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RC TOM Challenge 2018

November 13, 2018

Read The Full Prompt

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://d3.harvard.edu/platform-rctom/how-to/.

Submitted (926)

Darktrace: Battling Machine Learning Threats, With Machine Learning
Michael Scott
Posted on November 14, 2018 at 10:31 am
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.
PayPal’s Use of Machine Learning to Enhance Fraud Detection (and more)
Casilda Aresti
Posted on November 13, 2018 at 7:56 pm
This essay will begin by focusing on how and why PayPal is leveraging machine learning in fraud detection today. It will then consider additional potential applications of machine learning across the customer journey, and how these applications may serve to [...]
Achieving more with less in pharma R&D: Takeda’s open innovation programs
Miho Sakuma
Last modified on November 12, 2018 at 8:57 am
Japan’s oldest and largest pharmaceutical company chose open innovation as a tool to compete in the race to increase R&D productivity
A Needle in an Underwater Haystack: Machine Learning and the U.S. Navy’s Hunt for Submarines
Michael Glynn
Posted on November 14, 2018 at 1:00 am
Submarines are becoming more numerous and quiet as an era of Great Power competition heats up. How is the U.S. Navy adopting machine learning to combat this new threat?
Are Killer Robots the Future of Modern Warfare
Major Payne
Last modified on November 12, 2018 at 1:49 pm
As AI and Machine Learning continue to develop, how will this affect the way we fight wars.
Keeping fighter jets in the fight; additive manufacturing’s solution to supply chain woes
Nicholas Dimitruk
Last modified on November 13, 2018 at 7:52 pm
How additive manufacturing could be the solution to part shortages in military aviation
Solidifying the impact of open data innovation in the government – NYC311
AA
Posted on November 13, 2018 at 7:28 pm
NYC311 has made great strides in evidencing the power of data analysis and innovation within the government, through opening up its data. Now it needs to build capacity in-house and answer tough questions to solidify the long-term impacts of open [...]
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 [...]
The Future of Preventative Behavioral Healthcare Powered by Machine Learning
Kentucky Freud Chicken (MDZ)
Last modified on November 13, 2018 at 11:02 pm
Improving preventative mental health care through passive a smartphone application enabled by machine learning
Envision Energy: Use machine learning technology to achieve an energy efficient and low-carbon future in China
YT
Posted on November 13, 2018 at 6:51 pm
How to release the full potential of renewable energy? Energy internet and machine learning would the right combination to achieve the energy efficient and low carbon future for China.
Zebra Medical Vision: Machine Learning Meets Healthcare Imaging
Agatha Christie
Posted on November 13, 2018 at 6:00 pm
Zebra Medical Vision: Machine Learning Meets Healthcare Imaging
Stitch Fix: The Fashion Maven of Machine Learning
John Harvard
Posted on November 8, 2018 at 7:35 pm
Stitch Fix is utilizing machine learning to be your personal shopping assistant--changing the retail landscape one algorithm at a time.
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 [...]
Metal Additive Manufacturing at General Electric (GE) as future Competitive Advantage across Business Units
Der Biez
Posted on November 12, 2018 at 9:54 pm
GE stomped its way into the metal additive manufacturing space through major acquisitions. Why did they do this and what are they trying to accomplish?
OpenIdeo – Using Open Innovation to Tackle the Biggest Societal Issues
A Iglehart
Posted on November 12, 2018 at 3:21 pm
OpenIDEO aims to utilize design thinking and open innovation to solve the worlds toughest problems.
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.
Predictive Policing: Promoting Peace or Perpetuating Prejudice?
Holly F
Posted on November 13, 2018 at 4:30 pm
The Chicago Police Department's embrace of machine learning raises critical questions about the balance between community safety, civil liberties, and systemic bias.
XPO Logistics (XPO): Attempting to Bring the Truckload and Less-than-Truckload (LTL) Industries into the Twenty-First Century
Count of Monte Cristo
Posted on November 13, 2018 at 1:47 am
In stark contrast to the airline and auto industries, the trucking industry continues to remain stuck in a time warp. Will XPO Logistics (XPO) – a leading provider of LTL services - be able to successfully harness machine learning and [...]
Printing Bone: How Should Orthopaedic Surgery Practices React to Advancements in 3D Printing?
Jordan Lebovic
Last modified on November 13, 2018 at 7:22 pm
3D printing technology has made significant advancements in the past few years. Can 3D printing be used in orthopaedics? Is this technology ready for surgery? How could orthopaedic practices best position themselves?
Easier Than Shoplifting: How Amazon Go is Revolutionizing Brick & Mortar Retail
Samuel F.
Posted on November 13, 2018 at 7:25 pm
Amazon’s application of machine learning to e-commerce transformed customers’ buying behaviors forever; the firm’s newest brick-and-mortar offering threatens to similarly revolutionize consumers’ retail experiences.
Product Innovation Requires Production Innovation: Additive Manufacturing as an Enabler
ksimmons
Last modified on November 13, 2018 at 2:08 pm
Lumiena, a startup making "smart" LED lighting systems, couldn't find the processing equipment it needed to make its novel products since the technology didn't exist. Thanks to additive manufacturing, it made its own equipment, and this was a game-changer until [...]
Chasing Glory: How Ferrari S.p.A. is embracing Additive Manufacturing to Win Again
rtillman@mba2020.hbs.edu
Posted on November 12, 2018 at 10:58 pm
Tired of finishing second to its racing arch-nemesis, Mercedes, Scuderia Ferrari S.p.A is leading Ferrari's charge into the future by teaming with Renishaw, a British engineering firm that specializes in additive manufacturing (AM). Ferrari is looking to ride the wave [...]
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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