21581 - SCTE Broadband August2022 COMPLETE v1

68 Vol. 44 No. 3 - September 2022 Issue technical While GDPR was developed and implemented to protect data and privacy, it has also proven to be a test of characters. There are worrying signs that in some telcos, instead of using GDPR to strengthen their business positions (consumers consistently put more trust in telcos than they do Internet companies when it comes to data security and privacy protection), the regulation has become a straightjacket put on their innovation and entrepreneurial spirit. It Starts With Probing, But Shouldn’t Stop There To overcome the challenges, telcos need to first ensure that all the necessary data is in their possession. Passive probing is an established, mature technology, and there are plenty of tools in the market that can extract data from the network systems. There are two shortfalls in many of the solutions when it comes to delivering values to telcos: data from passive probing is typically only used for network operation purposes by the network teams and stays there, and data extracted by passive probing is not integrated and reconciled with data from other internal and external sources to generate actionable and value-adding intelligence. It is true that the primary objective of probing is to provide operators with reliable data of the status of the networks, but it can serve more purposes than that. In particular, the data extracted from the networks should be made accessible to business operations, to be used as part of the input data to improve services and to deliver tangible business benefits, both in customer satisfaction and in financial returns. Data extracted by the probe engine is as important as any other data source but is not the only source. To deliver a comprehensive and holistic picture of the system, both business, and customers network operators need to integrate probing data with other types of data. The most important inputs on top of probing data include other network data like cell data and operational support systems (OSS) data. There should also include customer data extracted from the customer relationship management (CRM) system, business support system (BSS), call detail record (CDR) database, as well as devices data. The input should also integrate critical third-party data to supplement and corroborate with the operator’s own data, location data of customers and devices is an obvious example. The big variety of inputs does not only highlight the types of data a network operator can gather to generate business intelligence, it also makes it clear that the abundance and complexity of data gathered goes beyond the scope of manual crunching. It needs automated analytics to be both accurate and timely. Moreover, to make the automation smart, the algorithms need to be continuously “trained” with historical data, which demands the automated data processing platform to have strong machine learning capability. The demand for automation becomes more acute with the fast rollout of 5G networks, especially the advanced phase of 5G, with 5G radio networks on 5G core, or the so-called “standalone” (SA) mode. In the advanced mode, 5G operators are able to offer end-to-end network slicing, making a dedicated network slice available exclusively for a particular customer, Benefits of Effective Support for Customer Self-Service: