Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

FuturePMO 2017 - Rhys Lancaster, Tata Communications: “PMO 2030” – Robotic Process Automation, Machine Learning & Analytics

192 views

Published on

Rhys Lancaster is Global Head of Project Management at Tata Communications. In his presentation, he shows how he is planning to apply Robotic Process Automation (RPA), Machine Learning and Analytics to create the ‘Future PMO’ at Tata Communications. His workshop asked the audience on how automation may impact our PMOs and wider organisations in future.

Perhaps together we can answer the question ‘With the pace of automation, how can we all remain relevant in future?’. Or maybe we will just speculate on whether flying DeLoreans will exist in 2030 (having been predicted in 2015).

Published in: Business
  • Be the first to comment

  • Be the first to like this

FuturePMO 2017 - Rhys Lancaster, Tata Communications: “PMO 2030” – Robotic Process Automation, Machine Learning & Analytics

  1. 1. THE FUTURE OF WORK? RHYS LANCASTER GLOBAL HEAD OF PROJECT MANAGEMENT PMO 2030
  2. 2. INTRODUCTION 2
  3. 3. $108.78 billion ~68% outside India Europe largest market Over 140 Years in Operation Only Indian entity on Forbes’ List of World’s 20 Most Reputed Companies CSR focused 67% of shares are owned by a family trust 610,000 Employees Worldwide Over 100 Operating Companies in 7 Sectors across 6 Continents TATA GROUP
  4. 4. 1 Million Square feet of data center and co-location across 44 locations International wholesale voice minutes per year 70 Billion Service provider relationships 1,600 Of all international voice calls delivered by us 1 in 5 Of world’s roaming traffic is facilitated by us 50% International wholesale voice and mobile roaming Tb/s of bandwidth connected20 Billion invested in network and assets12 Submarine cable owner #1 International voice carrier #1 Mobile roaming and signaling provider#1 Petabytes delivered each month 9,400 192 Countries connected Offices in 31 countries. 71% revenues generated outside of India Cloud hubs, with over 40 interconnections 16 Network reaching 99.7% of the world’s GDP 710,000 km of subsea and terrestrial fibre: world’s only global fibre ring Accelerating growth to and within emerging markets Carrying 24% of world’s Internet routes World’s highest capacity network
  5. 5. GLOBAL HEAD OF PROJECT MANAGEMENT • 20 years in the IT & Telecommunications Industry • 7 years at Tata Communications, building a global PMO function, evangelising the practice, creating PS capability • Currently driving organizational change to automate processes & systems, and building a team of experts to guide customers on their digitalization journey SPEAKER
  6. 6. ROBOTIC PROCESS AUTOMATION MACHINE LEARNING & ANALYTICS 6 PMO 2030
  7. 7. WHY WE ARE ON THE CUSP OF A REVOLUTION THE POWER OF EXPONENTIAL CURVES • Humans are not wired to understand “Exponential” • Nothing happens for a long time. Then everything happens.
  8. 8. SAE Autonomy levels 1880s – Level 0 - No Driving Automation 1970s – Level 1 Driver Assistance 1990s – Level 2 Partial Driving Automation 2000s – Level 3 Conditional Driving Automation 2010 – Level 4 High Driving Automation 2015 – Level 5 Full Driving Automation 2021 – Ford’s target for Mass Market Level 5 EXPONENTIAL GROWTH - AUTONOMOUS CARS 8
  9. 9. • “Forced Labour” in Czech. A machine capable of carrying out a series of actions, programmable by a computer • Manufacturing – production line • Not fully automated, humans are still required where there is any variable ROBOTICS 9
  10. 10. WHAT IS IT? Repetitive (computer based) tasks that previously required a human to perform “Microsoft Macro” rebooted. Without the limitations or need to program Operates at the User Interface. More like “training” a human ROBOTIC PROCESS AUTOMATION 10
  11. 11. No need for costly IT integration No need for programming Already faster, more accurate than a human RPA ADVANTAGES 11
  12. 12. Learning to cope with variables, prefers structured data Currently limited decision making capability Cost vs Labour RPA will scale then convergence with other technologies such as Machine Learning and Analytics to address this RPA CURRENT CHALLENGES 12
  13. 13. GLOBAL PMO TRANSFORMATION Vendor handover via email to system entry e.g. SAP, CMDB Data Quality Vendor Access Handover Various email inputs to system updates Reduction in Error Rates Project Coordinator Automation Order creation in multiple systems from email inputs Reduction in Error Rates, Data Quality, System Integration Order Entry ROBOTIC PROCESS AUTOMATION PROJECTS 13
  14. 14. PMO 2017 TO PMO 2030 14 Governance Documenting Decisions & Tracking Action Items Management Information Reporting Quality Management Administration tasks within QM function Automation of Project Quality reports Able to assess quality of documents Risk & Issue Management Understanding situations and risks through machine learning and data analytics Resource Management Forecasting workload based not just on past patterns, but future predictions Decision Making Able to make “better than human” decisions based on analysis of huge data sets Project Management? Understanding scope, context and relationships Able to handle complex human conversations and nuances Completely replace the Project Manager? Project Performance Management Status Reports – various data sources Schedule Management Facilitate & automate system updates Supplier Management Automation of Supplier scorecards Billing & Invoicing – e.g. SAP administration Financial Management Tracking spend across various systems, collating to PMO tools
  15. 15. THANK YOU 15

×