Big data and analytics offer a key source of revenue for telcos at a time when many are looking for new growth avenues, according to a new report from Research and Markets. In fact, it’s estimated that 22% of carrier app value will come from big data by 2025. 

At the same time, there remains a growing data utilization problem in the telco industry. The average telco now resembles something like the dragon Smaug’s lair in The Hobbit — packed wall to wall with treasure, with no way of benefitting from it. 

In other words, telcos are now sitting on troves of data, just like Smaug sat on top of an ocean of gold. Unfortunately, many of them lack the ability to unlock the full value of that data because they’re still relying on outdated technologies that simply can’t keep pace with the velocity of the modern world. 

How data ghosting harms telcos

Since they lack a framework for processing, analyzing, and deploying data in real time, most telcos only use a tiny fraction of the valuable data they bring in. As a result, most of their data goes unused.

We call this problem data ghosting, taken from the social media term for someone who disappears during a conversation. 

At most telcos, data flows into the organization but is rarely used for actionable insights. Instead, it quickly becomes stale and winds up sitting in a backend repository — turning into a liability instead of an asset. 

At present, data ghosting mostly results in unnecessary processing and storage costs — and missed opportunities. However, the industry is quickly changing underfoot, and data ghosting is becoming increasingly dangerous as a result. 

That’s because a growing number of telcos are adjusting their analytics strategies and implementing cutting-edge event-driven architectures. Very soon, telcos that lack advanced event-driven architecture frameworks will be unable to keep up with competitors using data to guide daily business decisions.

What’s an event-driven architecture?

An event-driven architecture is a model that uses events to transfer data across decoupled microservices so that information can move quickly from ingestion to key decision makers. At a very basic level, an event-driven architecture consists of event producers like a mobile app or retail website, event consumers (like a fulfillment center or customer response team), and an event router.

In a typical workflow, an event producer first publishes an event and transmits a message to consumers alerting them about the change. An event processing platform then processes the message asynchronously, determines an appropriate response, and sends the activity to the consumer.

As an example, a telecom subscriber hits the send button to make a call. The subscriber’s phone’s UE (user equipment) request to connect generates the event data that travels through the layers of the network to reach the 5G network core (5GC), where a plethora of network functions act on that event data:

• The authorization and authentication function ensures the device is a legitimate device and not a spoofing device that is a bot trying to DDoS the network or place a “Wangiri” (one ring and cut) call.
• The charging function and the policy control function act together to ensure the call can indeed be placed according to the user’s plan and credits (charging) and the network’s bandwidth (policy). 
• Then, the quality of service functions (also policy-related) need to route the call through the most efficient path possible.

Interestingly, with smartphones, it doesn’t even need to be a call that creates the event; it could be a simple signal strength check or SMS update—ie, stuff happening while you aren’t using or looking at your phone. 

All of these “events” summon decisions that drive actions. With the rise of 5G, IoT, and machine type communication (MTC) applications, everything related to acting on events is becoming far more complex due to the increasing number and complexity of the events themselves. 

What this means for you, the enterprise that needs to act on events quickly and intelligently, is that you will need to switch to an event-driven architecture to keep up. 

The Four Main Benefits of an Event-Driven Architecture

Here are four main benefits of event-driven architectures and the main reasons why more and more telcos are embracing them.

1. Processing streaming data in real time

We are now in the 5G era, where telcos are facing enormous pressure to ingest large volumes of data quickly and cost-effectively so that the data can drive real-time business decisions such as the ones associated with enterprise business process automation or even industrial process automation. 

An event-driven architecture enables businesses to capture events as they occur and process complex multi-step decisions in real time — maximizing application responsiveness and enabling telcos to ensure improved customer experience and optimized network utilization converting event interactions into stronger profits.

2. Reduced operational costs 

In the past, enterprises implemented batch processing systems that essentially keep collecting the data and periodically process the data in batches. However, the 5G world will be enable data at such a faster rate  that if the event is not processed immediately, the event will remain unprocessed. 

Converting business processes into event-driven architecture removes the need for these batch processes and instead enables a continuous stream of data getting processed as it is generated.

This approach of continuous processing allows the enterprise to achieve predictable response times and processing scalability, thus reducing the amount of infrastructure required to periodically process a large swath of data. This, in turn, reduces the operational cost of extracting value from the data and increases overall efficiency, productivity, and profitability.

3. Scalability 

A distributed event-handling architecture can scale as the number of entities generating events increases. This means that, compared to monolithic solutions, a distributed architecture solution can scale according to the data needs, be it the amount of data or the number of events that need to be processed.

4. Enhanced customer experience response 

By being able to do real-time analytics, telcos can identify emerging patterns as they are developing and respond as events are unfolding. 

This results in a dynamic approach to customer experience and customer management — one that makes it easier to meet consumers’ expectations around personalization without missing the moment of engagement.

Putting data in motion 

Up until recently, the telco industry relied on an “always store and occasionally process” approach. Now, the data demands this approach to change to an “always moving and always processing” mode. 

To stay relevant, companies need to shift from periodic processing to making in-event decisions based on real-time data streams. Companies that continue relying on legacy technologies won’t be able to keep up in the emerging 5G era and its increasingly complex demands. 

In short, telcos have a choice: They can continue hoarding data like Smaug and ending up with a massive data ghosting problem or they can implement a cutting-edge EDA framework for capturing, processing, and communicating events — and transform into a data-driven enterprise because of it.

Use Case: Volt Active Data and Kafka 

Apache Kafka is an event streaming platform that many telcos are using as a data backbone. A growing number of organizations are now using Kafka along with Volt Active Data’s in-memory NewSQL data platform for real-time event decisioning. 

Curious about how Volt Active Data complements a program like Kafka? Check out this ebook.