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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://digital.hbs.edu/platform-rctom/how-to/.

Submitted (926)

Realizing the Promise of Additive Manufacturing at Boeing
NA
Posted on November 12, 2018 at 6:57 pm
I spent 6 years in the Propulsion Product Development (PD) team at Boeing. During this time, additive manufacturing (AM) has gained recognition as a technological solution that could significantly improve product development cycles, design and manufacturing at Boeing.  While Boeing [...]
Paypal vs. Fraud – Have no fear, machine learning is here !
Sophie Stuart
Posted on November 11, 2018 at 9:35 pm
As globalization and online shopping increase the risk of fraud, consumers are looking to protect their data. Some companies, like PayPal, promise end-users to keep their information safe. But how can they deliver on this promise? Machine learning is certainly [...]
ML and Chill: Machine learning at Netflix
A
Posted on November 13, 2018 at 5:59 pm
Netflix uses machine learning based on implicit data in nearly every part of the user experience — but what risks does this approach create?
Printing the Future of Helicopters with Bell
Ryan Lynch
Posted on November 13, 2018 at 5:43 pm
3D printing is reshaping the way that the aerospace industry develops and produces aircraft. Bell Helicopters is turning additive manufacturing into a competitive advantage within the world of rotary wing aerospace.
Machine Learning and the Future of Agriculture
David Host
Last modified on November 12, 2018 at 8:34 pm
The world faces a fundamental food problem: quantity versus quality. For the last several decades these two notions have been at odds, with the gap widening. What can put a stop to this?
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