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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)

When Machine Learning Influences Your Vote: Lessons from Cambridge Analytica in the 2016 US Presidential Elections
taiikukaikei
Posted on November 14, 2018 at 10:25 am
Machine learning is changing the landscape of political advertising. Consumers need greater transparency into how their personal data influences the political messages they see online.
Using Machine Learning to Improve Neonatal Patient Outcomes at Cohen’s Children Medical Center
KMA
Last modified on November 13, 2018 at 7:55 pm
A patient in the neontal intensive care unit cannot verbally communicate with his/her doctors, but generates approximately one terabyte of medical data per year. Hospitals like Cohen's Children Medical Center in New York have the opportunity to adopt machine learning [...]
Print-a-Part: How 3D Printing is transforming Medical Device Manufacturing
Prineeta Kulkarni
Last modified on November 13, 2018 at 8:17 pm
Win-Win Innovation Fueled by the trend of precision medicine, the use of new technologies such as additive manufacturing is seeing an uptick. Additive manufacturing, specifically 3D printing, allows rapid and flexible manufacturing of medical devices that are customized to patient [...]
DoorDash and Machine Learning
Shannon
Last modified on November 15, 2018 at 6:16 pm
How DoorDash uses machine learning to power its logistics platform
Will Zalando stay ahead of Amazon in European online fashion?
MB
Posted on November 13, 2018 at 7:59 pm
Europe’s largest online fashion retailer, Zalando, started in 2008 as a European copycat of Amazon and Zappos.com. It's market leader position is under pressure - Can machine learning enable the company to stay ahead?
Maybe She’s Born With It, Maybe it’s Maybelline… or Maybe it’s Proven
Chris Chen
Posted on November 13, 2018 at 1:20 am
As long as vanity exists there will be a market for skincare. Learn more about how innovative companies leverage artificial intelligence, machine learning, and big data to disrupt a $140B global skincare market.
Open Innovation Initiatives in UNHCR Refugee Communities
Eve
Last modified on November 12, 2018 at 11:09 pm
Open innovation, in which companies and organization source information from external sources, helps businesses approach strategic decisions in a creative manner. UNHCR, whose goals are to implement changes external to its organization, would highly benefit from sourcing information and potential [...]
Driving into the Future: The Impact of Self-Driving Haul Trucks on Oil Sands Mining Giant, Suncor Energy
Leah H
Last modified on November 12, 2018 at 4:41 pm
Canada's oil sands mining industry faces the entry of self-driving haul trucks as a means to lower operating costs. In an economic environment of low crude oil prices and an unclear future for oil sands mining, is this an investment [...]
Adidas in the 3D Printed Race – When Size Does Not Matter
Viet Nguyen
Last modified on November 15, 2018 at 12:49 am
Adidas, one of the world’s largest sportswear manufacturers, is betting on 3D printing to create the next generation of bespoken sneakers for individual customers. Will we see a future when size charts become redundant, and “custom-fitted haute couture” no longer [...]
3D Printing Better Surgery at the Mayo Clinic
NBowen93
Posted on November 13, 2018 at 6:21 pm
3D printing is revolutionizing surgery and healthcare, and the Mayo Clinic is on the leading edge.
Do More with Less: Can Machine Learning Help Feed the Growing Population?
TOM.Morrow
Posted on November 13, 2018 at 4:50 pm
How do we feed a growing population in the face of a changing climate and diminishing natural resources, all while protecting our planet? Monsanto thinks it has the answer: machine learning.
Sephora and Artificial Intelligence: What does the future of beauty look like?
LG
Posted on November 14, 2018 at 10:25 am
This post explores how Sephora is using AI to enhance its retail experience
Coding the Way to Better Patient Outcomes: Machine Learning at Cigna
gumpsky11
Last modified on November 13, 2018 at 7:24 pm
American health insurer Cigna must balance the benefits of machine learning with the internal challenges that arise during implementation and the external ethical implications inherent to the healthcare industry. (Image Citation - https://www.cigna.com/guideme)
Aetna: Artificial Intelligence Goes After Health Care Fraudsters
PM
Last modified on November 12, 2018 at 11:28 pm
US health care payers lose billions of dollars per year to insurance fraud, waste, and abuse. Payers turn to machine learning to revolutionize outdated manual review processes and improve the bottom line.
All Politics Is Local: Why Boston’s City Government is Making a Smart Investment in Machine Learning
Jeff Boyar
Last modified on November 13, 2018 at 3:03 pm
The City of Boston is leveraging machine learning to better deliver on the fundamental promises of local government.
The benefits of A.I. in Sub-Saharan Africa
Latta Latte
Last modified on November 14, 2018 at 12:58 pm
The benefits of A.I. in Sub-Saharan Africa   Artificial Intelligence is not immediately associated with Africa, a continent where c.60% of the population doesn’t have access to the electric grid1. A.I. has the potential to impact positively communities in SSA. [...]
Additive Manufacturing in Medical Device: Can Johnson & Johnson stay ahead of the curve?
Ti Gillespie
Posted on November 12, 2018 at 7:48 pm
Additive Manufacturing offers substantial promise to medical device products and supply chains, but it also presents an existential threat to the incumbents in the industry.
Machine Learning: The end for America’s Most Hated Company?
CreditBureauKarma
Posted on November 13, 2018 at 7:56 pm
AI enabled alternative credit scores: A threat to Equifax?
Can Machine Learning predict, prevent and diagnose Diabetes effectively?
TOManager
Posted on November 14, 2018 at 5:38 pm
Diabetes is one of the fastest growing disorders affecting population across the globe, where diagnosis remains as big a challenge as treatment. Will Machine Learning enable healthcare companies to develop an effective disease management solution?
Open Innovation in L’Oreal
Ariel
Posted on November 13, 2018 at 6:05 pm
L'Oreal is a the world's NO.1 beauty brand that emphasized both internal and external open innovation. However, innovation from both parties may sometimes cause misalignment of interest.
Building industrial-scale LEGOs using open innovation
Mariam Hachem
Last modified on November 13, 2018 at 6:25 pm
How one company is fulfilling every engineer’s dream using industrial-scale LEGOs and open innovation
Lemonade reinvents the insurance industry with machine learning
Petra
Posted on November 13, 2018 at 7:28 pm
Lemonade, a company offering home insurance policies, is a pioneer in the InsurTech world where its use of machine learning (ML) goes beyond satisfying customers and driving efficiencies to underwriting risks and managing claims Despite its exponential growth, Lemonade’s scalability [...]
Viacom: Transforming Television with Targeted Ads
Margaret Mitchell
Posted on November 12, 2018 at 11:20 am
Can programmatic ads combine the reach of television with the targeting of digital to change the face of TV Advertising?
Bidgely: Named After The Hindi Word For Electricity, This Company Can Help You Save It
Nathan Nemon
Posted on November 13, 2018 at 6:58 pm
Imagine looking at a graph of your home’s energy usage and knowing exactly what's shaping it. Would you find this information valuable? Bidgely is betting yes and has the machine learning capability to deliver.
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