Transcript ism-101-redacted-optimization-and-analysis-examplex

Credit and Collections optimization
and decision support
An example of the intersection of decision tool development and
management consulting
Includes experiences from work with PA Consulting Group
Me
Kevin Ross
Assistant Professor, Technology and Information Management, UCSC
From New Zealand
PhD, Management Science & Engineering
At UCSC Since 2004
Research areas: Scheduling, optimization, networks, pricing
Worked with:
 Eli Lilly & Company
 Bell Labs
 NASA
 Thomson Reuters
 London Councils
 Fitness First
 PA Consulting Group
 Electrical Utility Companies
Kevin Ross: Network and Service Management
Professor Ross develops analytical models for three application areas
Service
Management
Optimization Minimizing cost to
deliver services
Scheduling Allocating people
and machines to
tasks
Pricing Valuing resources
in call centers
Queueing Trading off waiting
Theory time with service
quality
Air Traffic Control
Communication
Networks
Minimizing total
delay in US
Airspace
Maximizing capacity
of a communication
network
Allocating arrival
and departure slots
Switching and
routing rules for
rapid scheduling
Utilizing auctions to
allocate arrivals
Pricing models for
online advertising
Minimizing air
holding time
Managing buffers
and backlogs
Today
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Walk-through of a real consulting assignment with a
decision tool focus
Details limited due to confidentiality
Situation
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Big utility provider in a major US City
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Has a monopoly on business
Is owned by taxpayers
Heavily regulated
“Too many of our customers don’t pay their bills on time.
What should we do?”
Step 1: Understand the real problem
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What is the objective?
Who cares?
What can be changed?
What cannot be changed?
What data is available?
How available is it?
Who will use what I produce?
Step 2: Propose an approach to find a
solution
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Much better than just proposing a solution!
Nothing an outsider produces will be adopted unless an
insider is excited and owning it
Agree a plan of action
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Deliverables
Timeline
Obligations & expectations
Sample timeline for this project
Step 3: Make it happen
Understanding the dynamics…
Due date
missed
Customer up to
date with
payments
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Regular bill cycle
Deposits
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Power
is cut
Account
Charged off
Phase 1
Phase 2
Phase 3
Customer behind
on payments
Customer
received final bill
Charged off
account
Deposit Review
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Proactive telephone 
calls
Disconnect notices 
Field notifications
Disconnection
Final bill issued
Final bill collections
agency
Charge off
collections agency
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Final recoveries
Receivable is
increasing
Recovery rates are decreasing
This project focused on understanding customer payment activity and collection activity
timing in order to understand the implications of changes to the collection cycle
Designing the optimization problem
Cost
Minimum total
Total expected cost
x
x
Optimal days
until next action
Expected charge off
Time
Expected
operational cost
Tool functionality objectives
 Optimized collection timeline – “when”
 Optimized cut strategy – “how many”
 Prioritized cut list – “what accounts”
 Scenario testing
Optimization is finding the most cost effective collection strategies for all
collection actions and for all customers
Interjection
“Wow that’s cool. If you can do that then can you also add
these features…”
Decision support system
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Right actions at the right time based on consistent data with
accurate reporting and ease of execution.
Dashboard
Forecasting
Prioritized cut
list
Customer
Analytics
Optimization
Tool
Timeline
Optimization
Data mining
(eg, ROI, etc)
Scenario
testing
Optimization is finding the most cost effective collection strategies for all
collection actions and for all customers
Final tool delivered…
Data
Customer
input files
Purpose
Information on the
customers in
collections
Modules
Current Customer List
Historic Collections Activity
Parameters
Summary Dashboard
Forecast Entries
Collection Actions
Describe the basic
activities, segments
and rates used in
the model
Outputs
Excel Reports
Risk Segments
Payment Probabilities
Transfer Rates
Comparison
Dashboard
Global Inputs
Timeline Optimization
Options
User selected
information for
different scenarios,
timelines and cut
limits
Cut limits
Timelines
Scenarios
Prioritized Cut List
Step 4: Handover
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Someone has to own a decision tool
This is different from the designer
Lessons
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Lots of opportunities for people with the right skills in
data mining, analysis and optimization
The people who use the tools we develop will not usually
be experts in these areas
Unless someone owns a tool, it will never get used