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Dynamic Help Desk Resource Modeling

Models and Methods Track




This paper discusses the concept of Dynamic Helpdesk Resource Modeling for a major Information Technology System. This methodology utilizes regression analysis based on the concept of learning curves to project the resource load for a three tiered help desk system based on a number of factors including system user population and maturity. The paper uses the implementation of an Enterprise Resource Planning System throughout the United States Navy as the user system with a three tiered help desk model as the basis for analysis.

The following establishes the typical escalation process for ticket items entering the help desk service; Tier 1 answers the initial call from the user, creates a ticket for tracking, performs the initial triage, and escalates the issue to the appropriate next level, Tier 2 or Tier 3. This paper argues that a combination of factors, including site user populations and system / user maturity exercise a direct causal relationship with the Tier 1, 2, and 3 help desk loads, with unique relationships to each.

Using regression analysis based on the concept of learning curves, this paper develops a methodology to understand the shifts in Helpdesk ticket volumes and resource requirements over time as the users, system and business processes mature. The model discussed in this paper projects Helpdesk requirements with demonstrated certainty, giving decision makers sufficient information to project future costs and ensure optimum staffing levels.


Sujoy K. Roy
Herren Associates
Mr. Roy has served as a consultant in both the academic and private sectors. His experience has been heavily invested in creating models using Operation Research principles to depict optimum solutions. He currently supports the Department of the Navy (DoN) with Cost Analysis and Program Management for the deployment and sustainment of the Navy’s Enterprise Resource Planning System. Mr. Roy has also had experience in the Insurance industry, where he has provided competitive intelligence and cost estimating tools for senior leadership in both personal line and business insurance. He holds a B.S. in Industrial and Manufacturing Engineering from Pennsylvania State University.

Nolin Huddleston
Herren Associates
Mr. Huddleston has served as both a project manager and technical consultant delivering high-tech capabilities to federal agencies in the greater Washington, D.C., metropolitan area. His work has focused on the topics of economic analysis, business case development, program/project management, and systems engineering. In addition, Mr. Huddleston has supplemented his technical background with graduate studies in management, finance, statistical analysis, decision theory, and strategy of high-tech businesses. He currently provides program analysis and cost estimation support to the Navy ERP Program (PEO EIS). Mr. Huddleston is a SCEA Certified Cost Estimator/Analyst.

Steve Sheamer
Herren Associates
Steve Sheamer is a technical consultant with over ten years of experience developing solutions to facilitate cost estimating, manpower analysis, operations research and program management for private sector firms and federal agencies. He has directly supported program management activities on multi-billion dollar acquisition programs, including the F-35 Joint Strike Fighter and the Navy’s Enterprise Resource Planning (ERP) Program, and has led the development of numerous tools to support decision making and effective program management.
Mr. Sheamer is currently a Senior Associate with Herren Associates, and co-leads the firm’s Program Analysis and Cost Estimating practice. Prior to joining Herren in 2008, Mr. Sheamer directed a team of IT developers and analysts at Lockheed Martin in the implementation of an automated performance management system for the F-35 Joint Strike Fighter program. Before his work at Lockheed Martin, he spent several years in the technology sector with Advanced Micro Devices and Applied Materials applying operations research techniques including queuing theory, discrete event simulation, and statistical analysis to optimize resources and reduce manufacturing cycle times.
Mr. Sheamer has both a master’s and bachelor’s degree in industrial engineering from Texas A&M University. He is a Society of Cost Estimating and Analysis (SCEA) Certified Cost Estimator/Analyst (CCEA), a Lean Six Sigma Green Belt, and holds a graduate certificate in Earned Value Management.