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

Submitted (926)

Creating a “Factory of the Future”
Anuj Lohia
Last modified on November 13, 2018 at 6:38 pm
How machine learning can improve inefficiencies and deliver cost-savings at the factory level in the manufacturing industry. Company Brief: Indorama Ventures (IVL) is a petrochemical company, operating in 29 countries across five continents. Their operations are mainly in the manufacturing [...]
Partners HealthCare: Leveraging Machine Learning to Predict Heart-Disease
cjames
Last modified on November 15, 2018 at 8:07 am
Faced with ongoing U.S healthcare reform that forces hospitals to bear financial risk for patient outcomes, Partners Healthcare should embrace the power of machine learning to cut costs and improve quality of care
StoryCorps: Crowdsourcing to Preserve Humanity’s Stories
Keith Bender
Last modified on November 15, 2018 at 10:38 pm
StoryCorps drives product and content generation through physical and digital crowdsourcing of human stories
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 [...]
The Ma in Machine Learning
Christie Klauberg
Last modified on November 12, 2018 at 10:38 pm
Machine Learning and AI in E-Commerce Jack Ma’s Alibaba has been at the forefront of innovation since its founding in 1999 from an apartment in Hangzhou, China. Alibaba’s original but lasting mission has been to connect buyers from around the [...]
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.
Using machine learning to bend the healthcare cost curve
wm25
Last modified on November 13, 2018 at 6:10 pm
EHR and billing services provider athenahealth uses machine learning to automate administrative tasks - how can they use their unique market position to add more value for their clients?
Building a Brave New World in Toronto’s Quayside
Chrissy Pringle
Posted on November 13, 2018 at 7:26 pm
What would the smartest city in the world look like? And how would we even begin to plan, build, and maintain it? This is exactly what Alphabet-owned Sidewalk Labs is trying to figure out with their latest Toronto waterfront development [...]
Will you marry me (if I ask with a 3D-printed ring)?
Aubrey Graham
Posted on November 13, 2018 at 2:50 pm
Additive manufacturing in jewelry has enabled rapid prototyping of customer-specific designs, improved the speed and accuracy of creating wax molds, and is beginning to disrupt traditional production methods with the direct printing of finished products using precious metal powders.
ZOZO’S AMBITION: CAN YOU QUANTIFY “COOL”?
Issei Suzuki
Last modified on November 13, 2018 at 8:12 pm
ZOZO, Japan’s dominant online retailer of apparel and related lifestyle products, with approximately $1B in sales and $7B in market capitalization, has taken on a journey to recreate the world of apparel to the next level. [1] It aims to [...]
Open innovation: Virgin Hyperloop One’s Global Challenge
soonerfan
Last modified on November 13, 2018 at 5:28 pm
Hyperloop - most people have an opinion about the technical feasibility of Elon Musk's space-age proposal transportation. Setting this discussion aside for a moment, consider an equally fundamental question: how would you even fund it, much less run one profitably? [...]
23 & Who?: Deep Research into our Genetic Code
John Bracaglia
Last modified on November 14, 2018 at 1:33 am
How can machine learning answer the centuries-old question of who we really are?  
Glossier Beauty: Innovating, Not Inundating
J Student
Last modified on November 13, 2018 at 8:14 pm
Glossier democratizes beauty, builds a community of consumers to drive product innovation.
Put Your Money Where Your Mouth Is. Align’s Approach to Additive Manufacturing
Gabe Rosen
Posted on November 12, 2018 at 8:11 pm
Align Technology, the makers of Invisalign, boasts the largest customized 3D printing operation in the world. But the revolution in additive manufacturing is nothing for them to smile about.
Process Development Disruption in the Oil & Gas industry: Open Innovation to Drive Value in UK Under-Explored Areas
Jane
Posted on November 13, 2018 at 2:25 pm
In 2015 and 2016 the UK Government took a new approach to attract interest to its oil & gas resources, adopting an open innovation model as a short and long term value driver in the country’s energy sector. First steps [...]
Building Homes for Those in Need and for the Future: How 3D Printing is Transforming the Housing Landscape
RCTomUser555
Last modified on November 15, 2018 at 6:08 pm
Housing is a basic human need, yet millions around the globe lack access to basic housing, or currently live in dire conditions. How can 3D printing transform access to housing around the globe?
Hinge and Machine Learning: The makings of a perfect match
Megan M
Posted on November 9, 2018 at 9:02 am
Hinge, an innovative dating app, is using AI and machine learning techniques to improve its matchmaking algorithm
Craft beer by the people, for the people
Craft Brewer
Posted on November 13, 2018 at 4:42 pm
Would you ever buy a craft beer whose taste is constantly changing? A UK startup is challenging the way companies approach product development by leveraging Machine Learning to improve its beer recipes based on drinkers’ feedback.
Everything is Awesome: Product Innovation at LEGO
LxHuang
Last modified on November 15, 2018 at 12:12 am
LEGO has been highly successful in translating user generated ideas into commercial product lines using its LEGO Ideas platform. How should the company approach the current and future challenges of keeping its external innovators engaged and continue the product innovation [...]
Skolkovo, Russian Silicon Valley vs. Corruption: how innovation can thrive?
SN
Posted on November 12, 2018 at 5:55 pm
Skolkovo was built with aspiration to nurture domestic breakthrough talent so much needed for the failing economy. In spite of the flamboyant federal support, empowered security services and corrupted government officials push innovation in the opposite direction.
The Death of the Starving Artist: Patronage via Patreon
VI Yap
Posted on November 12, 2018 at 11:18 pm
Subscription-based crowdfunding platforms like Patreon claim to help artists to make a fair living through fan support - but is that truly the case?
DoD Additive Manufacturing: Pushing Supply Solutions to End Users
Ian Hossfeld
Posted on November 12, 2018 at 10:49 pm
The US Department of Defense is implementing additive manufacturing capabilities across all unit levels on projects both big and small.
From Housing Marketplace To Lifestyle Platform. How Airbnb’s Democratized Innovation System Influences Its Product Strategy
King Mbaku
Posted on November 13, 2018 at 3:51 pm
Airbnb’s democratized innovation marketplace and external communities of hosts and guests has helped it to direct its product strategy over its 10-year history. In this piece, the author explores how the tech unicorn has utilized its distributed knowledge to develop [...]
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?
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