Tuesday, January 4, 2022

g-f(2)785 THE BIG PICTURE OF THE DIGITAL AGE (1/4/2022), MIT SMR, Catching Up Fast by Driving Value From AI




ULTRA-condensed knowledge


"g-f" fishing of golden knowledge (GK) of the fabulous treasure of the digital ageArtificial Intelligence, Catching Up Fast (1/4/2022)  g-f(2)426 


Lessons learned, MIT SMR

EXCEPTIONAL “Full Pack Golden Knowledge Container”


Some organizations may feel that acquiring AI capabilities is a race, and if a company starts late, it can never catch up.


  • That notion is belied by Scotiabank (officially the Bank of Nova Scotia), which has pursued a results-oriented approach to artificial intelligence over the past two years. While some of its resources are devoted to exploring how new technologies — including blockchain and quantum computing — might drive fresh business models and products, the great majority of its data and AI work is focused on improving operations today rather than incubating for the future.


Genioux knowledge fact condensed as an image


References


Catching Up Fast by Driving Value From AIThomas H. Davenport and Randy Bean, December 29, 2021, MIT Sloan Management Review, MIT SMR.


ABOUT THE AUTHORS


Thomas H. Davenport


Thomas H. Davenport (@tdav) is the President’s Distinguished Professor of Information Technology and Management at Babson College, a visiting professor at Oxford University’s Säid School of Business, a fellow of the MIT Initiative on the Digital Economy, and a senior adviser to Deloitte’s AI and Analytics practice. 

Extracted from Wikipedia

Thomas Hayes "Tom" Davenport, Jr. (born October 17, 1954) is an American academic and author specializing in analytics, business process innovation, knowledge management, and artificial intelligence. He is currently the President’s Distinguished Professor in Information Technology and Management at Babson College, a Fellow of the MIT Initiative on the Digital Economy, Co-founder of the International Institute for Analytics, and a Senior Advisor to Deloitte Analytics.

Davenport has written, coauthored, or edited twenty books, including the first books on analytical competition, business process reengineering and achieving value from enterprise systems, and the best seller, Working Knowledge (with Larry Prusak) (Davenport & Prusak 2000), on knowledge management. He has written more than one hundred articles for such publications as Harvard Business Review, MIT Sloan Management Review, California Management Review, the Financial Times, and many other publications. Davenport has also been a columnist for The Wall Street Journal, CIO, InformationWeek, and Forbes magazines.



Randy Bean


Randy Bean (@randybeannvp) is an industry thought leader, author, and CEO of NewVantage Partners, a strategic advisory and management consulting firm that he founded in 2001. He is the author of the new book Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI (Wiley, 2021).



Extra-condensed knowledge



Lessons learned, MIT SMR


  • Scotiabank — one of the Big Five banks based in Canada — has caught up to competitors in some crucial areas. It has done so by more closely integrating its data and analytics work; taking a pragmatic approach to AI; and focusing on reusable data sets, which help with both speed and return on investment.



Condensed knowledge




Lessons learned, MIT SMR


  • First Step: A New Organizational Structure
    • While some of Scotiabank’s competitors made early moves to build or acquire AI capabilities, Scotiabank, by its own admission, got a slow start in comparison. It was involved in a large-scale digital transformation and had some false starts along the way. By mid-2019, Brian Porter, the bank’s CEO, felt it was important to get analytics right.
  • A Highly Pragmatic Approach to AI
    • Back in 2019, Porter and Thomas decided that the primary focus of the bank’s analytics and AI activity should be customers — hence the “customer insights, data, and analytics” label. Thomas, Lee, and their colleagues felt that improving processes and making better decisions within the bank was the best way to catch up to and surpass competitors.
  • ‘RAD-ical’ Changes in Data Provision
    • The data management function at Scotiabank, headed by Peter Serenita as chief data officer, also made changes. The goal was to more rapidly provide data for analytics and AI use cases — and without the data, the models wouldn’t be possible. Before the 2019 CID&A restructuring, the bank’s data strategy had been primarily focused on defense — a “protect the bank” approach that emphasized regulatory compliance, financial reporting, and risk management.



Some relevant characteristics of this "genioux fact"

  • Category 2: The Big Picture of the Digital Age
  • [genioux fact deduced or extracted from MIT SMR]
  • This is a “genioux fact fast solution.”
  • Tag Opportunities those travelling at high speed on GKPath
  • Type of essential knowledge of this “genioux fact”: Essential Analyzed Knowledge (EAK).
  • Type of validity of the "genioux fact". 

    • Inherited from sources + Supported by the knowledge of one or more experts.


References


“genioux facts”: The online programme on MASTERING “THE BIG PICTURE OF THE DIGITAL AGE”, g-f(2)785, Fernando Machuca, January 4, 2022, blog.geniouxfacts.comgeniouxfacts.comGenioux.com Corporation.


ABOUT THE AUTHORS


PhD with awarded honors in computer science in France

Fernando is the director of "genioux facts". He is the entrepreneur, researcher and professor who has a disruptive proposal in The Digital Age to improve the world and reduce poverty + ignorance + violence. A critical piece of the solution puzzle is "genioux facts"The Innovation Value of "genioux facts" is exceptional for individuals, companies and any kind of organization.



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