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RC TOM Challenge 2018

November 13, 2018

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The TOM Challenge provides an opportunity for you to continue exploring organizational learning and innovation through the lens of process improvement and/or product development, the focus of RC TOM’s second module. In this challenge, you will investigate how an organization is grappling with machine learning, additive manufacturing, or open innovation. These megatrends are likely to significantly affect how organizations manage process improvement and product development in the coming years of your career. The TOM Challenge requires you to (1) conduct research and write an essay that examines how one organization is facing a particular aspect of one of these megatrends, and (2) write six comments that share your reflections on some of your section mates’ essays.

Your essay should address four questions in the context of the organization you choose:

  1. Why do you think the megatrend you selected is important to your organization’s management of process improvement and/or product development?
  2. What is the organization’s management doing to address this issue in the short term (the next two years) and the medium term (two to ten years out)?
  3. What other steps do you recommend the organization’s management take to address this issue in the short and medium terms?
  4. In the context of this organization, what are one or two important open questions related to this issue that you are unsure about that merit comments from your classmates?

Your essay should convey facts, analysis, and your recommendations. It should focus on a single organization (e.g., a single company, non-profit organization, or government agency) and a concern related to one megatrend. It is fine if the concern you choose relates to other megatrends that the organization is facing, but that’s not required. Roughly a third of your essay should be dedicated to each of the first three questions, with just a few sentences dedicated to the fourth question. Your essay should be at least 700 words but no more than 800 words, and must conclude with a word count in parentheses (such as 778 words).

When posting your essay to Open Knowledge, be sure to enter “Machine Learning”, “Additive Manufacturing”, or “Isolationism” in the Topics field.

More details on research, sourcing, deadlines, and other matters are provided in the RC TOM Challenge: 2018 note.  For assistance with the Open Knowledge platform during business hours (9:00 am – 5:00 pm M-F), email openknowledge@hbs.edu. A short video with instructions on how to post an essay to this platform is available at https://aiinstitute.hbs.edu/platform-rctom/how-to/.

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Submitted (926)

