Unlocking Better Telecom Infrastructure Planning
Published: March 14, 2023
Change is the only thing remaining the same for telecom network operators. But by leveraging machine learning and leading indicator data on a single planning platform, telecom companies can improve the quality and speed of their planning and decision-making and proactively address changing conditions.
This approach can also reduce reliance on reactive measures such as expediting purchase orders and building up inventory in response to shortages. By streamlining and modernizing the planning process, companies can improve efficiency and adaptability in the face of changing demand.
We’ve identified five principles for unlocking better telecom network infrastructure planning:
1. Siloed Planning Processes Lead to Inefficiencies
Traditional planning processes in the telecommunications industry tend to be reactive, siloed, and rely on manual processes, which can be inefficient and widen the gap between demand and supply.
2. AI/ML-Driven Planning Platforms Improve Demand Planning
Consolidating data and leveraging machine learning in a single planning platform can improve demand planning by bringing more data into the process and enabling planners to work on the operational horizon rather than short-term tactics.
3. Network Visibility Is Critical
Building critical supply chain capabilities involves creating visibility into the network and utilizing a configure-to-order-based planning model to predict component needs and ensure availability for processing.
4. Defined Business Rules Help Allocate Inventory
In instances of constrained supply, defined business rules can help allocate inventory to meet business objectives, including maximizing fill and prioritizing certain products.
5. Digital Transformation Helps Unlock Project-Based Planning
Improved project-based planning in telecommunications infrastructure can be achieved through digital transformation leadership programs and by establishing a center of excellence to enable the rapid development and evaluation of prioritized use cases.