CALL CENTER TRUNKS OPTIMIZATION
Presented as a senior design project in 2014, this initiative by ORM Technologies focused on optimizing call center trunks for efficient service delivery. The project aimed to create a dynamic model to determine the least costly trunk types for managing inbound call volume. Detailed services and benefits of ORM Technologies are highlighted, including supply chain management, revenue forecasting, sales optimization, and network resource management. The network overview illustrates call flow strategies and agent optimization techniques employed to enhance the effectiveness of the call center operations.
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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 Southern Methodist University EMIS 4395: Senior Design Spring 2014 May 7, 2014 1
ORM TECHNOLOGIES, LLC 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 Southern Methodist University EMIS 4395: Senior Design Spring 2014 May 7, 2014 2
ORM OPTIMIZATION SERVICES Supply Chain Resource Mgmt & Planning 2 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 Demand Forecasting Production Scheduling Production Scheduling Vendor Management System for authorized vendor s pricing, and quantity levels 2 Statistical, Analytics & Planning Revenue & Sales Management 2 Statistical & Analytics Services 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 Southern Methodist University EMIS 4395: Senior Design Spring 2014 Demand/Production Forecasting Revenue Forecasting Sales Funnel Forecasting Call Center Optimization & Planning Agents & Network Resources Fraud Detection & Management System May 7, 2014 4
OBJECTIVE STATEMENT Design a dynamic model for the least costly combination of trunk types to service a call center s inbound call volume Southern Methodist University EMIS 4395: Senior Design Spring 2014 May 7, 2014 5
NETWORK OVERVIEW CALL FLOW 100% IVR Agent Optimization - ErlangC PBX 7% resolved by IVR 10% Abandon rate 50% Retry Router 0% Bypass IVR 20% of Calls Wide Area Network Home Agent PSTN & Internet 80% of Calls Location 3 Network Resource Optimization - ErlangB Location 1 Agent Types Shift Management Module Location 2 May 7, 2014 6
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) E- offered traffic = *h = 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 Southern Methodist University EMIS 4395: Senior Design Spring 2014 May 7, 2014 7
SIMPLIFIED NETWORK OVERVIEW CALL FLOW 100% IVR 7% resolved by IVR PBX 0% Bypass IVR 10% Abandon rate 50% Retry Router PSTN & Internet Wide Area Network May 7, 2014 8
CLIENT SUPPORT NEEDED CONSTRAINTS and VARIABLES CONSTRAINTS (Known and Unknown) 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 DATA: Number of calls per 30 minute interval Average handle time Trunk type Trunk cost
PARAMETERS TRUNK TYPE NUMBER OF TRUNKS COST PER MONTH DS0 1 $30 DS1 24 $495 DS3 672 $4000 CALL TYPE Walk-ins Back-office Front-office Southern Methodist University EMIS 4395: Senior Design Spring 2014 May 7, 2014 10
General Algebraic Modeling System (GAMS) Outline May 7, 2014 11
GAMS OPTIMIZATION MODEL May 7, 2014 12
GAMS OPTIMIZATION MODEL May 7, 2014 13
GAMS OPTIMIZATION MODEL May 7, 2014 14
GAMS OPTIMIZATION MODEL May 7, 2014 15
GAMS OPTIMIZATION MODEL May 7, 2014 16
GAMS OPTIMIZATION MODEL May 7, 2014 17
GAMS OPTIMIZATION MODEL May 7, 2014 18
GAMS OPTIMIZATION MODEL Southern Methodist University EMIS 4395: Senior Design Spring 2014 May 7, 2014 19
RESULTS DS0 MONTH DS1 TOTAL TRUNKS PER MONTH January 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 20
MODEL FLEXIBILITY and OBSERVATIONS The Total Trunks per Month follow a cosine wave pattern. The peaks are quarterly: March, June, September and December Southern Methodist University EMIS 4395: Senior Design Spring 2014 May 7, 2014 21
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 Southern Methodist University EMIS 4395: Senior Design Spring 2014 May 7, 2014 22
