call center trunks optimization presented to: dr. richard barr dr. thomas siems emis faculty and...
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CALL CENTER TRUNKS OPTIMIZATION
PRESENTED TO:Dr. Richard Barr
Dr. Thomas SiemsEMIS Faculty and Students
ORM TECHNOLOGIES
PRESENTED BY:Alexandria Farrar
Ashley HallNeimy Sarmiento
May 7, 2014
Southern Methodist University EMIS 4395: Senior Design
Spring 2014
ORM TECHNOLOGIES, LLC
May 7, 2014
Southern Methodist UniversityEMIS 4395: Senior Design
Spring 2014 2
Our Client
ORM Technologies is a Business Analytics company focused on delivering the benefits of Optimization through our innovative suite of software and consulting services that are easy to use, deploy, and manage.
The Result – Optimized ThinkingTM
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Resource Mgmt & Planning
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Revenue Forecasting Sales Headcount Planning to achieve
Budget Sales Goals Lead/Funnel Forecasting and “Risk”
Assessment with CRM and SalesMethodology integration
Marketing and Advertising Analytics& Spending Optimization
Revenue & Sales Management
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Demand Forecasting
Production Scheduling
Production Scheduling
Vendor Management System for authorized vendor’s pricing, and quantity levels
Supply Chain
ORM OPTIMIZATION SERVICES
2Statistical, Analytics & Planning
Resource Workload Schedulingo Training & Support Scheduling & Assignmento Call Centers & Help Deskso Project Managemento Research & Development
Resource Budgeting and Planning Resource “What If” scenarios
Statistical & Analytics Services Demand/Production Forecasting
Revenue Forecasting
Sales Funnel Forecasting
Call Center Optimization & Planning – Agents & Network Resources
Fraud Detection & Management System
Southern Methodist University EMIS 4395: Senior Design
Spring 2014
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OBJECTIVE STATEMENT
Design a dynamic model for the least costly combination of trunk types to service a call
center’s inbound call volume
May 7, 2014Southern Methodist University
EMIS 4395: Senior Design Spring 2014
6May 7, 2014
NETWORK OVERVIEW CALL FLOW
Agent Optimization - ErlangC
Shift Management Module
PSTN & Internet
Wide Area Network
Location 1Agent Types Location 2
Location 3
Router
PBX
0% Bypass IVR
100% IVR
7% resolved by IVR
10% Abandon rate 50% Retry
Home Agent
80% of Calls
20% of Calls
Network Resource Optimization - ErlangB
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ERLANG B OVERVIEW
An Erlang is a unit of telecommunications traffic measurement. Erlang B s a formula for the blocking probability that describes the probability of call losses for a group of identical parallel resources (telephone lines, circuits, traffic channels, or equivalent)
Southern Methodist University EMIS 4395: Senior Design
Spring 2014
E- offered traffic = λ*hλ = call arrival rate of busiest hour during h = average call holding time
m – number of trunks the probability that a new call arriving to an agent is rejected or blocked
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SIMPLIFIED NETWORK OVERVIEW CALL FLOW
PSTN & Internet
Wide Area Network
Router
PBX
0% Bypass IVR
100% IVR 7% resolved
by IVR
10% Abandon rate 50% Retry
CLIENT SUPPORT NEEDEDCONSTRAINTS
(Known and Unknown)• DATA:
– Number of calls per 30 minute interval
– Average handle time
– Trunk type– Trunk cost
• PROJECT CONSTRAINTS– Feasible completion
within 4 months
• MODEL CONSTRAINTS– Must be integrated into
current system (Erlang)– One trunk level per
month (not type)– Trunk type and cost– 250-trunk maximum
CLIENT SUPPORT NEEDED CONSTRAINTS and VARIABLES
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PARAMETERS
TRUNK TYPE NUMBER OF TRUNKS COST PER MONTH
DS0 1 $30
DS1 24 $495
DS3 672 $4000
May 7, 2014Southern Methodist University
EMIS 4395: Senior Design Spring 2014
CALL TYPE
Walk-ins
Back-office
Front-office
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General Algebraic Modeling System (GAMS) Outline
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GAMS OPTIMIZATION MODEL
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GAMS OPTIMIZATION MODEL
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GAMS OPTIMIZATION MODEL
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GAMS OPTIMIZATION MODEL
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GAMS OPTIMIZATION MODEL
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GAMS OPTIMIZATION MODEL
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GAMS OPTIMIZATION MODEL
May 7, 2014
Southern Methodist University EMIS 4395: Senior Design Spring 2014
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GAMS OPTIMIZATION MODEL
RESULTSMONTH DS0 DS1 TOTAL TRUNKS PER
MONTHJanuary 2 1 26
February 2 1 26
March 7 1 31
April 2 1 26
May - 1 23
June 2 1 26
July - 1 23
August 1 1 25
September 7 1 31
October 5 1 29
November 4 1 28
December 8 1 32
TOTAL ANNUAL TRUNK COST
$7,140.00
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MODEL FLEXIBILITY and OBSERVATIONS
• The Total Trunks per Month follow a cosine wave pattern.
• The peaks are quarterly: – March, June, September and December
May 7, 2014Southern Methodist University
EMIS 4395: Senior Design Spring 2014
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RECAP and RECOMMENDATIONS• Erlang B used to determine lowest cost
combination of trunks per month.• Backwards engineer data set for gross call
volume• The Total Trunks per Month follow a cosine
wave pattern.• The peaks are quarterly: – March, June, September and December– Client review business needs every quarter
May 7, 2014Southern Methodist University
EMIS 4395: Senior Design Spring 2014