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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 noteFor 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)

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Machine learning at Spotify is a source of product differentiation in the music streaming industry.
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How unwanted crowdsourcing can be the difference between life and death for the United States Department of Defense (DoD) and leads to Open Innovation in an insurgent war
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Last modified on November 13, 2018 at 1:35 pm
This article explores the negative effects of undesired crowdsourcing and how it has been used in the battle field to yield catastrophic results.
Adidas’s Race to be #1 in 3D Printing
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Adidas is investing heavily in additive manufacturing, partnering with Silicon Valley's Carbon Inc to one day produce 50 million pairs of 3D printed shoes per year.
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Posted on November 13, 2018 at 2:55 pm
Making cutting edge products since 1900, Procter and Gamble Gillette is the market leader in the hyper competitive shaving and grooming category. Can Gillette use 3D printing technology to design artistic, innovative and customizable razors in its bid to stay [...]
Roche: Machine Learning Brings a Big Pharma Business Model Under Siege
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Roche, the Swiss pharmaceuticals giant, is caught in a race against time. After making a big bet on breakthrough drugs and personalized medicine, the company has spent much of the last 18 months thinking ahead to the challenges that machine [...]
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Posted on November 13, 2018 at 1:37 pm
Additive Manufacturing’s Importance Despite a recovery from the Great Recession of 2008-2009, productivity in the construction sector lags behind many other segments of the economy. According to a McKinsey Global Institute paper, world manufacturing productivity has increased an average of [...]
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It is undeniable the importance of data processing in decision making. Colombia has started implementing machine learning to better understand the efficient policies and maximize the impact of the taxpayers’ money in the country’s development.
Darktrace: Battling Machine Learning Threats, With Machine Learning
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As technology, and machine learning, has continued to develop exponentially, the risk and impact of cyberattacks has also increased drastically. Darktrace is using machine learning to get defense once step ahead of the attacks.
Walmart takes on Amazon: The Journey from Brick & Mortar to Click & Mortar
dook
Posted on November 13, 2018 at 6:58 pm
The retail industry is facing a digital revolution at a pace never seen before. With the digital behemoth that is Amazon, traditional brick & mortar retailers are challenged to find ways to integrate analytics to remain competitive. This article looks [...]
Blockchain Powered Asset Tokenization Protocols Threaten Goldman Sachs’ Investment Banking Business
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Tokenization of assets, including equity and debt, will disrupt investment banking.
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Posted on November 12, 2018 at 4:38 pm
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3D Printed Cars – The Future of Auto Manufacturing or a Pipe Dream?
Angelica Davis
Posted on November 13, 2018 at 4:49 pm
BMW releases the new awe-inspiring i8 roadster becoming the first OEM to mass produce a printed component for a road car. Is this the start of a technology revolution in auto manufacturing?
An Apple a Day Keeps Premiums at Bay: AI at Discovery Ltd.
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CircleUp: Riding The Wave of Machine Learning Into Your Pantry
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Posted on November 13, 2018 at 5:26 pm
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Spotify + The Machine: Using Machine Learning to Create Value and Competitive Advantage
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Machine Learning at PredPol: Risks, Biases, and Opportunities for Predictive Policing
Leila Meliani
Posted on November 13, 2018 at 4:40 pm
Law enforcement agencies are using machine learning tools to analyze, track, and attempt to predict crime.
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