Your AI-powered forecasting solution shopping list

Telecoms has already recognized the need for AI, with implementations across predictive maintenance and traffic management. But the same can’t be said for BSS. The investment in AI for BSS has been slow and out of pace with the technological maturity needed for CSPs to stay agile.

The gap is particularly evident with forecasting. Providers sit on a wealth of BSS data that is largely underutilized, either through traditional or a lack of forecasting. By exploring AI algorithms, providers can unlock a new world of insights to help them make more informed and accurate decisions. These insights help build customer loyalty and reduce churn by better anticipating customer needs and curating offerings for more niche customer profiles.  As with any AI solution, you need the right BSS solution for your specific needs and challenges. Picking the wrong solution and partner means expense with little reward and potentially altering processes for the worse.

So, how can providers identify a solution that’s just right for them? In this blog, we’ll explore the key attributes of a successful AI BSS tool and what you should include in your shopping list.

The elements of success for an AI BSS tool

When investing in any technology solution, you need to make sure that it’s right for your needs, challenges, and goals. Not only this, but you also need to ensure that a solution measures up against others out there. If you want market-leading results, you need a market-leading solution. There are some key features you can use to assess whether a tool’s capabilities can deliver the results you’re looking for:

• Technical capabilities
• Data integration capabilities
• User-friendly interface

Let’s take each of these in turn and cover the elements that indicate a successful BSS AI forecasting tool.

Technical capabilities

The first feature of a tool we can assess is its technical capabilities. Algorithms are the core of any AI-powered forecasting tool. There’s a huge variety in algorithm approaches and complexity, making it key to explore and compare against other tools you’re exploring.

Questions to ask:

• Does the tool use “traditional” algorithms that rely on well-established statistical concepts or machine learning algorithms? Machine learning algorithms are more complicated, but they overcome the limitations of more “traditional” approaches, including analyzing larger and more varied data sources.

• Does the solution use one or multiple algorithms? Combining multiple, well-performing models can create more accurate forecasts.

Your solution is only as good as the models it uses, so make them a focus when choosing a solution.

Data integration capabilities

As a provider, you have an abundance of BSS data, and in forecasting, this data can translate directly into value. Your solution needs to be able to interact seamlessly with existing data sets, processing multiple sources for the most accurate output.

When selecting a solution, think about:

• Can the tool ingest and process all relevant data types you have? The more data it can handle, the more valuable its forecasts will be.
• Does it offer robust integration with your existing systems? A solution that excludes certain data types might limit its ability to deliver comprehensive insights.

Strong data integration capabilities translate into better, more actionable forecasts, so this should be a top priority in your evaluation.

User-friendly interface

Whilst AI tools and solutions can seem complicated, using them shouldn’t be. A solution you’re looking to invest in must be one that’s feasible to work with.

Questions to ask yourself:

• Is the solution intuitive enough for non-specialist users? A complex tool requiring extensive training or specialized knowledge can create barriers to adoption. It can also lead to extra expense and time needed to see value.
• Does it streamline backend complexity, allowing users to focus on insights rather than technical operations?

A tool with an intuitive design broadens accessibility across your organization, enabling more teams to leverage AI-driven insights.

Your AI-powered forecasting solutions shopping list

Whilst any one of the features explored above is important, the key is finding a solution that has a balance of all of them. The right solution that delivers results will have not just advanced technical capabilities but also deep data integration and an intuitive user interface.

Here’s your quick stop shopping list for your AI BSS forecasting tool:

• Advanced analytics
• Machine Learning algorithms
• Algorithm ensembling
• Integration with existing data
• Combining multiple data sources
• User-Friendly Interface

The ZIRA solution

At ZIRA, our Telco AI platform is crafted to help you unlock the maximum value and insights from your BSS data. Combining technical excellence, expert insights, data integration, and ongoing enhancement, ZIRA’s Telco AI Platform empowers you with an out-of-the-box solution tailored to your requirements for quick and significant results.