CALL CENTER TRUNKS OPTIMIZATION PRESENTED TO: Dr. Richard Barr Dr. Thomas Siems EMIS Faculty and Students ORM TECHNOLOGIES PRESENTED BY: Alexandria Farrar Ashley Hall Neimy Sarmiento May 7, 2014 Southern Methodist University EMIS 4395: Senior Design Spring

ORM TECHNOLOGIES, LLC May 7, 2014 Southern Methodist University EMIS 4395: Senior Design Spring 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 Thinking TM

ORM - Approach May 7, 2014 Southern Methodist University EMIS 4395: Senior Design Spring ORM – Optimized Thinking TM  Deliver a suite of software and consulting services that are easy to use, deploy and manage.  Deliver the ORM - Optimized Enterprise Architecture TM framework of software services that enable functional and cross functional Optimization. Simple Proposition – you will achieve a 5% - 20%+ improvement in any area of deployment.

May 7, Resource Mgmt & Planning 2  Revenue Forecasting  Sales Headcount Planning to achieve Budget Sales Goals  Lead/Funnel Forecasting and “Risk” Assessment with CRM and Sales Methodology integration  Marketing and Advertising Analytics & Spending Optimization 2  Revenue Forecasting  Sales Headcount Planning to achieve Budget Sales Goals  Lead/Funnel Forecasting and “Risk” Assessment with CRM and Sales Methodology integration  Marketing and Advertising Analytics & Spending Optimization Revenue & Sales Management 2  Demand Forecasting  Production Scheduling  Vendor Management System for authorized vendor’s pricing, and quantity levels 2  Demand Forecasting  Production Scheduling  Vendor Management System for authorized vendor’s pricing, and quantity levels Supply Chain ORM OPTIMIZATION SERVICES 2 2 Statistical, Analytics & Planning Resource Workload Scheduling o Training & Support Scheduling & Assignment o Call Centers & Help Desks o Project Management o 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

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, Southern Methodist University EMIS 4395: Senior Design Spring 2014

May 7, NETWORK OVERVIEW CALL FLOW Agent Optimization - ErlangC Shift Management Module PSTN & Internet Wide Area Network Location 1 Agent 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

May 7, 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

May 7, 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 NEEDED CONSTRAINTS (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

PARAMETERS May 7, 2014 Southern Methodist University EMIS 4395: Senior Design Spring CALL TYPE Walk-ins Back-office Front-office

General Algebraic Modeling System (GAMS) Outline May 7,

GAMS OPTIMIZATION MODEL May 7,

GAMS OPTIMIZATION MODEL May 7,

GAMS OPTIMIZATION MODEL May 7,

GAMS OPTIMIZATION MODEL May 7,

GAMS OPTIMIZATION MODEL May 7,

GAMS OPTIMIZATION MODEL May 7,

GAMS OPTIMIZATION MODEL May 7,

May 7, 2014 Southern Methodist University EMIS 4395: Senior Design Spring GAMS OPTIMIZATION MODEL

RESULTS MONTHDS0DS1TOTAL TRUNKS PER MONTH January2126 February2126 March7131 April2126 May-123 June2126 July-123 August1125 September7131 October5129 November4128 December8132 TOTAL ANNUAL TRUNK COST $7,

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, Southern Methodist University EMIS 4395: Senior Design Spring 2014

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, Southern Methodist University EMIS 4395: Senior Design Spring 2014