Enabling digital transformation: Is your network ready?
Why is data quality key in digital transformation?
Numerous communications service providers (CSPs) across the globe have embarked on a digital transformation journey. Their primary goal? To drive automation and reduce costs while continuing to provide innovative offerings to their customers. But to reach these goals and achieve the desired level of automation, they must first overcome a key challenge common to multiple CSPs: the current state of their data estate.
Managing major incidents is key when it comes to a CSP’s overall success, as quantified by the standard of its operations and how well it meets customer needs. This is because QoS may be negatively affected by unforeseen and unplanned network interruptions which in turn causes subscriber frustration thereby increasing the likelihood of churn.
CSP teams have typically worked in silos—whether it’s in operations, customer services, sales or engineering. This has led them to use different platforms that hold multiple instances of data, much of which is both misaligned and inaccurate which in turn leads to a distorted understanding of the data Inability to address this data quality management issue is the primary cause of delay and failure of most transformation initiatives. Effective incident management (trouble tickets, workflows and their associated processes) is very difficult to achieve if the underlying data is not accurate and therefore cannot be applied to achieve satisfactory results. Longer term, this may curtail digital transformation ambitions.
How can real-time live network topology platforms help in your digital transformation journey?
Tools now exist to improve incident management by addressing data quality and integrity issues across inventory and other platforms using agile modeling and semantic inference technology that enables quick reconciliation between network and inventory.
To ensure success, CSPs need an end-to-end solution whose platforms not only support business processes but also allow for management of data integration requirements, data quality and integrity, and meet data migration requirements. Even more importantly, they need a solution that can achieve this by providing flexible, agile modeling capability that can adapt to the network’s dynamic environment within short timelines.
Platforms like Nova Context use technologies originally developed for the semantic web to understand the relationships between data from multiple disparate systems.
Over the past 12 years, EXFO has developed and refined these technologies to a level where they can rapidly load, analyze and link data in a fraction of the time it would take to achieve the same results with traditional data integration and reporting techniques.
This innovative data modeling technique puts data quality and data integrity at the heart of the deployment approach.
Today providers are more frequently using platforms such as Configuration Management Databases (CMDBs)—which were never designed to manage the complex modeling aspects of a telecom network despite being very well suited to IT networks where the hierarchy is less complex. They are used to manage various systems in order to know what assets exist in those systems and to provide the awareness of configuration data and the confidence that it is accurate. The advantage of CMDBs is that they are good at storing infrastructure and relationships, they are also adept at discovering IT based infrastructure and relationships. On the other hand, they are limited when it comes to discovering the complex nature of a Telecoms network, specifically the multi-technology transport network. They are also weak in managing data quality and data integrity which continues to be a significant challenge in telecom network inventory. This is significant, because for transformation projects to be successful CMBDs require data quality and data integrity, the absence of which has implications for processes such as service impact analysis and change impact analysis as their effectiveness will be diminished without it.
This is why a combined approached of CMBD and Nova Context (formerly known as EXFO Ontology) can be a powerful means of mitigating data accuracy risks. Context collates data from the network, the associated inventories and their relevant stores, plus the CRM platform (end to end). It therefore aligns the network, services and customer information into a logical model streamlining all the data which is then fed easily to the CMDB giving it an accurate model of the telco network and its associated services which it can utilize. One advantage Context has making it particularly strong and differentiating from other offerings, is its ability to efficiently manage data quality, increase the accuracy of the inventory records and overall improve efficiency of CSPs. It enables efficient reconciliation and data quality management processes helping CSPs to increase the quality of their inventory data. Simultaneously, the CMDB can take care of what it was built for, a platform to understand the IT environment including service impact analysis, asset management, compliance, and configuration management.
Benefits of using Nova Context
CSPs have a lot to gain from using real-time active topology platforms like EXFO’s Nova Context for automation of service and customer assurance. Ongoing business impacts include:
Comprehensive topology for maximum ROI
- End-to-end service assurance and inventory is a common goal.
- Single source of cross-domain, real-time inventory reduces operational and capital costs.
- Service assurance outcomes and process efficiency is maximized by automation and accurate topology.
Lower total cost of ownership and risk compared with traditional approaches
- EXFO’s Nova Context eliminates the costs and complexity of traditional integration.
- Deployment timeframes are incredibly short.
- Deployment teams are very small.
- The system can be maintained and expanded by the customer or SI.
Plus, EXFO’s Nova Context is unique—and it works
Many service providers have attempted to create wider topologies, but Nova Context supersedes the scope and capability of other solutions at a fraction of the cost and timeline, as evidenced by several top CSPs who have successfully opted for the Nova Context platform.
Conclusion
Many providers working to transform their businesses are introducing a more streamlined and efficient customer focus within the service management and assurance domain in the aim of boosting customer satisfaction and revenue while reducing operational costs.
To do so, they are looking to overhaul platforms within their OSS and BSS estates, introducing new platforms and processes that can drive these business aims and further accelerate the digital transformation journey.
CSPs with an effective root cause investigation process like Nova Context are empowered to take swift action to restore service to its usual conditions and deliver a consistent level (and high standard) of service to their customers.
