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The 5 biggest challenges in telecom service order management

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Telecom leaders naturally push for increased revenues and business growth. It’s easy to assume that this means launching more products and offers as well as chasing faster, automated provisioning. However, there’s something worth fixing first. Typically 5-10% of service orders still fall out and require manual intervention, clogging up the system and increasing customer dissatisfaction. The real impacts of poor order management on telecoms are rising OPEX, delayed revenue and churn risk.

Which technologies support cost and time optimization in new network deployment?

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Telecom network operators invest billions in building their networks and accelerating network rollout cycles. Unfortunately, there are often significant losses of time and money due to outdated processes, systems and data. However, forward-thinking operators aren’t blindly allocating ever greater OPEX funds to fix the problem. They’re deploying clever technologies that cut weeks from every project.

The Hidden Millions: GIS-based Telecom Network Planning That Pays Back Fast

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Network deployment isn’t getting cheaper, which has a direct impact on CAPEX budgets set months ago. However, smarter planning is making some operators far more efficient. Operators using automated design tools are reducing planning effort by up to 70%, before any cable plant even hits the ground. This article focuses on reducing telecom infrastructure costs through data-driven OSP (outside plant) design.

How Does the Service Order Management (SOM) Process Work in Modern OSS / BSS?

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Network operators the world over are investing billions to improve their service automation levels. However, it’s not uncommon for 5-10% of service orders to fall out at some point in their end-to-end journey. This is often due to breakdowns across disconnected OSS / BSS systems and misalignments in data flows. This article breaks down the seven operational steps modern network operators follow to close the gaps and ensure seamless service order management (SOM).

The Top 7 Reasons Telecom Operators Automate OSS-CRM Data Flows

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Telecom operators rely on massive data “factories” (and ecosystems) to seamlessly handle their day-to-day operations - delivering fast, reliable and personalised services. But even the most advanced data factories can be brought to a grinding halt when the ecosystems fall out of sync. Orders fall through the cracks, billing errors multiply and customer experience deteriorates.

5 Network Resource Management mistakes that can cost Millions, and how to fix them

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Speak to anyone in the telco industry and they’ll almost inevitably want to discuss their network automation aspirations. Unfortunately, most overlook the single biggest factor that will prevent those aspirations ever being realised, regardless of how much budget is available to spend on tools and integration.
This article will look at the factor above and the four other most costly errors in resource planning and management. It will also provide hints on how to avoid or mitigate each of them.

How can Service Order Management automation reduce operational costs?

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Telecom operators have long understood that processing service orders efficiently at scale is critical to their operations. This is why countless funds are invested in making incremental process improvements and staff training to keep workflows running smoothly.

But despite these efforts, most Telcos are still bleeding money through outdated, manual service order management (SOM) systems. These legacy systems / processes slow down fulfillment, introduce costly errors and stretch operational teams to the limit.

How to effectively plan telecommunication network expansion to avoid costly mistakes?

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Most operators believe they’re planning and scaling their network efficiently. After all, they’ve hired some of the best designers in the world. Or so they think.

They may have the best human designers in the world, but what if humans empowered by static engineering rules like “fibre deeper” and “overbuild by 25% everywhere” just aren’t even close to being the most optimal answer?