- Deliver hyper-personalized customer experiences
- Predict the products and services that customers will want, and competitively deliver them
- Accelerate time to market with features and services
- Predict and prevent churn
- Reduce costs
Yet, for many service providers, a major stumbling block comes from a lack of organization in the way their data is stored, categorized and accessed. Indeed, data organization is crucial to an operator’s ability to make use of the information in their systems and allow its decision makers to extract the business insights they need to add value to the business.
The service provider’s data challenges
The challenges that service providers most frequently face while trying to organize their data for better accessibly, visibility and ensuring faster time to insight, including:
- Quality, where poor data quality results in poor business decisions;
- Management and governance, which help to create and maintain data quality, but which are difficult to execute when managing multiple data sources and large quantities of streaming data, while at the same time, trying to ensure adherence to privacy regulations;
- Speed, which is critical in operational systems that require real-time decisioning, but is difficult to achieve when there are many legacy systems in place;
- Completeness, mandatory for building effective data models that drive insights, but which is often unattainable with data being dispersed across many siloed organizational systems;
- Sharing among teams, departments and operating companies, which frequently is not possible due to the prohibitive nature of cost, complexity and organizational differences in data sources and uses.
Overcoming the challenge
The value of public cloud
Overcoming these challenges and improving how data can be used means first prioritizing public cloud over on-premises data centers.
The benefits of cloud for scale, elasticity, agility and cost-efficiency are well established. But there are additional data-centric benefits of cloudification that may not always be top-of-mind.
These, though, are equally strategic to the success of the service provider’s business, and include applying analytics for:
- Deriving new customer insights from usage data
- Developing new data-driven solutions
- Unlocking value that is often trapped in data
The value of well-organized data
Well-organized data is likewise of utmost importance. When data is well-organized, analytics can be applied to measure and optimize the customer journey as well as to inject intelligence into customer-related workflows.
And when decomposing the journey into the domains and entities that comprise it, service providers can also identify the main KPIs that matter most to customers and the business. Doing so enables them to gain the insights they need to optimize engagements, drive intentional journeys, prevent fallout and improve business outcomes.
It is only with the kind of intelligence that you can get from well-organized data (along with well-trained machine learning algorithms and high-performing analytics) that service providers can know when to introduce recommendations or execute predictions for delivering hyper-personalized experiences, regarding product fit, price plans, offering configurations, support channels and more.
Accordingly, before launching the migration of the data center to the cloud, it’s critical to make sure that the migration of the actual data to the cloud is meticulously planned and that the data is well-organized so that it can be ready for analytics and insights.
How Amdocs can help
Amdocs Cloud Services enables service providers to plan the data migration and organize data so they can extract all the strategic insights they need to deliver value and drive the business.
The offering comprises three key practices that help ensure better data management:
Data build to help migrate data to the cloud and modernize the data infrastructure with:
- Building a smart data warehouse in the cloud
- Data integration and cloud onboarding
- Data quality, governance, privacy and compliance services
AI and analytics for faster insights and improved automation with:
- An AI catalog of solutions
- Machine learning operations services (MLOps)
Managed data and MLOps automation to operationalize and govern data and AI with:
- Data managed services
- Data analytics as a service
To learn more about how Amdocs can help you plan, organize and migrate your data to the cloud, reach out to me at email@example.com.