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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)

Machine learning to save millions of dollars of advertising waste at P&G
MZ
Posted on November 13, 2018 at 7:30 pm
The power of machine learning is leveraged today by P&G to improve advertising targeting and ROI, especially in search and programmatic. In the near future, ad fraud is an area that might also benefit from this new trend.
IBM’s Deja Vu in Disruption
Jason Jackson
Posted on November 13, 2018 at 6:54 pm
Is IBM making it's biggest mistake since 1970 by not fully embracing open innovation?
The Future at Nike: 3D printing customized shoes at home
Alexandra Groot
Last modified on November 14, 2018 at 1:03 pm
Assessing the path towards 3D printing your customized Nikes at home
MOO-ve Over Alexa, Meet the Udderly Efficient IDA (a.k.a. the Intelligent Dairy Farmer’s Assistant): How One Food Conglomerate Helped Pilot Machine Learning to Make the Dairy Industry More Sustainable
L Wallace
Posted on November 13, 2018 at 7:16 pm
Danone teams up with a start-up to explore artificial intelligence in the dairy industry. Can a FitBit for cows keep farmers happy and cows healthy with long-term benefits to the conglomerate's supply chain?
Machine Learning in Airline Loyalty Programs
Paxton Zhou
Last modified on November 13, 2018 at 6:39 pm
Airline loyalty programs (also called Frequent Flyer Programs) have become a new source of high margin income for traditional airline companies. Meanwhile, loyalty programs also generate massive amount of data on customer behaviour as people spend and collect their points. [...]
Data on Tap: PepsiCo Knows What You Like to Drink
hbsstudent123
Posted on November 13, 2018 at 2:28 pm
How AI can help soda giant, PepsiCo, adapt to changing trends towards health and wellness.
iFLY uses Open Innovation to (Sky)dive into the World of Virtual Reality
Hermione
Posted on November 9, 2018 at 9:50 am
Can a growing experiential entertainment company revolutionize its product offering? Leveraging open innovation and new technologies allows iFLY to soar to new heights!
Music Curation: Finding Quality When We Get Quantity Over Quality
VP
Posted on November 12, 2018 at 5:36 pm
In an age where music is readily available via streaming music services, how is Spotify using machine learning to find music that is right just for you?
Dynamic Yield Is Using Machine Learning to Generate Personalized User Experiences for Your Customer
Marketer Mary
Last modified on November 15, 2018 at 6:34 pm
Dynamic Yield is building an omni-channel personalization marketing software that equips any company to rival Amazon. Through machine-learning capabilities, a user received a personalized customer experience across any platform.
Danko Arlington: The Future of Additive Manufacturing in the Aerospace Casting Industry
Sean
Posted on November 12, 2018 at 5:34 pm
3D printing to disrupt the aerospace casting supply chain
Overpromising and Underdelivering at Sloan Kettering: is AI Still ‘Human’ After All?
LPB
Posted on November 12, 2018 at 7:33 pm
The introduction of artificial intelligence to healthcare has sent shockwaves through the system with the promise of dramatic increases in quality of care and organizational efficiencies coupled with much needed cost reductions. The promise of AI in healthcare predicts a [...]
Buoy Health’s mission to debunk Dr. Internet
Anna Lake
Posted on November 13, 2018 at 6:53 pm
Buoy Health is improving the way you Google your symptoms
Machine Learning, Defense Innovation and the British Army
Desmond Wolfe
Posted on November 13, 2018 at 4:50 pm
A discussion of machine learning, its applications with respect to the British Army and an examination of the organizational structures required to support Research and Development.
Sharing Data to Advance Cancer Care at Memorial Sloan Kettering Cancer Center
Theo Williamson
Posted on November 13, 2018 at 8:01 am
The trend towards precision oncology and machine learning for cancer care is unmistakeable. In a fast-growing industry, however, it is important to consider the risks and unintended consequences of sharing data.
Cedar: Making Paying Doctors Much Easier
Nick Van Exel
Posted on November 13, 2018 at 7:16 pm
Sick of receiving confusing hospital bills in the mail that take hours to interpret and process? Through the use of machine learning and modern payments technology, Cedar addresses this major pain point by saving the patient and hospital valuable time, [...]
3D Printing & The Future of Army Resupply in Remote Areas
Al Borland
Last modified on November 13, 2018 at 9:07 am
The US Army has long struggled to resupply remote combat outposts. With advances in additive manufacturing, that need may disappear.
U.S. Department of Health and Human Services: Using Open Innovation to Fight the Opioid Epidemic
PS2020
Last modified on November 13, 2018 at 2:38 pm
The U.S. government has turned to crowdsourcing to help solve some of the most pressing public health issues.
Tesla: Driving Into the AI Future?
Low Rider
Posted on November 13, 2018 at 6:29 pm
This post examines the impact of machine learning and public perception on Tesla's autonomous vehicle product development process.
Gantri Shines a Light on 3D Printing for Home Décor
TOMGirl29
Posted on November 13, 2018 at 2:52 pm
Gantri (a new design company based in San Francisco) uses 3D printing to create light fixtures that are designed by independent artists from around the world.
Grammar(ly): Who sets the rules?
Ben
Posted on November 13, 2018 at 11:58 pm
Over the past decade, Grammarly has accumulated 7M daily users of its grammatical suggestion engine [1]. Now Grammarly hopes to go beyond grammar in its mission of improving communication. How they do that depends on us.
The Road to Autonomous Driving at Fiat Chrysler Automobiles
Brian Rockwell
Last modified on November 12, 2018 at 8:42 pm
As the world's automakers commit billions to autonomous driving, FCA chooses to rely on the experts
Running on Netflix: How Machine Learning is Fueling Your Netflix Binge-Watching Problem
Reed Hastings
Posted on November 13, 2018 at 7:27 pm
In an era of decreased attention span, heightened competition and high content creation costs, Netflix is countering churn with innovative machine-learning algorithms which aim to provide subscribers with the most personalized entertainment experience but would this be enough to maintain [...]
Can Machine Learning Save Us From Being Stuck in Traffic?
Sebastian Wilner
Posted on November 13, 2018 at 6:23 pm
Rapid-Flow is solving traffic congestion by offering governments a real-time traffic signal control system powered by machine learning.
Alexa, What’s in my Wallet? Open Innovation at Capital One
Dave Colletta
Last modified on November 14, 2018 at 3:42 pm
In an effort to spur innovation, Capital One has opened up access to its data for external developers via API. To what extent can they shift toward the business model of technology platform, and what organizational changes will they need [...]
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