The pace of technological change has been speeding up at a seemingly unprecedented pace in the 21st century, and in few places is that more evident than in the telecom sector. Just a few short decades have taken us from what would now be considered legacy telephony through 4 generations of broadband cellular networks—with a fifth on the way. In the meantime, things like VoLTE and VoWiFi have become commonplace offerings in your typical telco operator’s portfolio. The race to provide new service offerings and update the functionality of existing ones is underway, and it’s already pretty heated.
When it comes to new service offerings, one of the most important factors that will determine the success of your rollout is time-to-market, i.e. the span of time it takes your offering or update to go from conception to actual implementation. If you’re trying to be the first operator in your area to roll out 5G, for instance, there’s a real competitive advantage to moving quickly so that no one else beats you to the punch. By contrast, if you’re simply making improvements to your existing network, the faster you roll out updates the more quickly your customers will (hopefully) benefit from improved quality of service (QoS). Unfortunately, speeding up your time-to-market often feels like a daunting task.
If that's the case for you, not to worry—here are five strategies telco operators can use to improve their time-to-market.
Of course, as your service offerings become more complex, so too do the resources at your disposal. To wit, telco operators have greater access to advanced analytics than ever before—meaning that during the design stage of your service development you can analyze previous customer behavior and previous rollouts to predict likely hurdles and better define your needs. This can be an effective way to jumpstart your design process, with one crucial caveat: you need to have a history of effective data collection. If, for example, the results of your past conformance tests are standardized, readable, and accessible, then they’ll make effective fodder for data-driven insights. If, on the other hand, your tests have been historically disorganized and lacking a repeatable framework, and the results are stuck in an excel spreadsheet on someone’s laptop, your analytics won’t have very much to go on.
2. Dynamic Bandwidth Allocation
One of the other distinct challenges in rolling out a new service offering is provisioning bandwidth appropriately. Since you don’t yet know (analytics aside) what the load on your new service will be, it’s difficult to ensure that it will have the necessary bandwidth to hold up under heavy traffic. Luckily, modern telco operators have the ability to implement dynamic bandwidth allocation within their existing network structure, meaning that the service offering will have bandwidth on demand without the need for an immediate outlay of physical resources prior to deployment. This can give operators a degree of flexibility when it comes to releasing a service whose likely usage rates aren’t yet known or easy to predict exactly.
3. Test Automation
Generally speaking, one of the most significant factors impacting the length of a particular project rollout is testing. Once the design for a given service offering is completed and your team has finished implementing that design, test engineers need to perform conformance tests, functional tests, drive tests, acceptance tests, etc. As telco networks get more complex, these test flows tend to happen more and more slowly, meaning that service verification increasingly has the potential to be a significant bottleneck—especially if your test engineers are also the ones who are slated to fix whatever bugs are uncovered. By automating these service verification passes, you can remove this bottleneck practically overnight. Instead of waiting around for a series of laborious manual tests to be completed, you can power through hundreds of use cases per day, all while ensuring high quality reporting. Think back to our first tactic; any improvement in reporting quality also stands to empower smarter analytics workflows, producing a cascade effect of operational efficiency.
4. Reduction of Bottlenecks
Just as manual testing is a potential bottleneck that telco operators need to avoid in order to speed up time-to-market, so too are any points in your process that require the input of a specialist within your organization. I.e., if there’s only one person who can perform a particular task (say, analyzing test results to locate bugs), you run the risk that they won’t have the capacity to take on everything that needs doing in a timely way. The trick here is to reduce the number of touchpoints that require specialized knowledge, such that the employees who have the capacity to take on tasks and solve problems are actually put in a position to do so. There’s any number of strategies for doing this, depending on the precise nature of your existing corporate structure and workflows. If we take testing as a representative example, reducing specialized knowledge bottlenecks might mean incorporating keyword based testing into your service verification. Keyword based testing is designed to produce test reports that make use of recognizable keywords, making them much more readable (and thus much more actionable) for personnel who might otherwise lack the technical know-how to interpret test result can find suitable tasks, whether that’s fixing simple bugs or performing back-office processes.
5. Continuous Integration
Continuous integration and deployment (CI/CD) is frequently talked about in tech circles, but it can certainly be applied to telco operations as well. The basic concept here is that multiple teams working on the same project will centralize their efforts into one primary repository multiple times per day in order to ensure that any design issues are identified as early as possible. As a subset of agile development, CI/CD is designed to promote just that—agility. As such, it can be a big help in terms of increasing deployment velocity. The caveat, of course, is that it also requires continuous testing in order to uncover bugs early and often. Again, this is an area where automated regression tests could quickly become a necessity if you’re going to focus your engineering resources on your most pressing goal: improving time-to-market.