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

Submitted (926)

Innovating the innovation process: Raízen incubates third party innovation
Annie Hall
Last modified on November 13, 2018 at 7:14 pm
Raízen is the technology-driven and sustainable Brazilian star child of Royal Dutch Shell and Cosan, a well-established producer of bioethanol and sugar based in São Paulo. Acting as a fully integrated agro-energetic company, Raízen operates in every single stage of the [...]
An Apple a Day Keeps Premiums at Bay: AI at Discovery Ltd.
Austen fan
Last modified on November 13, 2018 at 7:26 pm
Exploring the trajectory and potential of machine learning in incentive-based insurance at Discovery Ltd.
Capacity Command Center: Machine Learning & Hospital Management at Johns Hopkins
Alexa Elinor Walls
Last modified on November 13, 2018 at 10:36 pm
A top US hospital is taking substantial steps in the use of machine learning to transform healthcare delivery
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.
Can Organovo Bio-print a Human Organ Before Money Runs Out?
Jack Livingston
Posted on November 13, 2018 at 5:54 pm
How close is Organovo to bio-printing implantable human liver tissue? Will it be able to afford the time required to achieve this monumental step in healthcare?
Recursion Pharmaceuticals: Machine Learning in Drug Discovery
Elmo
Posted on November 10, 2018 at 2:47 pm
Recursion Pharmaceuticals is deploying machine learning to deeply understand the interactions between genes, proteins, and chemicals to inform not only future drug discovery and drug repurposing, but biological life as we know it.
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?
Winsun: Revolutionizing the Construction Industry with 3D Printing
AY2020
Last modified on November 12, 2018 at 11:27 pm
Winsun is at the forefront of a paradigm shift in the construction industry. Will 3D printing be the default way we build houses in the future?
Organovo: bioprinting tissue to speed up drug development
Keeps You Guessing
Last modified on November 13, 2018 at 8:23 pm
Organovo, kicked off use of 3D printed liver tissue in big pharma research and drug development. Can it catapult the industry to shorten drug development cycle time and print entire liver organs in the next 15 yrs?
Machine Learning and AI at Delta Air Lines
Sam D.
Posted on November 13, 2018 at 12:30 pm
Understanding how AI and machine learning are affecting Delta and the world's airlines.
Darktrace: Can Artificial Intelligence lead the fight against Cyber Crime?
Maham Syed
Posted on November 13, 2018 at 2:31 pm
Rapidly increasing frequency of cyber crime In 2017, more than 4000 daily ransomware attacks were recorded in the United States, up from a daily average of 1000 in 2015. According to a survey of 254 companies in 7 countries, an [...]
Los Angeles’ Traffic Issues Could be Alleviated with Machine Learning
Bruce Wayne
Posted on November 13, 2018 at 5:45 pm
If a Los Angeles County resident is asked “what is the biggest problem facing Los Angeles?”, they typically answer with one word, traffic. Therefore, it should be no surprise that INRIX recently ranked Los Angeles the most congested city in [...]
What does Machine Learning mean for a technology services vendor?
The biltmore
Posted on November 14, 2018 at 12:18 am
Machine learning is disrupting Zensar's business model in the short term but also creating significant opportunities over the medium and long term
Future X and Open Innovation at Nokia
Commander
Last modified on November 13, 2018 at 9:45 pm
Anticipating the technical revolution around the corner, Nokia took a longer view and made a strategic shift to become a wireless-equipment company. Recognizing limitations in its research, manufacturing, and human capabilities, Nokia invested in open innovation to improve product development. [...]
Alibaba: Application of Machine Learning in Logistics
Water-harvested Cranberry
Posted on November 12, 2018 at 6:14 pm
Yesterday, Alibaba reached $31B of sales in 24 hours in the Singles' Day Shopping Festival. Alibaba is able to deliver 100 million packages in 2.8 days. This miracle is enabled by its huge investments in the logistics sector and by [...]
Axon Enterprise and Machine Learning
Lost Angels
Posted on November 13, 2018 at 4:16 pm
Axon, known for its tasers and body cameras, is now using enhanced video, image, and audio processing to make communities safer
BMW & Additive Manufacturing: Using New Technologies to Drive Down Production Costs & Timelines
T123
Last modified on November 13, 2018 at 12:33 pm
BMW is committed to using additive manufacturing to increase production efficiencies as well as allow for easier part replacements.
Climate Connect: Bridging the gap in Utilities
J.C.
Last modified on November 11, 2018 at 7:39 pm
Role of AI and ML help in bridging the gap in utilities sector as the industry shifts from fossils to renewables.
Machine Learning for Machines
Akash Section H
Posted on November 13, 2018 at 7:21 pm
Kebotix is a startup in Boston combining machine learning and robotics to accelerate the discovery of advanced materials.
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?
Can data buy you value in the capital-intensive oil and gas industry?
Sneha Biswas
Last modified on November 12, 2018 at 11:42 am
“Data is just like crude. It’s valuable, but if unrefined it cannot really be used.” [1]
Spotify: Music Discovery in a World of Discover Weekly
TOM Petty
Last modified on November 13, 2018 at 1:02 pm
Machine learning has underpinned Spotify's foray into personalized recommendations, distinguishing from earlier players in the arena. How good are its formulae and what are the broader implications of programming taste?
How Stryker Hopes to Win with Additive Manufacturing
Hersh Patel
Posted on November 13, 2018 at 2:01 pm
While Stryker has launched 3D-printed medical implants in the past, it recently made significant investments in additive manufacturing technology that it hopes will make it a leader in the medical technology industry.
Fashion Forward – using deep learning at ASOS to predict customer lifetime value in online fashion retail
Karen Nyawera
Last modified on January 12, 2019 at 9:35 am
ASOS is using deep learning neural networks to predict customer lifetime value based on online shopping behavior.
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