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ROI Analysis of WiFi Offloading PowerPoint Presentation

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On : Nov 13, 2014

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  • Slide 1 - ROI Analysis of WiFi Offloading
  • Slide 2 - To offload or not to offload… Operators of mobile cellular data networks (3G and 4G) face an uphill battle against increasing data usage and declining ARPUs ROI on macro network expansions scrutinized by shareholders iPhones, iPads, Android smartphones, netbooks are all tapping the mobile network for access anywhere, anytime Majority of access occurs when the user is stationary in high traffic density areas (home, office, coffee shop etc.) 2 …the bad news is…
  • Slide 3 - 3 Comscore found that more than one third (37.2 percent) of U.S. digital traffic coming from mobile phones occurred via a WiFi connection. by Karl Bode Thursday 27- Oct 2011 Phil Marshall head of Tolaga Research. estimates that about 20 percent of iPhone traffic on AT&T Mobility's network is landing on the public WiFi network, and it's likely that another 60 percent is landing on home WiFi networks now that the operator has instituted tiered data plans, he said. “When you have WiFi, you do more, and that effect is pretty hard to measure," Steve Glapa, Rukus. "But nonetheless, I would say network traffic on PCCW's network would be 20 percent higher than if it didn't have WiFi. In some of the dense traffic areas of Hong Kong, some 80 percent of data traffic is traveling over WiFi”, he said …the good news is WiFi offload already occurs naturally…
  • Slide 4 - 65% of mobile data traffic already offloaded Users are in Wi-Fi coverage 63 percent of the time during the day/ 65 percent of traffic can be offloaded to Wi-Fi under typical usage conditions using on-the-spot offload Greater offload performance can be achieved if the user is prepared to accept delayed offload (e.g., sync your videos or photos when you get home) This means that out of the 7GB usage per month, 4.5GB would travel by Wi-Fi and 2.5GB by cellular. Therefore a 2GB-3GB per month cellular data plan is probably enough for most users. 4 …a fair assumption according to Light Reading would be… Observation: A cellular service provider already benefits from WiFi Offload without making any investment in deploying a WiFi Network of its own.
  • Slide 5 - How do we quantify the offload dilemma? How do we analyze the impact of a 3G/4G Service Provider’s Own WiFi Offload Deployment on its overall Business Case? Does it make economic sense to deploy a WiFi Offload Network? What is the Business Case for MNO WiFi Offload? What is the ROI of an MNO WiFi Offload? 5 Answer: Develop a WiROI™ Model to answer these questions …in-depth analysis required to make informed decision…
  • Slide 6 - Using a holistic approach Study the Impact of WiFi Offload on an Urban LTE Deployment Deploy an LTE network for Coverage Deploy a WiFi Network for Capacity Surgically place the WiFi AP’s in high traffic areas Calculate the TCO (CapEx and OpEx) for the WiFi Offload Network Compare to the TCO of providing Capacity by deploying LTE Cells for Capacity Understand the key deployment parameters which lead to positive economic impact of WiFi off load Calculate and Compare ROI metrics such as NPV, IRR 6 …the wireless 20|20 process…
  • Slide 7 - Real time simulation and analysis Allow the simulation of public wifi offload to vary the % of the natural offload Allow the simulation model to vary the % of the Urban Area covered by WiFi Allow the simulation model to vary the Density of WiFi AP’s per sq km Vary WiFi Vendor Equipment Performance and Price (Cell Radius of AP’s, cost of AP’s) Vary the WiFi Backhaul Cost Vary the operating cost of the WiFi network Vary the total data capacity a user consumes on a monthly basis 7 …WiROI™ capabilities… Objective: Discover under what conditions WiFi Offload pays off
  • Slide 8 - Major Assumptions One Time Costs (CapEx) Cost of WiFi Access Point Cost of WiFi AP installation Cost of Backhaul Equipment Cost of Backhaul Equipment Installation and provisioning WiFi Core Network Equipment (Servers, Portals, etc.) Recurring Costs (OpEx) Monthly WiFi and Backhaul Site Rental Monthly WiFi and Backhaul Maintenance Monthly Traffic Backhaul Cost 8 …CAPEX and OPEX drivers… Objective: Discover under what conditions WiFi Offload pays off
