g-f(2)117 THE BIG PICTURE OF THE DIGITAL AGE, MIT SMR, The Transformational Power of Recommendation.

Extra-condensed knowledge

• Recommendation engines are revolutionizing how customers buy and employees work.
• In data-driven markets, the most effective competitors reliably offer the most effective advice. When predictive analytics are repackaged and repurposed as recommendations, they transform how people perceive, experience, and exercise choice. The most powerful — and empowering — engines of commerce are recommendation engines.
• Superior recommendations measurably build superior loyalty and growth; they amplify customer lifetime value. Computing compelling recommendations profitably reshapes human behavior.
• Google, have adopted and adapted recommendation engines as internal productivity platforms to nudge workers to their best decision options.

Genioux knowledge fact condensed as an image

Condensed knowledge  

• Helping Customers Make Better Choices Drives Business Growth.
• People who want to make better choices are increasingly willing to accept recommendations from smart machines.
• Discover Weekly is the company’s premier recommender system — and an incisive case study in how rethinking and combining recommendation algorithms profoundly changes people’s paths to novelty.
• Every Monday, Spotify customers receive a customized mixtape of 30 songs they’ve likely never heard before but are probabilistically likely to love. 
• Companies like Spotify are betting that helping customers make better choices — that is, making them smarter — will make them more loyal and profitable. 
• Netflix observes that 75% of what people watch on the service comes from their personalized product recommendations.
• The recommendations people follow — and ignore — also reveal a great deal about who they are. 
• Better Employee Choices Boost Performance.
• Recommenders promote greater personal — as well as enterprise — productivity. For instance, marketers and salespeople worldwide use recommenders to plot campaigns and target prospects. 
• With relentlessly ongoing innovation in machine learning, artificial intelligence, sensors, augmented reality, neural technologies, and other digital media, recommendation’s reach becomes more pervasive, powerful, and important.
• Recommendation engines have been essential to the success of digital platforms Alibaba, Amazon, Netflix, and Spotify, according to their founders and CEOs. For companies such as these, recommendation engines aren’t merely marketing or sales tools but drivers of insight, innovation, and engagement.
• The recommendation future promises to be not just more personal, relevant, and better informed but transformative in ways guaranteed to (persuasively) surprise.    A strategy and technology that learns to reliably deliver serendipity has long-term prospects.

Category 2: The Big Picture of the Digital Age

[genioux fact produced, deduced or extracted from MIT SMR]

Type of essential knowledge of this “genioux fact”: Essential Deduced and Extracted Knowledge (EDEK).

Type of validity of the "genioux fact". 

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

Authors of the genioux fact

Fernando Machuca

References

The Transformational Power of Recommendation, Michael Schrage, November 24, 2020, MIT Sloan Management Review, MIT SMR.

ABOUT THE AUTHORS

Michael Schrage is a research fellow at the MIT Sloan School of Management’s Initiative on the Digital Economy. He is the author of Recommendation Engines (MIT Press, 2020), from which this article is adapted.

Michael Schrage is a Visiting Fellow in the Imperial College Department of Innovation and Entrepreneurship where he examines the various roles of models, prototypes, and simulations as collaborative media for innovation risk management.