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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)

Uber: Future challenges in the era of AI and ML
mthai
Posted on November 12, 2018 at 8:59 pm
Uber has been successful in implementing machine learning to solve critical business problems and bridge the gap between the physical and digital world. Claiming itself a technology platform, Uber collects a huge amount of data from both drivers and riders [...]
Open Innovation in the Investment Management Industry: Is This The New Frontier?
Hypatia
Posted on November 13, 2018 at 7:06 pm
Can the benefits of open innovation in investment management outweigh the costs? In this piece, we quickly examine the benefits of such an approach agains the backdrop of a traditional asset manager and one of the biggest struggles Quantopian, a [...]
Royal Bank of Canada banks on machine learning as equity research propels into a new paradigm
TT
Last modified on November 13, 2018 at 1:05 pm
As one of the first North American banks to incorporate artificial intelligence into equity research, RBC is capitalizing on the opportunity to use machine learning as a way to dramatically improve the speed and accuracy in conducting capital markets research.
Could Additive Manufacturing (3D-Printing) Be the Answer to Boeing’s Program Accounting Woes?
Jesse Bendit
Last modified on November 7, 2018 at 6:27 pm
Boeing has committed to investing in and expanding its use of additive manufacturing, helping to improve upon the company's complex production of select commercial jet parts. But the company will need to continue to push the limits of 3D-printing if [...]
Lily Health – Scaling access to reproductive health advice with machine learning
Howard Roizen
Posted on November 8, 2018 at 7:24 pm
Introduction to Lily Health Lily Health is an early stage start-up in Nairobi, Kenya that provides women with sexual and reproductive health advice via mobile messaging. While there are a large number of companies that provide women’s health information and [...]
Additive Manufacturing at Ford: A Long Way from the Model T
Chip
Posted on November 13, 2018 at 6:11 pm
How can Ford use additive manufacturing to speed up its product-development process, improve its competitiveness, and create value for the consumer?
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Posted on November 12, 2018 at 10:05 pm
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Hurry Up and Wait: Bringing Machine Learning to the US Department of Homeland Security
Romaan
Posted on November 12, 2018 at 10:53 pm
The US Department of Homeland Security is exploring machine learning. The outcome could be increased security and shorter lines, but what are the risks?
Turning Feelings into Data: Applying Natural Language Processing to Employee Sentiment
Jason Brown
Posted on November 14, 2018 at 10:25 am
Employees give feedback and comments to express how they're feeling. Can vendors specializing in natural language processing help organizations scale their ability to understand this data?
JP Morgan: Expanding Machine Learning Capabilities in the Financial Services Arena
Mike
Posted on November 13, 2018 at 7:59 pm
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Taking to the Skies with 3D Printed Jet Engines? GE Aviation Already is
MJamieson
Posted on November 10, 2018 at 10:22 pm
GE Aviation gains efficiency while reducing weight and complexity on its way to proving that widespread additive manufacturing is viable with critical jet engine components.
FOLIO: Challenging the Status Quo Through Community-Based Development
PA
Posted on November 13, 2018 at 7:36 pm
In response to competitive industry pressures,The FOLIO project was initiated as a community collaboration between libraries, vendors and developers to build an open source library services platform (LSP) to compete with existing players.
Duolingo: From Hello to Hallo through Machine Learning
Jackson
Posted on November 12, 2018 at 11:04 pm
Duolingo is using machine learning to help users acquire new lanaguages and verify their current language skills - are broader educational applications for Duolingo's machine learning next?
Visual Deep Learning – The Power of Images at Pinterest
C9
Posted on November 8, 2018 at 11:10 pm
Pinterest – leading the field in extracting information from visual content.
The tension between people and data at Netflix
Hebarla-Halludba
Last modified on November 13, 2018 at 8:29 pm
Netflix is one the largest media companies in the world, growing from a small DVD rental company to a subscription-based streaming platform and media behemoth. In 2017, Netflix reported having over 117 million subscribers in more than 190 countries. Every [...]
3D Printing Straighter Smiles
Jane Harvard
Posted on November 13, 2018 at 7:54 pm
"Align Technology disrupted the orthodontic industry by creating a digital approach to straightening teeth that makes treatment possible for more people than ever. None of what we have been able to achieve would be possible without 3D printing technology" - [...]
The ugliest bridge in the world. 3D printing in Acciona…
Kasia
Posted on November 13, 2018 at 2:33 pm
3D printing seems to be a natural fit for construction. It can potentially fix some of the most burning operational problems in the industry. But attempts to approach the trend are rather clumsy so far...
Enhanced Learning Through Machine Learning
Patricia Andrade
Posted on November 13, 2018 at 6:13 pm
DreamBox, an ed-tech company based in Seattle, uses machine learning to create an adaptive platform that teaches k-8 math.
How 3D chocolate printing open up new opportunities for The Hershey Company?
Objatois
Posted on November 13, 2018 at 5:00 pm
How can additive manufacturing help the US leader of the chocolate industry to address the current challenges facing its industry?
Can AI Help Tyson Foods Lead The Protein Revolution?
Sam
Last modified on November 13, 2018 at 1:44 pm
Artificial intelligence is forcing car manufacturers to change. Will the same thing happen to Tyson Foods?
Death by due diligence? Legal tech takes one for the team.
ACG
Posted on November 13, 2018 at 4:25 pm
In an industry where time is everything, legal technology is increasing both the efficiency and the accuracy of review. And this is only the beginning.
Dial-an-Algorithm: Using Machine Learning for Child Welfare Screenings
iaw507
Last modified on November 13, 2018 at 12:50 am
Should algorithms intervene when child welfare is at stake?
Flipkart: Using Machine Learning to solve unique problems in Indian E-commerce
SAML2020
Posted on November 13, 2018 at 2:02 pm
Home addresses in India pose a uniquely Indian problem- lack of standardization. This poses a challenge to e-commerce players whose success relies on efficiencies in last-mile logistics. This post talks about how Flipkart, an Indian e-commerce major is using Machine [...]
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