Efficiently manage product creation, launch and management of a unified catalog, and incorporate business analytics required to anticipate, track and monetize the needs of customers.
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Challenges
- Business data validation: Unable to detect incomplete customer data.
- Operations data validation: Unable to detect incomplete OSS data.
- Subscriber data validation: Unable to detect incomplete subscriber data.
- Network data validation: Unable to detect network inventory and configuration data.
- Product data validation: Unable to detect inconsistent product configurations.
- Marketing data validation: Unable to detect inconsistent marketing information across the footprint.
- Product catalog validation: Unable to detect incomplete Product catalog data.
- Multi-point distribution: UUnable to distribute same data to multiple BSS / OSS.
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Results
- Operational impacts.
- Cost overruns.
- Data reconciliation nightmares.
- Delays in new product roll-outs.
- Revenue losses.
- Migration delays.
- Lack of confidence in integrating with new OSS / BSS applications.
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Tool (Solution): Coscend's Product Management Service Factory
A set of automated tools that help CSPs personalize their services by shifting from network-centricity (using network competence) through service-centricity (using service competence) to customer-centricity. It comprises of:
- Business Data Validator
- Operations Data Validator
- Subscriber Data Validator
- Network Data Validator
- Marketing Data Validator
- Product Catalog Validator
- Mediation Multi-point Distributor
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Key Features
Enable CSPs to present customers with an intelligent catalog of services in the context of several critical success factors.
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Benefits
- Provide the much needed process automation.
- Help create and integrate as a building block into a unified catalog.
- Adapt and integrate as building blocks to create new products suitable for new environments intrinsically.
- Operational efficiency from automation.
- Standards-based low cost tool.
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Impact
- Realize higher process efficiency.
- Overcome the current data intelligence challenges.
- Rapidly re-package a complex combination of services into a product that is personalized.
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