Making predictions can be a risky idea. Who, for example, could have anticipated the outbreak of COVID-19 and the impact it would bring on the world economy?
Just as it’s difficult to foresee how communication service providers (CSPs) will evolve over the next five years, so too is the challenge of predicting what assurance their businesses will require.
Same old same old
Clearly, revenue leakage, fraud, ongoing transformations and digitization aren’t going anywhere. This is a very important point. That’s why doing business assurance right, which is key to effectively dealing with these forces, will continue to be critical to the success of any CSP.
AI/ML to the rescue
Let’s talk about agility and efficiency. CSPs will continue experimenting with and creating innovative business models, based on the latest technologies. For example, there are the business models driven by 5G that focus on QoS, network slicing, and/or multi-party transactions.
To enable such advanced models, business assurance needs to aggregate and extract insights from masses of data coming from different sources, such as from the network (for slicing, QoS and ad-hoc SLAs), or CRM and billing (for transactions) and from distributed ledgers (i.e., blockchain). Moreover, the practice must be able to adapt quickly and continually to changing business models and new data sources. Since today’s rule-based technologies cannot provide the agility and efficiency necessary for these developments, the only way to become future-ready is to turn to AI/ML and robotics process automation.
This journey has already started and in five years’ time, we can expect AI/ML to be even more central to business assurance.
APIs, APIs, and more APIs
Most business assurance activities are still not API-based – a situation that simply isn’t sustainable. We’re still at the beginning of the process by which more and more BSS/OSS systems are exposing data and capabilities via standard APIs. We can expect to see the increasing proliferation of APIs. This will enable business assurance to rely mainly on consuming data and exposing capabilities via standard APIs, which will significantly reduce the overall cost of implementing and integrating business assurance solutions.
It’s now or never
The need for real-time business assurance is set to continue growing over the coming years. The problem is that while fraud management has always required real-time functionality, other business assurance domains such as revenue assurance, are lagging.
This has been a topic of much discussion. For over a decade, when people asked me about real-time revenue assurance, I always answered that while revenue assurance systems can deliver, there were two key questions that lacked a satisfactory answer: Can your OSS/BSS provide the data in real time at a reasonable cost? And what are the benefits of leakage reduction? The bottom line was that real-time revenue typically came at high cost and without enough benefits.
Today, with the proliferation of self-service and digitization, the need for real-time business assurance is greater than ever. And with the use of APIs and their associated cost reductions, real-time has become more economically viable for CSPs, placing it in a great position to finally make it into prime time.
If you aren’t moving ahead, you’re falling behind
Leakage remains a significant challenge for CSPs. According to a 2019 TM Forum survey, over 30% of these players’ revenues were not covered by revenue assurance activities. And revenue leakages, excluding fraud, represented an estimated 1.5% of the total revenues.
CSPs are always ‘moving the cheese,’ creating new business models and adding new technologies. Likewise, business assurance can’t stay put and expect to remain effective in battling leakage. Rather, its methodologies and technologies need to continually advance to avoid falling behind. For a positive change to happen, it will require CSPs to embrace advanced technologies such as AI/ML, real-time assurance, robotic process automation, blockchain, multi-partner assurance and other technologies that have yet to come to the fore.