A Better Brain: Machine Learning in Guided Meditation
Keagan Pang
Posted on November 12, 2018 at 8:34 pm
Meditation, with its many mental benefits, has remained an elusive skill to master. While there has been a surge in the number of guided meditation mobile apps available, none offer any real insight to the most common question that beginner [...]
Ushering authentic advertising – Can machines help marketers understand their audience better for the benefit of all?
Luis Valles
Last modified on November 13, 2018 at 8:07 pm
Influential.co is a platform using machine learning to improve the development and deployment of marketing campaigns with influencers on social media.
Data is the new oil: Rio Tinto builds new intelligent mine
Gavriel Goidel
Last modified on November 12, 2018 at 10:18 pm
An executive "innovation field trip" to America, marked the beginning of a new era for Rio Tinto. That happened merely a decade ago, and now as data turns the new oil, the company must follow its innovative approach and evolve.
Open Innovation at Lego – The Back Beat in “Everything is Awesome”
Jaclyn Markowitz
Posted on November 13, 2018 at 7:33 am
After avoiding bankruptcy in 2003, LEGO has effectively used open innovation to align with customer demands and to become a global leader in toy innovation. Now, can LEGO’s use of open innovation maintain its growth with increasing digital competition?
Anadarko: Big Oil Meets Big Data
Michael Volpert
Posted on November 13, 2018 at 5:42 pm
The oil and gas industry is undergoing a digital transformation.
Flotek – Drilling Into The Fracking Data With Machine Learning?
John S.
Posted on November 13, 2018 at 4:40 pm
The management team of Flotek is facing pressure from public market short-sellers and using fracking data to build a new machine learning tool that helps differentiate its specialty chemicals product in the marketplace.
Breaking the Molds: 3D-Printing and The Future of Shoemaking
James Eckfeldt
Posted on November 12, 2018 at 8:16 pm
“Imagine walking into a store, running briefly on a treadmill and instantly getting a 3D-printed running shoe”. This is the ambitious goal that Adidas has set itself for the future. What role will additive manufacturing play in making it possible?
Nvidia: Datacenter Dominance
Everett Frost
Last modified on November 13, 2018 at 6:26 pm
Nvidia seeks to extend its lead in the datacenter space with advanced machine learning capabilities.
Grammar(ly): Who sets the rules?
Ben
Posted on November 13, 2018 at 11:58 pm
Over the past decade, Grammarly has accumulated 7M daily users of its grammatical suggestion engine [1]. Now Grammarly hopes to go beyond grammar in its mission of improving communication. How they do that depends on us.
IoT and Me: Nest, Machine Learning, and the Smart Device Revolution
Greatest of All TOM
Posted on November 13, 2018 at 12:52 am
Nest, a market leader in the smart devices space, employs machine learning and big data to cater to its customers, push its products forward, and explore new areas of innovation.
Teladoc about Machine Learning
TOM_HBS2020
Posted on November 13, 2018 at 7:06 pm
Telehealth has recently emerged as a convenient alternative to the traditional in-person health care appointment. Teladoc, the oldest and largest telehealth company, provides 24/7 access to physicians worldwide via audio or video consultations. Patients use the Teladoc website or mobile [...]
Machine Learning to Revolutionize Military Training
Scipio
Posted on November 12, 2018 at 6:43 pm
Normally sluggish to adapt, the military is taking swift action to utilize cunning edge tech in combat training
Solving the Opioid Crisis through Crowdsourcing Contests: HHS’s Opioid Code-a-Thon
RB
Last modified on November 13, 2018 at 7:03 pm
Why did the Department of Health and Human Services host a two-day Code-A-Thon focused on the opioid crisis? What role does crowdsourcing play in government agencies?
JP Morgan Chase & Machine Learning
Anonymous
Posted on November 14, 2018 at 8:13 am
JP Morgan Chase and Machine Learning
GuiaBolso: How machine-learning is changing competition landscape for Financial Institutions in Brazil
John Bonham
Last modified on November 11, 2018 at 1:10 pm
Machine-learning is disrupting how companies manage credit default risks allowing medium banks and fintechs to produce robust prediction models obtaining supreme accuracy and speed. GuiaBolso, one of the main fintechs in Brazil, is leveraging its large customer information database with [...]
Can Walmart Machine Learn its Way to the Top?
Nancy
Posted on November 13, 2018 at 6:41 pm
In a war between Amazon and Walmart for the e-commerce crown, who will ultimately win?
Dangerous Innovation – Defense Distributed and the Democratization of Weapons Manufacturing
Edmond Dantes
Posted on November 13, 2018 at 6:44 am
Additive manufacturing shows tremendous potential for commercial and humanitarian applications, but it also presents ethical questions and the potential for unintended consequences. 
The benefits of A.I. in Sub-Saharan Africa
Latta Latte
Last modified on November 14, 2018 at 12:58 pm
The benefits of A.I. in Sub-Saharan Africa   Artificial Intelligence is not immediately associated with Africa, a continent where c.60% of the population doesn’t have access to the electric grid1. A.I. has the potential to impact positively communities in SSA. [...]
MACHINE LEARNING IN RETAIL: AN EDITED APPROACH
tomasc
Last modified on November 15, 2018 at 6:40 pm
Over the last several decades, apparel retailers have struggled with the complexities of increasingly varied product assortments and changes in long established seasonal shopping patterns. As retailers implement new strategies to stay ahead of the demand for an omnichannel shopping [...]
Can artificial intelligence help address the complexities of non-artificial mind?
Me
Posted on November 13, 2018 at 5:53 pm
Can an app powered by machine learning be better and faster at diagnosing mental illness than humans?
Promise and Peril for Machine Learning at Netflix
S_Eckhardt
Last modified on November 12, 2018 at 11:31 pm
As the amount of content, competition, and subscribers in the online media space grows, Netflix is turning to machine learning to provide a more entertaining experience for its customers. While they are investing heavily in their proprietary recommendation engine and [...]
Could Daft Punk Actually Be Robots? How Machine Learning Could Redefine Musical Creativity at Next Big Sound
Mot Snave
Posted on November 13, 2018 at 5:52 pm
In the realm of music, Next Big Sound employs a data-centric approach to artist growth and strategy. Where future value lies for the company is in applying a similar model to the underlying product: music itself.
Irrational Exuberance: Machine Learning at the Federal Reserve
Yip
Last modified on November 13, 2018 at 6:58 pm
As the Federal Reserve enters its second century, will innovations in machine learning and artificial intelligence put our central bankers out of a job?
Partners HealthCare: Machine Learning to Improve the Patient-Doctor Experience
DoctorWatson
Last modified on November 13, 2018 at 7:27 pm
Many U.S. physicians feel that health care digitization has created serious headaches with limited benefits for patients. Will machine learning soon change their minds? Partners HealthCare, a health care system that oversees two world-class Boston hospitals, certainly thinks so.
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