Why Telcos Need to Make Mediation More Intelligent than Ever

When communications service providers (CSPs) think of mediation systems, it’s natural for them to consider billing and assurance processes. Most mediation platforms have traditionally been focused on the processing of transaction data records (xDRs). However, having too narrow of a focus on transactional data misses the big opportunities that can be made possible with analytics-enhanced data orchestration.

Data orchestration is all about making sense of the new sources of structured and unstructured data flooding networks. From social media networks to app usage, location points to alarms and probes, CSPs enthusiastically need a way to make all of this information more accessible, intelligent and actionable. Thanks to the dawn of the Internet of Things, we’re standing at the brink of a touchpoint explosion. Data is playing a fundamental role in every customer’s life. Yet while Big Data provides a significant opportunity for CSPs to make more intelligent decisions, the “data wrangling” – hand-sorting through mounds of data to collect what’s most relevant – is still consuming precious time and resources. In fact, according to recent research from The New York Times, data scientists spend 50 to 80 percent of their time just “wrangling” the data, to ready it for action.

While the xDR has usually been the only link between the network and customer data, now, the key to alleviating time-consuming data wrangling will be found in data orchestration – empowered by analytics and contextual intelligence. This will revolutionise how CSPs use data for operations, customer relationships and business planning.

A new, intelligent approach to event processing can help to make sense of this information tsunami, and fully leverage that data to make operations and businesses more intelligent, and enable real-time decision making. By combining more intelligent analysis and predictive analytics with complex event processing (CEP), it’s possible to bridge informational silos between back-office systems and glean actionable foresights that go far beyond simply processing transactions.

Imagine, for example, if your analytics-enriched mediation system could foretell when there’s going to be a service peak or potential revenue loss before it happens. Or what if OSS/BSS could communicate and correlate network and customer data, then send automated messages to customers based on current network events? Maybe it’s to notify customers of potential bandwidth issues in the next hour or to tell them about a new product.

Through data integration and orchestration enhanced with embedded analysis, that’s finally possible.

Measuring the Customer Experience

OSS/BSS systems are highly effective at processing the data related to billing and assurance, with the analysis based on xDRs. Full-blown data integration, ingestion and orchestration brings all the information from other sources into the mix, so CSPs have a full view of network and customer activity across an array of sources.

With that data collected and aggregated, machine learning-enabled mediation can have a big impact. Intelligent mediation can explore data and forecast service usage, which better informs service forecasting, operational efficiency and impact on revenue. Through a streamlined and intuitive presentation layer that allows for data visualisation through dashboards, CSPs can detect signs of service anomalies and patterns in customer behaviours that allow for proactive decision-making. By consolidating the data and learning from it through sophisticated artificial intelligence, this new kind of mediation can create displays and dashboards that help operators view opportunities and risks that were previously invisible.

Protecting Revenue with Operational Intelligence

Customer experience isn’t the only thing that can be vastly improved through intelligent mediation. Revenue loss often occurs when xDRs are lost, corrupted or otherwise arrive incomplete or malfunction in network becomes evident as a sudden drop of usage events is reported for a service. These errors can get lost in the processing shuffle, and by the time they’re detected, revenue has already suffered. Intelligent mediation can help prevent these issues.

By observing the deviations between the forecast and observed values of transaction records, the mediation system, leveraging predictive analytics, can notify operators that there’s an anomaly. Machine learning ensures that this process continually grows more intelligent and capable of more rigorous analysis in the future.

Analytics-enriched mediation empowers CSPs like never before by allowing businesses to make the most of the data that’s already being transmitted across networks and allows for real-time decision capabilities thanks to analytics and automation. With an embedded analytics-engine in place that can contextually read data and automatically send notifications to both customers and the operations team, CSPs can sidestep the data wrangling and make mediation systems – and business processes – more intelligent than ever before.