially breaches that have occurred in the State of Maryland.  We identify a selection of metrics and best practices that can be implemented to increase cybersecurity posture as well as outline an agenda for research.


A Review of and Agenda for Cybersecurity Policy Models

Natalie M. Scala, Paul Goethals

Proceedings of the 2016 Industrial and Systems Engineering Research Conference

We review three cybersecurity policy models: the three tenets model, attack graph and attack surface models, and the cybersecurity heuristic model.  We also outline a value based research model for cyber metrics.

Military and Defense Applications

Decision analysis has a rich history in military and defense related applications, and it is important to utilize perspectives from academia and outside of the traditional service branches when solving these really complex and important problems.  My research uses value and decision modeling to quantify attributes and enable decision makers to select optimal and/or preferred alternatives.


Eliminating the Weakest Link Approach in Army Unit Readiness

Paul L. Goethals, Natalie M. Scala

Decision Analysis, 15(2), p. 110-130, 2018

We examine the United States Army’s readiness metrics, as outlined in AR-220-1, and propose an improvement in the composite metric, in order to evaluate units with greater precision, flexibility, and robustness.  Our desirability function approach measures readiness based upon a set of priorities, adapting for type of mission and unit.  Accurate assessments of readiness are crucial, as the level of Army readiness drives federal funding, defense policy, and deployment decisions.  AAM via INFORMS Green Option


A Value Model for Asset Tracking Technology to Support Naval Sea-Based Resupply

Natalie M. Scala, Jennifer Pazour

Engineering Management Journal, 28(2), p. 120-130, 2016

Naval seabasing is a dense storage environment and requires specialized logistics to fulfill emergent requests for tailored resupply packages while at sea.  We develop a value model to identify the preferred technology to track inventory assets while stored in this dense environment.  Evaluated technologies include radio frequency identification, barcoding, internal positioning systems (IPS), and camera-aided technology.  We conclude that IPS is the preferred asset tracking technology in the seabasing environment.  An adapted version of this paper is available within the following Defense Technical Information Center report: link to report.


Multi-objective Decision Analysis for Workforce Planning: A Case Study

Natalie M. Scala, Richard Kutzner, Dennis Buede, Christopher Ciminera, Alicia Bridges

Proceedings of the 2012 Industrial and Systems Engineering Research Conference

We create a value model to evaluate the preferred ratio of civilian, contractor, and military personnel for an engineering related work role in the defense environment.

Spare Parts

My dissertation studied spare parts at nuclear power plants.  Spares are particularly interesting in this environment, as many exhibit extremely intermittent demand while possibly having plant safety implications.  The overall research enabled the case study company to save 18% of its total spares inventory volume.


Managing Nuclear Spare Parts Inventories: A Data Driven Methodology

Natalie M. Scala, Jayant Rajgopal, Kim LaScola Needy

IEEE Transactions on Engineering Management, 61(1), p. 28-37, 2014

This paper outlines and summarizes a four part methodology for managing nuclear spare parts: (1) influence diagram of relevant factors, (2) weighting influences via the Analytic Hierarchy Process, (3) assigning parts to groups using inventory criticality indices, and (4) base stock inventory policy for each group of parts.  This is a data driven methodology that can be used to manage the entire nuclear spare parts process, or portions may be used to manage components of the overall process.


Influence Diagram Modeling of Nuclear Spare Parts Process

Natalie M. Scala, Jayant Rajgopal, Kim LaScola Needy

Proceedings of the 2010 Industrial Engineering Research Conference

This paper details the first step in the nuclear spare parts methodology, and develops an influence diagram for the spare parts process.  Thirty-four influences were identified and grouped into seven themes, driving best practices for process continuous improvement.


Using the Analytic Hierarchy Process in Group Decision Making for Nuclear Spare Parts

Natalie M. Scala, Kim LaScola Needy, Jayant Rajgopal

31st ASEM National Conference, 2010

This paper details the second step in the nuclear spare parts methodology and specifically presents the interview protocol used for subject matter expert (SME) elicitation.  Examples of SME responses and data collection are also discussed.


An Inventory Criticality Classification Method for Nuclear Spare Parts: A Case Study

Natalie M. Scala, Jayant Rajgopal, Kim LaScola Needy

Chapter 15 of Decision Making in Service Industries: A Practical Approach, CRC Press, p. 365-392, 2012

This paper details the third step in the nuclear spare parts methodology and develops criticality indices for spare parts inventory.  Parts are then assigned to groups based on a criticality score, which is derived from part performance against the weighted influences.  Three overall groups of parts are defined.


A Base Stock Inventory Management System for Intermittent Spare Parts

Natalie M. Scala, Jayant Rajgopal, Kim LaScola Needy

Military Operations Research, 18(3), p. 63-77, 2013

This paper details the fourth step in the nuclear spare parts methodology and develops base stock inventory policies for each group of parts.  We use a historical numerical simulation to identify inventory levels that minimize the overall spare parts investment while following a user-defined risk tolerance profile.


Risk and Spare Parts Inventory in Electric Utilities

Natalie M. Scala, Jayant Rajgopal, Kim LaScola Needy

Proceedings of the 2009 Industrial Engineering Research Conference

We discuss risk in the context of nuclear power generation and utilities.  We also provide a research agenda for incorporating risk and costs into a quantitative decision analysis framework for controlling spare parts inventories.


Decision Making and Tradeoffs in the Management of Spare Parts Inventory at Utilities

Natalie M. Scala, Kim LaScola Needy, Jayant Rajgopal

30th ASEM National Conference, 2009

We discuss tradeoffs, in a deregulated generation environment, associated with holding large amounts of spare parts inventory versus the potential revenue losses if a nuclear generation plant were to go off-line.  We also explore potential forecasting methods for nuclear spare parts and establish that many parts exhibit highly intermittent demand patterns.


Spare Parts Management for Nuclear Power Generation Facilities

Natalie M. Scala

My dissertation discusses the four part inventory management methodology for nuclear spare parts, and includes details beyond my journal and conference papers.

Other Areas

My research can be broadly classified as decision analysis, so many of these papers examine applications of decision models in various contexts.  I’ve also done some work in post-secondary education, specifically examining how business and engineering students are motivated to learn analytics.


Group Decision Making with Dispersion in the Analytic Hierarchy Process

Natalie M. Scala, Jayant Rajgopal, Luis Vargas, Kim LaScola Needy

Group Decision and Negotiation, 25(2), p. 355-372, 2016

This is a theory paper that develops a method for aggregating a group of decision maker judgments in the Analytic Hierarchy Process (AHP).  This method should be used when the decision makers are dispersed and unwilling or unable to revise their judgments.  It can also be used to determine weights for homogeneous decision makers when using the weighted geometric mean for aggregation.


Motivation and Analytics: Comparing Business and Engineering Students

Natalie M. Scala, Stella Tomasi, Andrea Goncher, Karen Bursic

INFORMS Transactions on Education, 19(1), p. 1-11, 2018

This research examines differences between business and engineering students in motivation to learn analytics.  We find that effective approaches for teaching analytics vary by major. Business students can be influenced towards a positive attitude and thus be motivated to perform better. Caring instructors who demonstrate the relevance of the material in the classroom can help to influence positive attitudes among business students.  Visit my Media page for a profile of this article.


Examining Real Time Pricing in Electricity Usage

Natalie M. Scala, Samuel Henteleff, Christopher Rigatti

Proceedings of the 2010 Industrial Engineering Research Conference

Using a survey, we examine potential customer preferences to Real Time Pricing (RTP), or dynamic electricity prices based on time of day and weather. We consider potential residential customer willingness to shift usage to off-peak hours for 11 typical household appliances, identifying potential implications if RTP was broadly enacted in the United States.

This paper was selected as “Best Paper in Engineering Economy” at the 2010 Industrial Engineering Research Conference.


Analyzing Supplier Quality Management Practices in the Construction Industry

Rufaidah AlMaian, Kim LaScola Needy, Kenneth D. Walsh, Thaís da CL Alves, Natalie M. Scala

Quality Engineering, 28(2), p. 175-183, 2016

This article uses principal component analysis (PCA) to analyze a number of supplier quality management (SQM) practices from construction organizations known for effective SQM.  Practices are validated by a decision model built from subject matter expert elicitation.  We show that supplier's work observation, supplier performance rating, inspection effort tracking, and inspection and testing plans are important practices. The analysis can be extended to a quantitative methodology that quality engineers can use to analyze small sample size data.


Decision Modeling and Applications to Major League Baseball Pitcher Substitution

Natalie M. Scala

29th ASEM National Conference, 2008

This research examines the influences that affect a manager’s decision to substitute a pitcher in Major League Baseball and presents a decision model to analytically determine the best choice of pitcher to face a given batting line-up.  Historical box scores are used to both illustrate and validate the model.


An Analytic Network Process (ANP) Approach to the Project Portfolio Management for Organizational Sustainability

Fikret K. Turan, Natalie M. Scala, Mary Besterfield-Sacre, Kim LaScola Needy

Proceedings of the 2009 Industrial Engineering Research Conference

This paper presents preliminary research that uses ANP and the Triple Bottom Line to evaluate and prioritize projects based on their potential contribution to an organization’s sustainability initiative.


Organizational Sustainability: A New Project Portfolio Management Approach that Integrates Financial and Non-Financial Performance Measures

Fikret Turan, Natalie M. Scala, Akram Kamrani, Kim LaScola Needy

Proceedings of the 2008 Industrial Engineering Research Conference

This paper presents preliminary research of a decision model that integrates financial and non-financial performance measures in project portfolio management via the Triple Bottom Line.  Projects are prioritized to align with the organization’s financial, environmental, and social strategy.