Turning Complexity Into Opportunity: How AI Can Transform Service Assurance in Telecom
In this article, Mohammad Shaheen, Head of Product Strategy, shares practical insights on the challenges telecom operators face on their automation journey.
Blog
12 November 2025
Author
DataOps enables efficient data capture, analytics and utilization to finally unlock new monetization opportunities from location information for MNOs.
Blog
12 November, 2025
Author
There have been numerous efforts to monetize location data over the years – some examples have succeeded, while others have failed to land. But the opportunity remains – particularly as we explore how location (and other data from MNO networks) can be used to support both service innovation and to build commercial partnerships. The problem: data processing. The answer: data processing. So, how do we move from aspiration to reality with DataOps?
User Location Data in Telecoms
In about 2010, the telecoms industry got quite excited about how user location data could be used to support enhanced security and support partnerships — with providers of financial services, for example.
These initiatives largely ran out of steam – but today, we should revisit the subject. In this blog, we’ll explore how enriched data acquisition and analytics provides a means for operators — finally — to deliver on this vision.
Location Data for Validation - Revisited
Here’s the scenario. One of your mobile subscribers wants to make a cash withdrawal from an ATM or complete a transaction with their payment card. Their bank wants to ensure that they are protected.
Of course, the bank may send an alert to a mobile banking application to check the user’s intention. But the bank could also check to see if the ATM or merchant in question is in the same place as the user at the moment services are requested.
And that’s where we return to the ideas of some years ago.
As a mobile operator, you know the location of your customers. You also know individual patterns – habitual routes, frequently visited places and so on. You also know if they are roaming and if they have passed through appropriate locations before landing on a visited network (think airport, railway stations, ports). So, you know — to a high degree of accuracy — where your customer actually is and also where they are likely to be.
Back then, we were mostly concerned with real-time location information (tell me where user X is, because I think they should be here). However, this is only part of the picture. Their journeys and habits add to this.
We can also deal with privacy issues, because you can create opt-in lists or share opt-in data from their financial providers.
If You Could Access Data from Different Sources, You Could:
- Respond to a location request from a bank
- Check opt-in status in your database
- Retrieve current location and check proximity to other locations relevant to the request
- Check frequency with which those locations have been visited
- Check departure routes to correlate with normal behavior
- Provide an update to the bank
- Check journey to the ATM
- Confirm device status before accessing the ATM
- Take actions to suppress the SIM if the user behavior seems anomalous
- Notify the user via different secure channels of any suspicious activities
So, we can go beyond the basic offer of location validation, and we can enrich the view provided to the bank with a multi-dimensional picture of location enriched with contextual datapoints. They want to protect your customers; you want to monetize assets and increase the value you can offer.
That’s the theory, anyway.
What Prevented MNOs from Taking These Innovations Further?
If that were it, though, you might be forgiven for thinking that you have more pressing priorities. But it isn’t. Your data has long been seen as an asset, but the truth is that leveraging it hasn’t really taken off in the directions that might once have been anticipated.
It’s Time for That to Change
Yes, there are multiple ways in which you can engage with external partners to monetize your data, provided you safeguard your customers – to do so requires that all stakeholders see value. But there are also ways in which you can enhance both your customer relationships and the value you secure.
The problem has really been about data visibility and accessibility. If data is scattered between different silos, in different formats, and from different contexts, it becomes difficult to rationalize it or to learn from it.
Is Data the New Oil?
One of the main problems with the ‘data is the new oil’ mantra that everyone was repeating a few years ago was that, yes, there was plenty of data – but very few could actually refine and process it to generate the expected returns.
The data could be collected but was largely restricted to silos. That is, different platforms could process their own data but aggregating it and enabling general access to different processes and systems remained a complex task. Yes, many operators have evolved data lakes, but the problem of ingesting and processing all possible sources of data persisted.
As a result, the complete picture to which we referred above and all the data points necessary to create the validation possibilities was difficult to create. We could imagine the service, because we know the information that would be required. But, very few could actually realize such a vision.
DataOps Changes the Game
At least, that was the case until the introduction of DataOps-based processing. With DataOps, you can handle streaming and batch feeds from hundreds of network and OSS/BSS sources — 5G core, RAN, IoT platforms, CRM systems — at telecom scale (50 billion+ events/day) with low-latency pipelines.
With DataOps, You Can:
- Ingest data in real-time
- Leverage different data collection protocols
- Tag and enrich data through correlation
- Build configurable pipelines
- Encrypt and protect your data
- Discover anomalies
In other words, it provides a complete methodology and toolkit that can simplify data analysis, fuelling not just your insight and discovery programmes, but also service enrichment through recovery of contextual information, as well as accurate automation.
And that’s where we are today. The kinds of services dreamt up a few years ago can now be enabled without complex integration but through efficient data discovery and open interfaces that enable information to be shared across different platforms.
The obstacles that put friction between ambition and the realization of the kind of useful services and monetization opportunities desired by both operators and commercial partners have been eliminated – with more and more examples of innovation enabled by Polystar emerging to confirm the progress we have collectively made.
In the next article in this series, we’ll focus on how this data flow can lead to new optimization opportunities, before concluding with a look at monetization in Part 4.
Read the first article in the series: How Can Data Enhance Coverage Optimization and Extension for Mobile Network Operators
