Database Systems Corp.
Home  |   Contact Us  |   About Us  |   Sign Up  |   FAQ

predictive dialers and crm software
computer telephony software predictive dialer

Call Center Company
Call Center Solutions
Call Center Monitoring System
Call Center Simulator
IVR / ACD Simulation
Predictive Dialer Simulator
Contact Center Technology

predictive dialers and crm software

Call Center Simulation
Call Center Modeling
Call Center Monitoring
Contact Center Software
Call Center Software
Customer Contact Center Technology
Call Center Solutions
Telemarketing Software
Linux Call Center
Call Center Technology
Telemarketing CRM
Call Center Autodialer
Call Center CTI
Inbound Call Center
Outbound Call Center
Call Center Outsourcing
Call Center Services
Call Center Development
Contact Center
Contact Management Center
Call Center CRM

DSC Tech Library

Contact Center Equipment

telecommunications software solution This section of our technical library presents information and documentation relating to Call Center technology and Best Practices plus software and products. DSC is a leading provider of contact center technology and software solutions as well as predictive dialer phone systems for the modern call center. Customer contact center software includes CRM software and computer telephony integration solutions. These modern products help call center phone agents communicate effectively with your customers and prospects.

The following article presents product or service information relating to call centers and customer service help desks.

Call Center Simulation Modeling:
Methods, Challenges, And Opportunities

Page 1

By Vijay Mehrotra, Department of Decision Sciences
College of Business - San Francisco State University

Jason Fama, Engineering Group, Blue Pumpkin Software Inc.


Using stochastic models to plan call center operations, schedule call center staff efficiently, and analyze projected performance is not a new phenomenon, dating back to Erlang's work in the early twentieth century. However, several factors have recently conspired to increase demand for call center simulation analysis.
  • Increasing complexity in call traffic, coupled with the almost ubiquitous use of Skill-Based Routing.
  • Rapid change in operations due to increased merger and acquisition activity, business volatility, outsourcing options, and multiple customer channels (inbound phone, outbound phone, email, web, chat) to support.
  • Cheaper, faster desktop computing, combined with specialized call center simulation applications that are now commercially available.

In this tutorial, we will provide an overview of call center simulation models, highlighting typical inputs and data sources, modeling challenges, and key model outputs. In the process, we will also present an interesting “realworld” example of effective use of call center simulation.


The trend in our economy from manufacturing towards services is well documented. One notable facet of this transition towards services has been the explosion of the call center industry.

Mehrotra (1997) defines call centers as “Any group whose principal business is talking on the telephone to customers or prospects.” In this paper, we will refer to the individuals who talk on the phone with customers as “agents.”

While the size of the industry is difficult to accurately determine, a plethora of statistics from diverse sources reflect that fact that this is a huge and growing global industry. Most stunning: Mandelbaum (2001) cites a study that an estimated 3% of the United States population works in this industry. Most recent: an explosion of outsourced call centers springing up in India, the Philippines, the Caribbean, and Latin America, serving overseas customers in the United States and Western Europe as well as growing domestic market needs.

From a mathematical perspective, call centers are interesting for a variety of reasons:

  • Call centers typically handle more than one type of call, with each distinct call type referred to as a “queue” (as discussed below, this usage is not consistent with our normal definition of a queue). Inbound calls within each queue arrive at random over the course of time.
  • In many centers, agents make outbound calls to customers, either proactively (typically for telemarketing or collections activities) or as a followup to previous inbound calls.
  • Each call is of a random duration, as is the work (data entry, documentation, research, etc.) that agents must do after completing the phone call.
  • Through Automatic Call Distribution (“ACD”) and Computer Telephony Interaction (“CTI”) devices, inbound calls can be routed to agents, groups, and/or locations, with advancements in these routing technology supporting more and more sophisticated logic over time.
  • Individual agents can be skilled to handle one type of call, several types of calls, or all types of calls, with different priorities and preferences specified in the routing logic.
Thus, call centers can be thought of as stochastic systems with multiple queues and multiple customer types. As we discuss below, there are great challenges associated with managing these systems effectively.

To summarize, call centers are of interest both because of the sheer size of the industry, both in the United States and overseas, and because of the operational and mathematical complexity associated with these operations, which makes it difficult for decision makers to understand system dynamics without effective modeling.

Page  1   [2]  [3]  [4]  [5]  [6]  [7]  [8Next Page 

Vijay Mehrotra
Department of Decision Sciences
College of Business
San Francisco State University
1600 Holloway Avenue
San Francisco, CA 94123, U.S.A.

Jason Fama Engineering Group
Blue Pumpkin Software Inc.
884 Hermosa Court
Sunnyvale, CA 94085, U.S.A.