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Managing Equipment OPEX Through Data

Seize the data. This should be the mantra for IT professionals heading into 2020.

The telecommunications industry is, by and large, missing out on the advantages of a data-driven approach to operational cost-savings. Hardware monitoring suites have proliferated. Moment-by-moment network performance information is available. Every truck roll, warranty return, and hardware repair and redeployment incident is tracked somewhere. Yet despite all of this information, many IT professionals still feel they are making critical decisions in the dark.

IT professionals who are looking to achieve real business intelligence and want to slash operating expenditures (OPEX) can take advantage of the tremendous amount of data available to do so. Here’s how network providers are making this happen.

Key Barriers to Network Insights

The problem is two-fold. A lack of transparency among service providers and sometimes between internal departments means information often remains siloed. Even when data is shared, many enterprises lack the specialized analytics and visualization tools to realize actionable insights.

These are not low barriers to overcome, but there is ample financial motivation for network operators to identify and implement high-performance solutions. In our global experience working for thousands of clients, including tier 1 telcos, we have found that 30 percent of network maintenance costs are avoidable. Network operators are paying to fix products that never failed, upgrading too early or too late, wasting money on technician call-outs, and leaving value on the table when they decommission hardware—and that’s just the beginning.

Millions of dollars are on the table, but network operators need to know where and how to look.

Immediate Targets for OPEX Savings

Fortunately, data-driven analysis can point network operators toward solutions with significant short-term ROI potential. Following are some areas of opportunity to consider:

  • Track root causes of equipment failure, identify failure patterns and uncover environmental contributors to network outages in order to respond with predictive maintenance and upgrade strategies.

  • Evaluate supply chain performance, including total cost of ownership, manufacturing errors, and software issues, to make informed equipment purchasing decisions and reduce lifetime maintenance costs.

  • Answer the “repair or replace” question based on more than mean time to failure, making accurate, granular forecasts of impending issues.

  • Identify specific technician training gaps and direct the resources to help eliminate configuration, software installation, and diagnostic errors.

  • Improve field service deployment to reduce emissions and expenditures and tailor other cost-saving logistics optimization initiatives.

  • Identify remarketing opportunities for surplus network assets to divert hardware from e-waste streams and capture the value in this equipment for reinvestment.

Telecom enterprises are striving toward a fully predictive stance on network assets in order to maximize uptime and seal competitive advantage. Real-time data and powerful analytics can make the requisite operational adjustments possible.

The question is whether to pursue internal development of custom business intelligence tools or whether solutions on the market can fill the gap and deliver immediate bottom-line impacts. The answer will vary for each network operator, but the sense of urgency toward capturing and utilizing existing network data to deliver OPEX savings should not.