1 / 13

Cable MSO Update: RiskView® Cost-Savings Case Study

Cable MSO Update: RiskView® Cost-Savings Case Study. Outage Risk Analytics. Robert Cruickshank CEO & CTO robert.cruickshank@rev2.com (703) 568-8379. RiskView Cost Savings. Correlation and Risk Concentration Analysis™ enables RV to find issues that are otherwise hidden.

finna
Download Presentation

Cable MSO Update: RiskView® Cost-Savings Case Study

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Cable MSO Update: RiskView® Cost-Savings Case Study Outage Risk Analytics Robert Cruickshank CEO & CTO robert.cruickshank@rev2.com (703) 568-8379

  2. RiskView Cost Savings • Correlation and Risk Concentration Analysis™ enables RV to find issues that are otherwise hidden. • Characteristics of a hidden issue include: • Small and intermittent • Below real-time thresholds • Not detected right away • Add up in cost over time • Get worse and become larger • Some issues - even after fixes - remain problematic & costly • Key Outcomes: • Cost-savings analysis reveals “death by a thousand paper cuts” • Proactively identifying issues saves money on calls and maintenance • The longer an issue persists, the more voluntary disconnects result • A key attribute of RV is its ability to identify incidents that lead to voluntary disconnects Hidden issues often last for days, resulting in a snowballing effect of voluntary disconnects. Confidential 2

  3. RiskView Architecture Confidential 3

  4. RiskView® 90-Day Cost-Savings Case Study

  5. MSO Case Study Parameters of Blind Comparison Study by Maintenance Department • 1,000,000 subs in Region | 35,000 HFC miles | 180 technicians | 15 supervisors | 4 managers | 1 director • 7,500 nodes in 3,000 DOCSIS Serving Groups (combinations of nodes) Hypothesis • [operating cost without Automation – operating cost with Automation] = Quantifiable Savings Study Groups • Control Group = Business as Usual (BAU) • Test Group =RiskView (RV) Outage Risk Analytics Goals • Minimize downtime of the “operating assets”  To enhance customer satisfactionwhile lowering care and support costs • Monitor maintenance activity for its effectiveness  Earlier detection helps in solving chronic problems thereby reducing disconnects Departments Impacted by Control Group Discovered Issues • Service Department focuses on Non-Area Issues • Maintenance Department focuses on Area issues Confidential 5

  6. Systematically Correlate Multiple Inputs Over Time • Call Center • Connectivity Calls & Repeats • Field Service e.g., ARRIS WorkAssure • TC = Service Calls & Repeats • EC = Refer to Maintenance • DI = Voluntary Disconnects • Biz/Residential, 1/2/3 Services • Maintenance Activity • Planned, Demand • Telemetry e.g., ARRIS SAA • Hourly Degraded CMs • US/DS Errors/SNR/Power/Util • On/Offline, Node Combining Confidential 6

  7. Transaction Analytics • Problem Period: Any event which had a Reputational Cost of more than 15 transactions on a given day and stayed above 10 transactions for two days. • Reputational Cost: A dimensionless number that quantifies the potential effects on the reputation of the MSO among customers owing to the persistent problems in the network. It is represented by the following formula: Call + 2*TC + RepTC + 3*EC + 2*DI + CHG + TRB + Fluctuating Levels + DnErr + UpErr • 90-day Summary: • Total problem periods identified by RV: 4,208 • 38% of these problem periods had BAU activity • RV identified 6% of problem periods before BAU did Confidential 7

  8. Problem Period Example with Savings Model assumption: Early detection by RiskView saves 50% of the eventual cost. Confidential 8

  9. A Serving Group with 8 Problem Periods Problem period Finding: Reputational cost of 15 is a reliable early warning indicator. Confidential 9

  10. Accumulation of Problem Periods – 90 days Total Problem Periods: 4,108 15% of Problem Periods last 4 days or longer. Confidential 10

  11. Disconnects – 90 Days Total Disconnects: 68,834 Total Problem Periods: 4,208 • The average number of voluntary disconnects steadily rise with the rise in the duration of problem period. • With early detection, an operator can save onvoluntary disconnects by fixing the problems in time. Confidential 11

  12. Transactional Savings Impact on P&L (Proforma) • Maintenance Department: Additional Work 16K Preventative Maintenance Actions Created -4K Saved EC Tasks/year = 12K Net New Preventative Maintenance Actions/year $1.2M Cost due to additional Tasks @ $100 each • Service Department: Reduce Contractor Head Count • Approx. 50% of Installs performed by Contractors @ $60.00 • As TCs are reduced, Staff do “would be contracted” installs $900K Saved 15K TCs/year @ $60 $360K Saved 6K Disconnects/year @ $60 • Call Center: Reduce Capacity with normal attrition $320K Saved 40K Calls/year @ $8 • Savings: $380K net per year for 1m subscribers

  13. Thank you!

More Related