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Mission: Possible! Your cognitive future in government


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Welcome to the age of cognitive computing, where intelligent machines simulate human brain capabilities to help solve society’s most vexing problems. Early adopters in government and other industries are already realizing significant value from this innovative technology, and its potential to transform government is enormous. Currently, cognitive systems are helping government organizations navigate complexity in operational environments and foster improved engagement with constituents. Our research indicates that government leaders are poised to embrace this groundbreaking technology and invest in cognitive capabilities to improve outcomes for government organizations across mission areas.

Published in: Government & Nonprofit
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Mission: Possible! Your cognitive future in government

  1. 1. ©2015 IBM Corporation1 Your cognitive future in government Mission: Possible!
  2. 2. ©2015 IBM Corporation2 Three disruptive forces are forcing government industry to focus on three key areas … Increased demand for services and citizen expectations Placing greater pressures and demands on and expectations for public resources and services requiring organizations to operate smarter and more efficiently Increased complexity Challenging decision making capabilities in navigating complex operating and information environments and increasing the need for enhanced innovation capacity to drive operational improvements Stagnant economic growth and resource constraints Challenging organizations to do more with less and requiring them to better leverage existing resources and expertise while reducing instances of fraud and error Provide expert assistance and extend capabilities of human experts by leveraging deep insights from vast amounts of information Engage DecideDiscover Provide ability to digest vast amounts of data to identify new avenues, navigate complexity, and implement new ideas Provide personalized, contextual, evidence-backed recommendations to support decision making at all levels
  3. 3. ©2015 IBM Corporation3 Successful organizations have stronger capabilities in engagement, discovery and decision making Engage DecideDiscover Outperformers are 43% more competent in consumer engagement than underperformers 44% more outperformers are strong in decision making 48% Outperformers 18% Underperformers 167% more outperformers make innovation a major priority 60% Outperformers 42% Underperformers 62% Outperformers 43% Underperformers 43% 167% 44% Source: IBM Institute for Business Value Cognitive Computing Survey , 2015.
  4. 4. ©2015 IBM Corporation4 Government organizations need to engage with citizens, discover insights and make effective decisions to succeed Sources: See notes . Government CXOs actively pursuing industry model innovation1 Government CXOs that believe citizens demand more personalized experiences1 Engage DecideDiscover Today In 3 years 54% 59% 54% Annual spend of U.S. Federal Government3 … … amount allocated based on basic evidence2 $3 trillion <1%
  5. 5. ©2015 IBM Corporation5 They are faced with few key challenges pertaining to personalized experience, insufficient skills and lack of effective decision making Government organizations are weak in making cost reduction decisions Government CXOs that believe they’re not competent in providing personalized citizen experience Key challenges of Government CXO in pursuing disruptive innovation Engage DecideDiscover 58% 53% 54% 55% 58% Insufficient skills Lack of quality/ reliable data Lack of analytical tools Organizational complacency 67% Source: IBM Institute for Business Value Cognitive Computing Survey , 2015.
  6. 6. ©2015 IBM Corporation6 Data is growing fast – in volume, variety, and complexity – and traditional analytics solutions are not able to fully exploit its value Data is growing with time, but usability is limited.. ... because of the limits of traditional analytics Amount of world’s data being analyzed 1 .5%  Addresses predefined problems but cannot adopt to new problem domain  Provides accurate and definitive answers but cannot handle ambiguity or gray areas  Handles structured and unstructured information with known semantics – thus cannot make use of data from new and varied sources  Interacts in formal digital means (e.g., commands, screens) with human – thus limits the engagement of end user 2.63 PB Projected volume of data stored on average by in US Federal agencies in 20152,3 Sources: See notes .
