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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)

An A.I. Odyssey: How Fox is Using Machine Learning to Market Movies
Jean-Philippe Gauthier
Posted on November 11, 2018 at 2:56 pm
Movie studios have historically relied on experience to predict movie budgets and their allocations. In recent years, they have begun leveraging machine learning to improve marketing efficiency. Fox has been at the forefront of these efforts through its collaboration with [...]
New Story: Remodeling Affordable Housing Through 3D Printing
SHo
Posted on November 13, 2018 at 12:51 am
New Story is tackling global homelessness and affordable housing with a 3D printed home that can be built in 24 hours for $4,000.
When HHS becomes iOS: Harnessing Open Innovation to Combat the US Opioid Crisis
Justin Mundt
Posted on November 13, 2018 at 7:39 pm
Can same approach that delivered an open source operating system and the free encyclopedia help address the opioid crisis?
Mass General Hospital Radiology
MS
Posted on November 12, 2018 at 6:42 pm
Properly assessing a diagnostic image in radiology is imperative to a positive patient outcome. Unfortunately, there are major challenges that confront most radiologists, but AI and ML can help.
Detroit and the Future of the Automobile: Will Additive Manufacturing Help GM Beat Silicon Valley at its Own Game?
RL
Last modified on November 13, 2018 at 4:53 pm
Software and tech have eaten the automotive industry. Is 3D printing the key to Detroit's survival? GM plans to find out.
Snowy Cheese Flavored Latte: Starbucks and Machine Learning in China
Mutian
Last modified on November 12, 2018 at 3:26 pm
Starbucks has been an innovator in big data and machine learning through its highly successful mobile order and pay application. How can that translate to China, its next leg of growth?
Machine Learning – In Theatres Now
Anjali Itzkowitz
Posted on November 12, 2018 at 8:52 pm
Movie studios are using machine learning to try to predict audience demand and develop new titles
An Open Call for Help: Can Pfizer Find the Cure for Cancer… Outside the Walls of Pfizer?
Helene
Posted on November 13, 2018 at 7:20 pm
The discovery of groundbreaking medical treatments may no longer solely rest in the hands of scientists; grassroots R&D efforts combine scientific expertise with the experiences and creativity and horsepower of the masses.
Royal Bank of Canada banks on machine learning as equity research propels into a new paradigm
TT
Last modified on November 13, 2018 at 1:05 pm
As one of the first North American banks to incorporate artificial intelligence into equity research, RBC is capitalizing on the opportunity to use machine learning as a way to dramatically improve the speed and accuracy in conducting capital markets research.
Speeding the Drug Discovery Pipeline with Open Innovation
Patrick Jones
Last modified on November 15, 2018 at 5:21 pm
Can open innovation speed the drug discovery pipeline?
On the Shoulders of Giants: How Amazon Uses Machine Learning and Consumer Data to Disrupt its Partners
Nassim Graham
Last modified on November 11, 2018 at 2:15 pm
What if I told you...that the flow of aggregated consumer shopping data could be multi-directional?
Hurry Up and Wait: Bringing Machine Learning to the US Department of Homeland Security
Romaan
Posted on November 12, 2018 at 10:53 pm
The US Department of Homeland Security is exploring machine learning. The outcome could be increased security and shorter lines, but what are the risks?
The Artificially Intelligent Brewer: Carlsberg’s Breakthrough Project
Roni
Posted on November 14, 2018 at 8:02 am
Humans have been producing beer for over 5,000 years, and it has become our most consumed alcoholic beverage worldwide. But is brewing an art or a science? The rise of the craft beer segment suggests that many of us perceive [...]
UNICEF: Open innovation to tackle humanitarian crises
K Fukagawa
Posted on November 13, 2018 at 6:45 pm
Open innovation is drastically changing the way the humanitarian sector delivers aid: UNICEF leads the way.
Walmart Fights Fire with Fire: Traditional Retail in the Age of Machine Learning
Rob Stark
Posted on November 13, 2018 at 6:42 pm
Omni-channel retail is the battleground of the future. Walmart fights back against e-commerce giants like Amazon by using machine learning to roll out competitive product offerings in a race to omni-channel supremacy.
Xcel Energy: New challenges and ML solutions
Nametagfriday
Posted on November 13, 2018 at 3:02 pm
Electric utilities are facing new challenges as they try to integrate solar and wind generation. Machine learning technologies may have some of the answers.
Boeing: “Adding” to the Manufacturing Process
mlazarczyk
Posted on November 13, 2018 at 10:45 am
Boeing has leveraged additive manufacturing to improve upon its existing production processes. To what extent can Boeing continue to capitalize off of these capabilities and what obstacles stand in its way?
Additive Manufacturing at GE Aviation
Carlos G
Posted on November 13, 2018 at 7:14 pm
Can jet engine parts really be made from powder? General Electric certainly thinks so.
Face recognition technology hunts for rare diseases
Theon Greyjoy
Last modified on November 12, 2018 at 5:35 pm
FDNA Inc. helps doctors to diagnose rare diseases with a camera of a cellphone
Building the Worlds You Want To See: Lego Calls on You To Co-create
Gwen James
Posted on November 13, 2018 at 2:49 am
In an increasingly digital world, Lego, the famous plastic construction toy company, continues to generate interest in physical toys and to build brand loyalty by leveraging crowdsourcing and user co-creation for popular product innovations.
Unlocking the power of STATS
Significantly Correlated
Posted on November 13, 2018 at 4:12 pm
In an arena where any slight edge could mean the difference between winning and losing, machine learning has never been more important in sports. As the industry becomes more and more inundated with data, sifting through information to create meaningful [...]
American Express: Machine learning for customer churn prediction and more effective customer retention
CS squared and B cubed
Posted on November 13, 2018 at 7:59 pm
The financial services industry is especially challenged in customer retention. American Express has used machine learning to predict churn for its own customers, and have transformed that capability as a product for its merchants.
J.P. Morgan: Trades and payments with AI. What’s next?
Operator
Posted on November 13, 2018 at 12:57 am
J.P. Morgan is using AI to execute trades and assist corporate clients with payments. Other banks are also working on similar initiatives. Can AI help J.P. Morgan and other big banks retain customers and differentiate from competitors?
Can the maker of Post-it notes solve healthcare pricing?
Jeff Dean
Posted on November 13, 2018 at 5:21 pm
3M and Google's Verily team up to beat healthcare costs with machine learning
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