## Telecommunications Case Study

# In-House Intelligence for Network Optimization Cost Reduction

### The **client**

A European Tier-1 telecom operator that faced a strategic shift: to transform its Managed Services contract by insourcing key network optimization tasks while operating under a reduced budget.

### The **challenge**

To automate the day-to-day network optimization and troubleshooting tasks to at the maximum level to secure and even improve the network performance.

Their main issues before the implementation of the solution were:

• **Cost Constraints**  
Highly manual optimization process that made it impossible to reduce outsourcing costs.

• **Inconsistent Quality**  
Results varied significantly, depending on the individual skills of engineers, without a standardized approach.

• **Resource Limitations**  
Scaling the in-house engineering team was not feasible due to workload and budget restrictions.

### The **solution**

**Network Advisor** was deployed nationwide to automatically detect the **most significant** **low throughput related issues cell by cell**.

On a daily basis it produced plans with root causes and associated actions that leveraged the AI/ML driven framework.

#### 24 different root causes identified with associated actions, with all the **ML model accuracy metrics >97%**

#### **Integrated ticketing system** provided the ability to orchestrate and dynamically track the action plan

### **Benefits** for the client

## Automated Action Plans at **Cells Level**

Precise, scalable optimization across the network.

## Rapid Deployment in Just **2 Weeks**

Fast setup and integration, accelerating time-to-value and minimizing disruption to operations.

## **2.5x** Augmentation Effect

Delivered the equivalent impact of more than doubling the engineering team—without increasing headcount.

## **100%** Consistency and **90%** Accuracy

Reliable, repeatable results with minimal variation, supporting high-quality network performance.

## **90%** Reduction in Troubleshooting Effort

Significantly less time spent on manual analysis, freeing up engineering teams for higher-value tasks.

## **Expansion** to Other Areas

The solution was scaled to address additional challenges, including call drop rates, access issues, and sleeping cells.