Why Telcos Need to Make Mediation More Intelligent than Ever

Posted: August 25th, 2014 | Author: | Filed under: Industry Insights, Telecom Trends | Tags: , , , | 1 Comment »

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.

Want to learn more about intelligent mediation? Download “What You don’t Know Will Cost You: Using Contextual Intelligence in OSS / BSS Operations to Protect & Increase Revenue,” a whitepaper sponsored by Comptel and authored by ICTIntuition.

A Scarlett Johansson Movie Shows How Analytics Can Make Data More Human

Posted: August 12th, 2014 | Author: | Filed under: Industry Insights | Tags: , , | Comments Off on A Scarlett Johansson Movie Shows How Analytics Can Make Data More Human

When we traditionally think of data, we think of reams of numbers and not much else. It’s a pretty cold definition, a combination of ones and zeroes that help us stay organised. Companies are starting to leverage their data for all sorts of new business applications.

In the telecommunications sector, that’s often contributed to delivering a better customer experience and supporting more informed, strategic decision-making.

The problem with data is that you need to pore through back-office systems to find what you need.

Data can help optimise processes and build revolutionary new services, but it’s long been up to the humans on the back-end to sort and process the information in a way that makes sense for the business. That’s changing. As machine learning becomes more sophisticated, that technology can be applied to data, creating a system that can learn what the company needs and deliver that information in real-time.

Oddly enough, one of the best illustrations of these capabilities was in a Scarlett Johansson movie. Raj Amin, co-founder of Mana Health, recently wrote that the movie “Her” showed a glimpse of how data can adopt a more human-like context.

Making Data Come to Life

In “Her”, Johansson plays an artificially intelligent operating system. The scene that Amin highlights is when she helps the protagonist, Theodore (played by Joaquin Phoenix), sort through his emails. As he’s directing the process, Theodore adds that he thought some of them might be funny and – lo and behold – Johansson laughs and saves the emails that she thinks are amusing.

Amin points this out as a great example of how data can become more human and, therefore, a lot more meaningful to the people who are using it. By analysing emails and then adjusting the query based on what Theodore really wants, Johansson is connecting with Theodore not just through process, but through real-time, human-like learning.

At Comptel, we’re working hard to help ensure that automation, predictive analytics and Big Data have similar powers by applying machine learning to all the information being processed. Just like the operating system voiced by Johansson, our machine learning can make use of the data that companies already have and make automatic, contextualized recommendations. That’s the foundation for our business application, Critical Alarm Protection (CAP), for example.

CAP helps communications service providers predict and prioritise network issues and site failures before they occur. Just like in “Her,” CAP can provide rankings and recommendations for different actions. If there’s potential for an outage at a specific site, CAP automatically sends a notification to the operations team, with suggestions on how to fix the problem.

When data is combined with machine learning and automation, it really is possible to make numbers feel more human. Rather than digging through data for the answers, new applications like CAP can sort through the information and suggest the right solution for you. It might not quite be like having a fully sentient operating system, but it’s a step in the right direction.

If you want to learn more about what CAP’s predictive, contextual powers can do for your business, check out our informational page, or register for our webinar on 15 August.