BLOG | Jan 19, 2022

$6 Million Savings: How Rapid Insights Led To Valuable Network Upgrades

When a large government agency decided to refresh its infrastructure down to Layer 2 switches, Forward Networks data delivered over $6 million in savings. Like many companies around the world, this organization had challenges getting full visibility and the structure of its network, which had grown organically over time.

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Dawn Slusher
Sr. Marketing Manager

Who should read this post?

IT teams looking to upgrade their network from outdated, unnecessarily expensive equipment
Network engineers and architects seeking efficient inventory and topology management tools
Organizations managing large networks comprised of many different vendors, technologies, and deployments, including on-prem and cloud

What is covered in this content?

How Forward Enterprise saved a large government agency from device failures, support for unnecessary devices, and wasteful expenditures
How Forward Enterprise allowed this agency to clearly understand their network topology and to quickly find information in an intuitive manner

When a large government agency decided to refresh its infrastructure down to Layer 2 switches, Forward Networks data delivered over $6 million in savings. Like many companies around the world, this organization had challenges getting full visibility and the structure of its network, which had grown organically over time.

Initially, Forward Enterprise played a key role in providing accurate information that saved hours of manual effort by eliminating the need to manually synchronize spreadsheets from various inventory tools and internal sub-organisations. While that was certainly valuable, the real cost savings occurred through the rapid insights the platform provided.

The company's IT team wanted to understand everything connected to its network switches in hopes of finding ways to cut costs. Specifically, the team wanted to understand why its network was dependent upon a large number of 100M interfaces, which are considerably more expensive than standardizing on the more common 1G Ethernet standard.

To answer those questions, Forward's Network Query Engine (NQE) was used to create a list of all the devices connected to the network switches by MAC and VLAN. That list was then cross-referenced with the manufacturer to determine what was actually connected to the company's network switches. The results showed that the IT team didn’t need to support the 100M interfaces because the devices connected would support 1G. As such, the network was upgraded to 1G across the board, saving the agency more than $6 million.

The agency stated that without Forward Enterprise, the inventory would never have been done at all, resulting in device failures, support for unnecessary devices, and wasteful expenditures. NQE helps to solve common challenges in network automation when it comes to retrieving network device configuration and state to verify the network posture. Customers with large networks comprised of many different vendors, technologies, and deployments, including on-prem and cloud, find this functionality extremely valuable.

The agency was able to clearly understand its network topology because Forward Enterprise organizes network information like a database, including the number of devices, physical and logical topology, maps of all possible traffic paths, device state, and configuration. Using that data, NQE makes finding information in the network as intuitive and quick as performing a web browser search.

To learn more about how you can use Forward Networks to verify your networks and automate timely processes, schedule a demo today. Be sure to read our other blogs in this series about how Forward Networks is impacting enterprise networks around the world, including Six-Figure Savings: How A Financial Institution Banked On NQE For Massive Returns; From Days To Minutes: Digital Media Provider Uses Forward Networks To Overhaul Reconciliation; and Confidence In Action: Investment Bank Uses Forward Networks To Verify Automation Software.

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