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

May 7, 2014 4

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

8May 7, 2014

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

May 7, 2014

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GAMS OPTIMIZATION MODEL

May 7, 2014

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GAMS OPTIMIZATION MODEL

May 7, 2014

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GAMS OPTIMIZATION MODEL

May 7, 2014

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GAMS OPTIMIZATION MODEL

May 7, 2014

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GAMS OPTIMIZATION MODEL

May 7, 2014

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GAMS OPTIMIZATION MODEL

May 7, 2014

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GAMS OPTIMIZATION MODEL

May 7, 2014

Southern Methodist University EMIS 4395: Senior Design Spring 2014

19May 7, 2014

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

22

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