Transcript The Contact Center Supply Chain: Framework, Problems

“If the Phone Doesn’t Ring, It’s Me”:
An Services Science Success Story
Professor Vijay Mehrotra
[email protected] / [email protected]
Presentation Roadmap






Intro to Call Centers
The Business Problem
The Statistical Problem
The Organizationational Problem
The Results!
Summary: Rich Area For Research
What is a Call Center?


Any facility or group of
facilities which has the
processing of telephone
calls as its primary business
purpose
EXAMPLES:




Technical Support
Airline Reservations
Catalog Sales
Financial Transactions
Processing
Why Call Centers?

Ubiquitous



Growing Business Importance



Employ over 3% of US Population
Estimates: 78,000 centers (US), 28,000 (EUR),
Front Door to Firm (Over 80% of Businesses)
Impact of Poor Service on Customer Loyalty
Co$tly to Operate
Why Call Centers?

Data Rich

High Complexity




Stochastic Demand, Variable Process Time
Mass Customization / Segmentation  Variety
Email, Chat, Web  Multiple Channels
People Costs Dominate


Labor Accounts For 60-75% of Overall Cost
Agent Turnover >>30% Annually Across Industry
The Complexities of the
Technical Support Call Center
Operational
Economics
Management
And Organizational
Behavior
OR/ Statistics
Business
Processes
Telecommunications/
Information
Systems
Engineering
Disciplines
I/O
Psychology
Presentation Roadmap






Intro to Call Centers
The Business Problem
The Statistical Problem
The Organizational Problem
The Results!
Summary: Rich Area For Research
Business Problem


Client Faced a Significant Problem:
 Too Many Calls, Too Much $pent
on Technical Support
 Nearly 3x Industry Norm as a %
of Revenues
What To Do?
 Step 1: Move From HQ in PA to
Places With Lower Labor Costs
 Step 2: ????
“Tell Your Statistics to Shut Up”

FC
Model
Historical
Data
Business
Judgment

Traffic
Forecasting

Initial Engagement
 Develop a Call Forecasting Model
Quantified the Relationship Between
Software Units Shipped and
Incoming Calls
Call Intensity Factor – TOO HIGH!!
Our Solution: “More Statistics!”

Developed an Integrated “Call Stopping” Methodology

Solution is Obvious in Hindsight…

..The Story Behind the Solution is Instructive
Inf o to
PD/DOC
Call Tracking
Call Analy sis
Research
Knowledge
Base
Inf o to
TSRs
Improv ed
product
Direct-to-customer
support channels
(non-telephone)
Improv ed
phone serv ice
Presentation Roadmap






Intro to Call Centers
The Business Problem
The Statistical Problem
The Organizational Problem
The Results!
Summary: Rich Area For Research
Early Discoveries

“We Use a ‘Wrap-up’ Coding System.
It Has Been Working Just Fine For
Us.”
 Consistently Misused By TSRs
 Applies to Known Issues or Generalities
 No Drill Down to Root Cause or Solution
 First Step: Paper Tracking
 Small Group of Agents
 Instructed on How to Track Call Content
 Key Principle: Track What Caused the
Customer to Pick Up the Phone
Early Discoveries
Early Discoveries


Good News!
 TSRs Could Track Effectively
(When Taught)
 With Support From Product
Experts, We Could
 Identify Recurring Issues
 Classify Cases
Revelations!
 Top 50 Issues > 30% of Calls
 Top 100 Issues > 40% of Calls
 Rarely Did an Individual Issue
Comprise > 1% of Calls
 Substantial Differences in AHT
Across Different Top Issues
Major Implications…

Why Individual Agents Don’t
“Know” Call Content Patterns:



Typical Agents Handles Approximately
Calls Per Day, 150 Calls Per Week
 Over 300 Agents
 High Variance in Calls Handled
30
For an Issue with p=0.01:
 P(“Average” Agent Sees Any Issue
More Than 2 Times in a Week) = 19%
Lesson: Beware the “Anecdotal Data”
Modeling Challenge

How to Understand Call Patterns?



Too Many Calls For Two Assigned Analysts
Solution: Use Random Sampling
How to Determine Sample Size?

No Shortage of Trials (45,000 Calls/Week)
 Accuracy of Probability Estimates?
 Limited Skilled Resources, Lots of Skeptics
 “What Do These People Do All Day?”
 Sample/Classify Enough to Ensure Major
Issues Are Identified
 Get Analysts’ Buy-In on Feasibility of
Sample Size
Presentation Roadmap






Intro to Call Centers
The Business Problem
The Statistical Problem
The Organizational Problem
The Results!
Summary: Rich Area For Research
Organizational Challenges
Product
Mktg
Eng
& Doc
Sales
Technical Support
Organizational Challenge


Technical Support Holds Low Status in Business
 Perceived Cost Center
 Perceived Drain on Bottom Line
 No Credibility Internally (Historical, Endemic)
Marketing and Sales Driving Product Direction
 Typical For Software Industry
 “More Features, More Features, More Features”


Puts Pressure on Engineering Resources
Historically, Crowded Out All But Most Egregious Fixes
Our Solution: Crosses Many
Organizational Boundaries


Relied on Data Collected Through New CRM System
 System Design Was Largely FUBAR
Cross-Functional Team with Active Representation From:
 Product Marketing
 Engineering and QA
 Documentation and Web
Inf o to
PD/DOC
Call Tracking
Call Analy sis
Research
Knowledge
Base
Inf o to
TSRs
Improv ed
product
Direct-to-customer
support channels
(non-telephone)
Improv ed
phone serv ice
Organizational Challenge

Why Did We Get Traction? Several Reasons:

Exploited Corporate Visibility of Problem



Identified Champions at Leadership Positions


Perceived “Crisis”
Made our Cross-Functional Team Politically Attractive
Engineering, Documentation Heads
Credibility of Process and Analysts


Spoke Language of PMs, Eng, Doc
Provided Detailed Information
Presentation Roadmap






Intro to Call Centers
The Business Problem
The Statistical Problem
The Organizational Problem
The Results!
Summary: Rich Area For Research
Results: Major Savings
Typical Customer Calling Behavior
0.2500
Calls in the Month
0.2000
0.1500
0.1000
0.0500
0.0000
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Months Since Purchase
Results: Major Savings
Top 50 Isues:
Comparison of V2, V3, and V4
35.00
Percent of All Calls
30.00
25.00
20.00
15.00
10.00
5.00
0.00
1
4
7
10 13 16 19 22 25 28 31 34 37 40 43 46 49
Cumulative Questions
5
Presentation Roadmap






Intro to Call Centers
The Business Problem
The Statistical Problem
The Organizational Problem
The Results!
Summary: Rich Area For Research
Vijay’s View on the Value of
Services Science Research
“If you hold on tight to what you think is your thing,
You may find you’re missing all the rest.”
Dave Matthews
Research Opportunities

CRM Value Creation Success Stories

What are the Key Characteristics?




Process Improvement Accompanying Tech Innovation
Quantifiable Business Results
How Do We Study This?
Design for Supportability / Software QA

What are best practices? Who is doing this well?



Enterprise Software Firms
Internal IS Groups
Fair and Accurate Measurement Methods?
Research Opportunities

Ethnography: Technical Support Operations


Huge, Growing, and Barely Researched
Successful Research Requires Skills From




Strategy, Organizational Behavior
Information Systems
Decision Sciences
Automated Call Content Segmentation


Rich problems in AI / CS Realm
“Sexy” Solutions