  7. 7. ©2015 IBM Corporation7 … that can be bridged using a mechanism for overcoming the limitations of humans and current systems Organizations need a tireless machine that can learn new problem domain, reason through the hypotheses, resolve ambiguity, evolve towards more accuracy, and interact in natural means to pursue three opportunities Human Machine  Human brain can consume and process only limited amount of information  Human beings are subject to physical and mental fatigue – thus not scalable  Human workers and experts can make mistakes  Traditional technology cannot handle ambiguity  Traditional paradigm of computing is pre-programmed and rigid; it cannot learn, reason, or relate  Machines do not interact in natural means
  8. 8. ©2015 IBM Corporation8 Cognitive computing with its three capabilities can be that new vehicle that opens the door to new opportunities Engage DecideDiscover  Acts as a tireless agent providing expert assistance to human users  Carries a conversation naturally, e.g. in human language  Understands consumers from past history and enriches interactions with context- and evidence- based reasoning  Helps people discover insights far above human levels  Finds insights and connections, understands the vast amounts of information available  Visualizes possibilities and validates theories like experts  Offers evidence-based recommendations  Evolves continually towards more accuracy based on new information, outcomes, and actions  Provides traceability to audit why a particular decision is made
  9. 9. ©2015 IBM Corporation9 Cognitive computing complements traditional analytics by creating a value continuum Analytics Cognitive computing  Addresses predefined problems  Addresses ambiguous problems  Provides accurate and definitive answers  Provides answers with a margin of error  Handles structured and unstructured information with known semantics  Handles unstructured information without explicitly knowing semantics  Interacts in formal digital means (e.g. commands, screens) with human users  Interacts in natural language with human users
  10. 10. ©2015 IBM Corporation10 20% 53% 27% 1-2 yrs 3-4 yrs >=5 yrs Government executives believe cognitive computing will play a disruptive role in the industry and plan to invest in this capability soon … of executives familiar with cognitive computing believe it will be critical for their business in future … of executives familiar with cognitive computing also believe it will play a disruptive role in governments 100% of executives familiar with cognitive computing indicated they are likely to invest in this technology in the future with the majority doing so in the next 4 years 83% 87% Source: IBM Institute for Business Value Cognitive Computing Survey , 2015.
  11. 11. ©2015 IBM Corporation11 Cognitive is helping public organizations to provide better service, discover insights and make effective decisions Deakin University’s online student engagement advisor is reimagining the way of engaging with students, and providing them improved service1 Baylor College of Medicine is applying cognitive computing to accelerate research and make discoveries with greater precision2 MD Anderson Cancer Center leverages cognitive features to help oncologists develop more personalized care for their patients3 Engage DecideDiscover Sources: See notes .
  12. 12. ©2015 IBM Corporation12 Organizations should follow a structured road map that nurtures optimism whilst break any complacency in their organization 1 2 3 4 Chart the course  Identify candidate opportunities across mission & functional areas  Define business benefits case  Develop organization’s cognitive computing journey/road map Experiment  Prototype use cases  Test and validate use case scenarios with users  Test business case hypotheses Develop & Train  Develop & train the system  Build & improve required corpus  Train & educate solution end users & the organization Deploy, Explore & Evolve  Deploy baseline solution  Continuous learning & corpus improvement  Further use case exploration
  13. 13. ©2015 IBM Corporation13 18 November 2015 Study approach and methodology Quantitative Insights  Survey conducted by The Economist Intelligence Unit with 813 respondents  Survey conducted in February and March of 2015  Industry cover: Healthcare, Banking, Insurance, Retail, Government, Telco, Life Sciences, Consumer Products, and Oil and Gas  Geographical cover : Australia, Brazil, Canada, China, Egypt, France, Germany, India, Iran, Israel, Japan, Kuwait, Mexico, Netherlands, Oman, Qatar, Saudi Arabia, Singapore, South Africa, Spain, Sweden, UK, United Arab Emirates, and US Field Research  Interviews with subject matter experts across IBM divisions  Supplemental desk research
  14. 14. ©2015 IBM Corporation14 18 November 2015 Dr. Cameron Brooks Director, Watson Public Sector Solutions IBM Watson Group Study authors Dr. Sandipan Sarkar Cognitive Computing Leader IBM Institute for Business Value Dave Zaharchuk Global Government Industry Leader IBM Institute for Business Value Patricia Martone Carrolo Director, Public Sector IBM Watson Group