For telecom businesses, the hours and days lost to evaluating telecom serviceability through manual research has been a necessary cost of doing business. However, digital transformation has paved the way to alleviate this burden through data-driven processes and automated research tools.
Thanks to algorithmic evaluation and improved data connectivity, today’s telecom serviceability research isn’t relegated to manual research involving tracing routes of fiber maps. Here’s a look at how modern telecom software is achieving greater speed of service while also providing more accurate results.
The days of combing through data and maps are over.
Telecom serviceability has grown far more complex in recent years. From the rise of 4G and then 5G connectivity, to fiber, cable, and copper wired infrastructure, the task of evaluating availability at an address involves more work than ever before.
Accurate telecom research must consolidate both public and private data sets to produce the most comprehensive insights into availability at a given location. This is a tedious, time-consuming process that can be rife with errors when performed manually.
However, new serviceability research tools are able to optimize both access and consolidation of this data, centralizing this information to facilitate easier evaluation and calculation of which service option is best for the client. Evaluating a map for route diversity may still be required, but why evaluate data plotted on a map when software-led digital transformation can give you the answers?
Ultimately, automation doesn’t get rid of any of the processes used to evaluate telecom serviceability. It just means that software-based tools are doing this labor for you—and improving your efficiency and scalability in the process.
Inject intelligent solutions to your research, not mountains of data to analyze.
An algorithmic approach allows users to get immediate answers that leverage data filters and other modifications to identify the best service solutions based on factors unique to a specific location or set of locations.
Through the use of customizable features, this algorithmic software can ensure service solutions are optimized to match the needs and constraints of each potential client, resulting in better telecom service and a better overall branded experience. The use of algorithms is an important step toward intelligent operations that are increasingly necessary to tackle growing complexity within the telecom market.
Crunch numbers via an algorithm.
Data-driven solutions should decrease the amount of manual labor involved in research telecom solutions. BandwidthFinder achieves this by balancing multiple aspects of serviceability and performance to find the best technology solution for each client.
These solutions are identified by evaluating three key criteria:
- Rating Precision: This metric quantifies the proximity of telecom service to a specific address or set of addresses. The higher the rating, the greater the confidence you can have in the quality and consistency of that service.
- Technology Quality: Not all telecom technologies are created equal. By using technology metrics to quantify the infrastructure serving a location, BandwidthFinder automatically promotes the best technologies first with the ability to override the algorithm easily if needed.
- Relationship to the Data: Do you own the facility, lease it, or is it public data shared on the platform? The algorithm takes into account the relationship you have with the data and promotes the right relationship when it matters.
Reallocate your talent to other areas of need.
When serviceability research can be managed through innovative telecom solutions, your company’s staff and expertise are freed up to focus on higher-order goals such as creative problem-solving and exceptional customer service.
Ready to see for yourself how BandwidthFinder can transform your serviceability research and free you from the burden of combing over fiber maps to connect clients with the best service options? Schedule demo for BandwidthFinder today
