Although the Telecom industry has largely transitioned to IP-based architectures, many carriers still retain Time Division Multiplexing (TDM) infrastructure for several strategic, technical, and business reasons. TDM continues to play a role due to legacy customer needs, cost-benefit trade-offs, regulatory constraints, and the operational stability it offers in certain parts of the network. As such, TDM assets are still common, but they are becoming increasingly expensive to support, and these escalating fixed costs are bringing them into focus as Communication Service Providers (CSPs) seek to migrate to some or all TDM to less costly alternatives.

In this evolving hybrid environment, Least Cost Routing (LCR) requires maturation beyond pure cost-based optimization. While traditional LCR engines focused solely on minimizing termination costs, modern networks require routing logic that also accounts for Quality of Service (QoS) metrics—such as Answer Seizure Ratio (ASR), Post-Dial Delay (PDD), and Mean Opinion Score (MOS)—to ensure a high-quality customer experience. Additionally, capacity-aware optimization is increasingly vital during peak usage periods or busy hours as emerging constraints, such as session limits and calls per second (CPS), drive overflow traffic onto alternate routes that may be both more costly and deliver lower QoS. Intelligent LCR systems must be capable of rerouting traffic to alternative carriers or technologies such as from TDM to Internet Protocol (IP) routes, based on these new measures of available capacity, utilization thresholds and performance indicators. This shift enables CSPs to balance cost, quality, and load in a more strategic and customer-centric manner.

Further complicating this balancing act is the fact that the fixed costs for the remaining TDM facilities are rising at a dramatic clip and will continue in a somewhat unpredictable manner over the next several years as existing inter-carrier contracts expire. This upsets the previously well-understood cost considerations for traffic routing and requires responsive routing “tweaks” to keep margins intact and above water.

In all cases, overflow has returned as the “new-old” enemy of cost optimization.

To maintain their competitive edge, CSPs must adopt routing strategies that are more adaptive and statistical, particularly as networks face higher traffic volumes, stricter regulations, and ever-growing performance expectations. This effect is amplified during the busy hour(s) as capacity ceilings are most evident then. Thus, a significantly more sophisticated approach to LCR is required.

Replace ‘Set It and Forget It’ with ‘Adaptive and Statistical’

To describe the nature of a solution, imagine traffic for a destination is divided into two groups: EXPENSIVE traffic carries a high-cost penalty for overflow, and INEXPENSIVE traffic carries a relatively low cost of overflow. The best-case scenario would be an ability to reserve capacity for the EXPENSIVE traffic, preventing overflow, and allowing intentional overflow of the INEXPENSIVE traffic at a low-cost penalty.

Of course, this would only be done during the busy hour(s). During non-busy hour(s) overflow is not an issue, and traffic will route to the “first-choice” for lowest cost.

But how do we know this in advance? Traffic data that’s collected and enriched provides deep insights about traffic patterns and behaviors, that are then used in everyday data-driven routing decisions. This data drives analytics, informing where to shore up the worst busy hour overflow offenses.

So, as the telecom landscape evolves, it has become imperative for CSPs to adopt a precise, data-driven, statistical approach to routing voice traffic. Failing to refine and optimize routing strategies can have mounting financial consequences. Without regular adjustments, networks face hidden cost penalties, especially during peak times.

Step 1 is Opportunity Identification

Data analytics and expert insights uncover suboptimal busy-hour costs and inefficiencies from the past. These patterns are used to craft more adaptive routing. CSPs that lack in-house optimization experts may be missing valuable opportunities for improvement.

When those capabilities aren’t available in-house, engaging external data analysts through a consultative approach can reveal strategic opportunities to move CSPs beyond static cost control toward continuous improvement. This subtle shift transforms routing from a set-it-and-forget-it model—where savings gradually erode—into a dynamic, optimization-driven process, where performance is actively monitored and routing decisions are continuously refined for maximum efficiency.

In Conclusion: Move Toward a More Adaptive, Value-Centered Routing Model

The telecom industry continues to evolve rapidly, and so too must the strategies that CSPs use to manage their network routing and control costs. CSPs must embrace dynamic, data-driven solutions such as busy hour routing overlays which can be brought into focus via opportunity identification. These tools empower CSPs to optimize their existing infrastructure, avoid overflow penalties, and continuously improve voice routing performance.

Discover how TEOCO’s SmartRoute can help you unlock the benefits of routing voice traffic more intelligently at https://aircomnext.com/smartroute/