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| Case Study |
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Optimization of Siebel CRM application helps consumer
product company improve decision making capability
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Leveraging its expertise on Siebel Analytics, Patni helped a leader in the consumer products marketplace
stabilize and increase application performance of its CRM application.
The Client
The client is a world leader in the consumer products marketplace engaged in the development, manufacturing, and marketing of a wide range of products across 200 countries.
The Challenge
The client had implemented Siebel eConsumer Goods and Siebel Analytics for
account planning and management. The application enabled the client's account
executives to systematically build and monitor their account plans including trade &
promotions management. However, in order to enhance the efficiency and
effectiveness of the system, the client needed to carry out enhancements to meet its
evolving business needs. Some of the critical users were also unhappy with the level
of information available in the dashboards and the time it took to obtain information
updates for their day-to-day planning activities.
Having implemented a complex and highly integrated system, the client wanted a
partner who had the wherewithal to:
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Optimally transition, stabilize and support the application |
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Provide quick turnaround on functionality enhancements to improve
acceptance & adoption of the solution |
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Align the application to business needs of the account managers and extend
the application user base to cover marketing and finance managers. |
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Serve its long-term plans and establish Siebel as the backbone for account
planning and management needs covering trade promotions, deductions
and settlements. |
The Solution
Patni worked closely with the client's IT and business teams to transition the application &
ensure its adoption by the users.
Patni ensured the following:
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Defining an aggressive timeline of 4 weeks each for knowledge and responsibility
transitioning |
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Facilitating 24x7 availability using a lean multi-locational support team. This included
logging and assignment of trouble tickets, prioritizing calls according to severity,
providing case visibility and service metrics |
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Identifying the service levels that were to be adhered to for providing an initial
response, resolving user queries and fixing bugs |
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Quickly augmenting the team to takeover and complete work in progress from the
outgoing implementation team |
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Automating routine support and maintenance activities by development of tools and
application enhancements. |
Actual service levels were then tracked, monitored closely and discussed with
the business users to fine tune the response requirements and staffing. The
team from Patni quickly built a sound understanding of the application
functionality and technical design, working through and resolving several gaps
and inconsistencies in the documentation
The team worked to quickly resolve issues pertaining to a significant
percentage of dashboards for demand planning, finance & marketing which
were required to be changed or completely replaced. This restored the user
confidence in the system, enabling the users to add value to the
enhancements being proposed to the system
As the client user base was new to a service level based support system, the
team from Patni put in extra efforts to handhold the user. This included
standardizing incorrect and inconsistent priority classifications of trouble
tickets by business users. The complexity of the solution can be seen from the
fact that the scope of the application covered 197 DAC (Direct Action Control)
jobs, 60 analytics reports, 20 business processes, 40 business entities and 26
interfaces across 5 systems.
Achievements
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Over 95% defect free enhancements delivered. |
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Over 90% reduction in issues during critical batch processing |
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100% system uptime |
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Maximum case age reduced from 3-4 months to 4 weeks. |
The Benefits
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Effective application support through better and more consistent
categorization and tracking of calls |
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Improved application performance through root cause analysis and
optimization of existing interfaces of the batch job cycle |
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Increased application stability through implementation of crucial design
modifications |
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Substantial cost savings by leveraging the offshore model |
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Improved decision making capability through creation of Waterfall &
Demand Planning reports with complex representation of data |
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Optimized system for faster reporting performance. For example, the
demand planning report can be generated within 2 minutes as compared
to more than 12 minutes earlier. |
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