  • Slide 9 - Cover Areas of High Traffic Density 9 …customized analysis of traffic density…
  • Slide 10 - More AP’s per Sq Km provide better offload 10 …and WiFi AP Density…
  • Slide 11 - Coverage vs. Traffic Offload 11 Hotspot coverage of high traffic density areas versus contiguous coverage yields better offload percentage Customized formulas for different market conditions …coverage vs. traffic offload… Coverage
  • Slide 12 - WiROI™ Research Analysis Case Study 1 – LTE Deployment on New York City 12
  • Slide 13 - Baseline: New York City 13 Assumption: LTE deployment in NYC Activity: Simulate TCO impact of implementing MNO WiFi Offload Network Identify: The scenario for optimal financial return Analyze: Understand main drivers of the results …large dense urban city…
  • Slide 14 - Assumptions: CapEx & OpEx 14 …WiFi vs. LTE assumptions…
  • Slide 15 - Analysis: TCO impact of WiFi Offload 15 TCO savings of about $123m already with only 20% coverage and density of 24 AP’s per sq km. Optimal TCO savings of $253m is achieved with 100% coverage and 42 AP’s per sq km. The number of macro LTE capacity sites reduced by 1,447 and replaced by 33,138 WiFi access points. …WiFi offload results… TCO Savings $123m TCO Savings $253m Observation: Optimal Financial Return might not be Optimal Commercial Proposition Optimal Commercial Proposition?
  • Slide 16 - Analysis: Optimal TCO Results 16 …New York results…
  • Slide 17 - WiROI™ Research Analysis Case Study 2 – LTE Deployment in San Diego, USA 17
  • Slide 18 - Baseline: San Diego 18 Assumption: LTE deployment in San Diego Activity: Simulate TCO impact of implementing MNO WiFi Offload Network Identify: The scenario for optimal financial return Analyze: Understand main drivers of the results …midsize urban city…
  • Slide 19 - Analysis: TCO impact of WiFi Offload 19 TCO savings of about $10m already with only 20% coverage and density of 24 AP’s per sq km. Optimal TCO savings of $16m is achieved with 40% coverage coverage and 24 AP’s per sq km. At 40% the number of macro LTE capacity sites reduced by 100 and replaced by 2,400 WiFi access points. …WiFi offload results… TCO Savings $10m TCO Savings $16m Observation: Beyond 80% coverage you start to see diminishing returns
  • Slide 20 - Analysis: Optimal TCO Results 20 …San Diego results…
  • Slide 21 - Conclusions & Recommendations In New York, a dense urban environment with high traffic profile, MNO WiFi Offload is optimal at 100% coverage In San Diego, a urban environment, with high traffic profile, MNO offload is optimal at 40% with diminishing return beyond 80% MNO WiFi offload makes an compelling business case under the right circumstances Main driver is OpEx, especially the WiFi site rental and backhaul costs as well as the assumed growth of the traffic demand on the 3G/4G network. OpEx less than $40 per month a highly attractive solution OpEx exceed $100-$150 per month, it becomes challenging 21 Recommendation: Create a customized WiROI™ Tool for your market to drive informed decisions. Contact us at www.wireless2020.com …large vs. midsize city deployment…
  • Slide 22 - WiROI™ Tool Demo 22 Test drive the WiROI™ Tool by register online at www.wireless2020.com to gain access to our online demo or contact us for a WebEx Demo. USA - Western Region Randall C. Schwartz +1-650-490-3090 info@wireless2020.com Armenia Office Levon Mkrtchyan +374 91 421-266 info@wireless2020.com Spain Office Azat Sakanyan +1-408-884-1561 info@wireless2020.com Tonse Telecom #446, 2nd Cross, 9th Main, HAL 2nd Stage Bangalore India 560 038 Phone: +91 80 4211 5355 USA - Eastern Region Haig A. Sarkissian +1-408-884-1561 info@wireless2020.com Peru Office Magnus Johansson +51 988 352 info@wireless2020.com Media Relations Robin L. Bestel +1-610-861-5956 robin@wireless2020.com …test drive our WiROI™ 4G WiFi Offloading Tool online…

Description : Title: ROI Analysis of WiFi Offloading Author: Haig Sarkissian Last modified by: robin Created Date: 11/22/2010 4:28:51 PM Document presentation format

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