Behind the scenes with Verizon: Network reliability during the pandemic
Download HEAVY.AI Free, a full-featured version available for use at no cost.GET FREE LICENSE
NOTE: OMNISCI IS NOW HEAVY.AI
The proactive response from the telecommunications industry worldwide has ensured that friends, family and professionals around the world remain connected and entertained in the face of the Covid-19 health pandemic. On January 7, TM Forum’s Chief Analyst Mark Newman led a webinar in which participants from Verizon and OmniSci reviewed what Verizon has been doing behind the scenes before and during the pandemic to keep its networks up and running and to respond to significant, unexpected changes in traffic flows and volumes.
There were a number of important changes in traffic flows during March and April 2020 when Covid-19 arrived in the United States and people moved into lockdown, according to Verizon.
- Upward trends in collaboration tool usage and VPN usage.
- A notable increase in call volume, and then a sustained increase in minutes of use driven likely in part by increased work from home conference calls and meetings that would have traditionally been in person.
- Increases in gaming traffic and video traffic with stay-at-home orders alongside “a shift in entertainment consumption to at home options.” (see table below).
Adjusted retail patterns
Changes in consumer behavior are highly palpable in the retail industry. Verizon noted that looking at 20 of the top 25 National Retail Federation retailers, these retailers’ website traffic on Thanksgiving Day was up 560% from the previous year, while Black Friday to Cyber Monday saw an increase in 200% in online traffic from the previous year. Video conferencing services on Thanksgiving Day also increased 31 times compared to previous year with more people communicating with their family, relatives and friends virtually.
Verizon added: “People were more cautious when traveling out of their homes and as a result, a lot of Thanksgiving transactions occurred online…that definitely impacted the mobility patterns around stores.”
On the move, or not
Through a partnership with OmniSci, an accelerated analytics platform, Verizon was able to track changes in traffic flows across its mobile networks in near real time. This enabled Verizon to identify pain points in the networks and to allocate investments and resources to improve network capacity. Verizon was also able to predict where future problems may occur. “We use this dataset to forecast when we think mobility will go back to normal and when we think certain areas will experience more usage again” explained by Verizon.
Verizon was also able to concisely map mobility patterns across the US, aligning behaviors to the various lockdowns and predicting future traffic so as to be able to adjust accordingly (see the video below).
A good example of where Verizon was able to boost its network capacity was the Providence St. Vincent Medical Centre in Oregon. “Throughout the country there have unfortunately been a lot of hospitalizations, so we wanted to ensure that there was additional capacity in places like hospitals to meet expected demand,” Verizon said.
Built for robustness
Verizon referenced the robustness of the Verizon network which was able to manage the surges and changes in traffic flows. Verizon was also able to take advantage of the additional capacity allocated by the FCC to help operators manage traffic during the pandemic.
Verizon also followed developments in other countries and how operators responded to the pandemic and lockdown.
“As we learned more from the telco providers in other countries, it enabled us to be more successful in addressing and anticipating the demands that were coming from our customers during different phases of the pandemic.”
Learn more about how Verizon’s consistent investment and continuous deployments of the latest technology led to strong performance when customers needed it most. Watch the webinar for the full insight here
- OmniSci Telecom Industry Use Cases
- Solution Brief: Accelerated Analytics and Data Science for the Telecom Industry