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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)

How Instagram is Implementing Machine Learning to Help W/ Cyber Bullying
blovell
Last modified on November 13, 2018 at 8:39 pm
Instagram strives to irradiating cyber-bullying by leveraging machine learning.
JBS and Robot Butchers
Blake Wilson
Posted on November 13, 2018 at 12:58 pm
The world's largest meat processing company begins experimenting with machine learning in their plants. Developing and implementing these smart machines, capable of performing skilled and dexterous tasks, is pushing the current boundaries of automation.
How McKinsey is Dealing with the Machine Learning Challenge
NCB
Posted on November 13, 2018 at 6:29 pm
All industries are facing a great challenge regarding how to take advantage of all the data they have available to steer their business. How can strategy consulting firms, known for their "generalist approach", help its clients in a topic that [...]
3D printing in Automobile: End of Invention from 100 Years Ago?
H&M
Posted on November 13, 2018 at 7:59 pm
Challenge of VW: 3D printing will replace the conventional mass production process of cars?
Techs and the City: Data and Machine Learning in Boston
Paula Álvarez
Posted on November 13, 2018 at 7:57 pm
The City of Boston faces new challenges as it seeks to harness the power of machine learning to improve performance, optimize processes, and explore frontiers in local governance.
Using Machine Learning to Optimize Hospital Operations
kw
Posted on November 13, 2018 at 3:06 pm
Many healthcare systems grapple with the paradox where assets are over-booked but under-utilized daily. LeanTaaS is a startup that is using machine learning to solve this problem.
Chanel has a magic wand for beautiful eyelashes, thanks to 3D printing
mac2020
Last modified on November 16, 2018 at 12:40 am
Chanel is on the cutting edge of additive manufacturing in the cosmetics industry, as evidenced by their latest mascara launch.
Caterpillar – Embracing Open Innovation and Co-creation
July
Last modified on November 13, 2018 at 7:05 pm
Even though the global construction market is worth about $10 trillion, it is one of the slowest industries to adopt new technologies. To complete one construction project, many stakeholders, such as architects, engineering firms, equipment manufacturers, surveying companies and local [...]
Partnering with AI: Optum Labs’ Efforts to Improve U.S. Health Care
Alex Rosenblit
Posted on November 13, 2018 at 1:58 pm
Through industry partnerships, a 200 million life database, and the use of artificial intelligence (AI), Optum Labs is confronting the daunting cost and quality challenges facing the U.S. health care system
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 [...]
Quick on the Uptake: Digital transformation for industrial companies
J. Stephenson
Posted on November 13, 2018 at 7:39 pm
The future for Uptake is promising, but there are lots of opportunities - or potential pitfalls. (706)
DeepMind and the Development of Artificial General Intelligence
acm
Posted on November 13, 2018 at 6:13 pm
First Chess and now Go. What's the next to go?
Foxconn: Large Scale Manufacturing in the Machine Learning Age
C. Xu
Posted on November 13, 2018 at 5:50 pm
As Foxconn, the largest contract manufacturer in the world, faces increasing profit pressures, can it leverage machine learning to turn its business around?
To Catch a Rogue Train – SMRT’s Continuous Fight against Rail Breakdown
Kai
Last modified on November 13, 2018 at 4:00 pm
In the backdrop of increasing ridership and almost zero tolerance for breakdown, Singapore’s rail operator, SMRT, is turning to machine learning and predictive maintenance to manage failure.
SpaceX – Surviving Enrico’s Paradox
Bruce Willis
Posted on November 13, 2018 at 6:43 pm
SpaceX is in an epic effort to make humans a multi-planetary species, and escape the trap of Fermi's Paradox. To achieve this the Company has been adopting 3D-printing to gain efficiencies and reduce costs. Will it be enough?
The Merging of Sports and Technology – Nike and Additive Manufacturing
Robert Victor
Last modified on November 6, 2018 at 8:00 am
Nike and Additive Manufacturing
Crowdsourcing at Amazon: Democratization of TV / Film Content
Anonymous_HBSer
Posted on November 13, 2018 at 7:59 pm
Amazon Studios recently shutdown its crowdsourcing initiatives. This article explores their approach: What went wrong? How could they have better utilized open innovation?
Faster, Cheaper, Better: The Promise of Machine Learning for Drug Discovery
Boreal
Posted on November 12, 2018 at 10:38 am
GSK is rethinking its drug discovery pipeline using machine learning
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.
Dream On: An Exploration of Neural Networks Turned Inside Out
Jon Snow
Posted on November 13, 2018 at 7:17 pm
What if computers could dream? In fact, they can. Google's groundbreaking DeepDream software is turning AI neural networks inside out to understand how computers think.
Does the CIA want your geopolitical input? Yes, it actually does!
Matthew Ferguson
Last modified on November 13, 2018 at 11:00 pm
Intelligence agencies are considering open innovation to better predict geopolitical trends and to better respond to the new face of terrorism. Is this a great idea or a misguided attempt at forecasting the future?
Crowdsourcing as the Future of Secret Cinema
SECRET CINEMA
Posted on November 13, 2018 at 7:17 pm
With 46 ground-breaking events completed in over a decade and ambitious expansion plans on the horizon, immersive film company Secret Cinema should integrate crowdsourcing into all elements of its production. Crowdsourcing will enable Secret Cinema to continue to be a [...]
How Additive Manufacturing Can Improve Access to Adequate Housing
SD
Last modified on November 13, 2018 at 3:17 pm
Additive manufacturing improves access to housing
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