Ticket allocation problem optimization in an IT service support company.

1. Bhawik Kumar Raja
Prashant Kumar
K.Venkataraghavan
Department of Management Studies, IIT Madras

2. Incidence Management
Agenda
 Introduction
 Literature Review
 Model Development
 Implementation
 Implications
 Conclusion
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3. Incidence Management
Introduction
What is Incidence Management ?
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4. Incidence Management
Backlogs in Incidence
Management
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Common Issues in Incidence Management

5. Incidence Management
Literature Analysis
 Examining Capability of the IS Desk
(Simulation environment for IT service support processes)
 Tickets are considered as discrete events occuring with a certain
probability
 Tickets are of different nature like SAP, Networking etc
 Tickets are assigned to various consultants with varying capabilities
 Time taken to solve tickets vary with consultants
 IS is SLA bound
 Helps to optimize help desk resources
 Auction based Models for Ticket allocation in IT Service Delivery
Industry
 Online scheduling of tickets
 Inefficiencies in the standard model are overcome
 Ticket is allocated to the member who bids the least time
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6. Incidence Management
Model Development
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Gaps in Literature
• The Papers were online scheduling models
• Objectives were in broad are of Incidence Management
• Our Model is focused on Decision Making in allocating Backlog tickets
Backlog Situation
Back Log tickets
Tickets
-Types
-Complexities
Team Leader
[OBJ]
Minimize Time
Consultants
- Expertise
- Availability

7. Incidence Management
DSS Model
 Optimization of problems with few alternatives – use decision tables,
decision trees
 Optimization via algorithm – use linear and other mathematical
programming models, network models
 Optimization via an analytic formula – example Inventory models
 Simulation
 Heuristics – Use Heuristics Programming and expert systems
 What if Analysis – Financial Modeling, Waiting Lines
 Predictive Models – Forecasting models. Markov analysis.
OBJECTIVE Function
N N N N
Minimize ∑ AmiTai + ∑ BmiTbi + ∑ CmiTci + ∑DmiTdi
i =1 i =1 i =1 i =1
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8. Incidence Management
DSS Model
Constraints Set 1
N N N N
∑AmiTai + ∑BmiTbi + ∑CmiTci + ∑DmiTdi <= Hi
i = 1 i = 1 i = 1 i =1
Hi is available time for a consultant i.
Constraints Set 2
N N N N
∑Ami <= A, ∑Bmi <= B, ∑Cmi <= C, ∑Dmi <= D
i = 1 i =1 i =1 i =1
Constraints Set 3
A mi , Bmi , Cmi , Dmi > 0 and integers
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9. Incidence Management
Implementation – Prototype
Testing
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Prototype implemented using Excel Solver

10. Incidence Management
Implementation – user
Interface
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11. Incidence Management
Implementation - Lingo
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12. Incidence Management
Implications, Limitations and
Future Scope
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IMPLICATIONS
• Aides judgment in allocation of Backlog tickets
• Optimize resource usage
• Helpful in Identifying marginal utilization
LIMITATIONS
• Only few variables are considered in this model
• Tests were done with synthetic data
• Soft Variables like Knowledge Management, Resource Related risks have not been included
FUTURE SCOPE
• Constraints on Ticket type i.e. certain tickets cannot be assigned to certain users
• Apart from time constraint include a schedule constraint
• Incorporate existing workload of the consultants
• Incorporate ticket dependencies
• Look at knowledge optimization Issues
• Incorporate Prediction Capabilities.

13. Incidence Management
Thank you
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