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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)

AI chatbot behind Alibaba’s $31 billion Single’s Day sales miracle
Amanda Dong
Posted on November 12, 2018 at 4:27 pm
This essay introduces how Alibaba uses the artificial intelligence chatbot, AliMe, to perform customer service.
Sherwin-Williams: A Case Study of Open Innovation
Rupert Thaddeus Mortimer III
Last modified on November 12, 2018 at 6:50 pm
One might not expect a 152-year-old paint company to have an intense focus on open innovation. But Sherwin-Williams, the largest global producer of coatings (i.e. paint products), is doing just that.
Does a 3-D Printing Startup Have a Solution to the Affordable Housing Epidemic?
HBSN714
Last modified on November 13, 2018 at 4:45 pm
Will 3-D Printing of Homes Become a Viable Tool for Social Impact and Addressing Unaffordable Housing?
Machine Learning Is Already Changing How We Buy Online, But Will It Transform How We Think Of Commerce?
@NedStark
Last modified on December 17, 2018 at 4:19 pm
eBay is already using machine learning capabilities to enhance your experience on the site, have you noticed?
Machine Learning for Recruiting at Amazon – Challenges and Opportunities
HBS2020_12345
Posted on November 13, 2018 at 7:06 pm
Amazon's challenges and opportunities using machine learning for recruiting
Training Robots to Curate Individualized News
North
Posted on November 13, 2018 at 1:54 pm
Social news provider Newstag is addressing issues of user engagement and content aggregation through deployment of machine learning algorithms
Pinterest knows what you want before you do
JC
Posted on November 8, 2018 at 8:11 pm
With the world's largest image rich data set, Pinterest is using machine learning to show you what you want before you are able to articulate it.
Ripple: Leveraging Distributed Ledger Technology to create a single International Remittance Network
Jayant Walia
Last modified on November 14, 2018 at 9:26 pm
Opening up International Remittances
Opening up the doors of city hall, everywhere
Vanessa Trinh
Last modified on November 13, 2018 at 2:44 pm
Governments have to innovate to meet the growing and complex demands of its constituents, but how? And with who?
Toronto Raptors: Machine Learning as a Method for Improving the Roster Decision Process
Bo G
Posted on November 13, 2018 at 5:22 pm
In the competitive world of professional basketball, organizations such as the Toronto Raptors are turning to AI to improve the roster decision process in order to gain a competitive advantage in the race for a championship team.
Predicting loan repayment rates for unsecured loans in Uganda
Satomi
Last modified on November 13, 2018 at 5:33 pm
Using machine learning to gauge small business owner's credit worthiness to provide unsecured loans. Real application limited by small sample size. Basic statistical analysis could be more useful than complicated predictive analysis for small data sets.
Round Down: John Deere Brings Machine Vision to Precision Agriculture
cranberries
Last modified on November 13, 2018 at 6:14 pm
In 2017, the world's largest tractor company spent $305M to acquire a startup that distinguishes lettuce from pigweed. As a result, US farmers are freeing themselves from Monsanto's Roundup. Is John Deere's machine learning approach the future of ag tech?
Not just winging it: predicting airfare at KAYAK
Em Batt
Last modified on May 23, 2019 at 5:36 am
How KAYAK uses machine learning to predict drops in plane ticket prices.
Investment Banks and Machine Learning: Friend or Foe?
Samuel Hill
Posted on November 13, 2018 at 6:31 pm
Investment Banks must start embracing machine learning to remain competitive. For instance, UBS is rethinking the bond issuance process through a Canadian tech startup – Overbond – which provides estimates for the timing and price of a potential issuance.
NIVEA: Leveraging Open Innovation to Drive Product Development in a Race to be the World’s Leading Skincare Company
John Smith
Last modified on November 13, 2018 at 12:38 pm
Utilizing open innovation to drive product development at NIVEA
DHL: Cracking Logistics with the help of Machine Learning
CrackingLogistics
Last modified on November 13, 2018 at 7:40 pm
DHL is using Machine Learning and AI to augment its vast logistics platform.
Goldman Sachs: Is a dedicated App Store the Future of Retail Banking?
veritas
Last modified on November 13, 2018 at 4:56 pm
As traditional retail banks catch up to Goldman Sachs’ success with online savings bank Marcus, public open innovation facilitated by a dedicated App Store could build upon Goldman's internal innovation to unlock the next generation of retail banking.
How unwanted crowdsourcing can be the difference between life and death for the United States Department of Defense (DoD) and leads to Open Innovation in an insurgent war
Alejandro Martinez
Last modified on November 13, 2018 at 1:35 pm
This article explores the negative effects of undesired crowdsourcing and how it has been used in the battle field to yield catastrophic results.
Spotify: Machine Learning as Recommendation Engine and Musical Composer?
Jane S
Last modified on November 13, 2018 at 1:09 pm
Spotify has invested heavily in machine learning capabilities to power its recommendation and personalization engines in a competitive streaming environment. Is this a competitive advantage the company can maintain?
Volkswagen Hits the Road with the Adoption of 3D Printing
L_401
Last modified on November 13, 2018 at 5:23 pm
Volkswagen is leading the pack in integrating additive manufacturing into its production process. But is this technology scalable? Can it ever materially impact VW's bottom line?
Stanford Health’s Vision of a “Smart Hospital”
Alec Petersen
Last modified on November 13, 2018 at 2:19 pm
Creating smart hospitals using artificial intelligence
3D Printing and Humanitarian Aid, Will the US Learn from Past Disastrous Response?
Bnewton@mba2020.hbs.edu
Posted on November 13, 2018 at 1:43 pm
I argue that the standard US response to disaster (i.e. Puerto Rico) could be drastically improved by incorporating Additive Manufacturing in relief efforts.
CIA to CAI? Spycraft in the Era of Machine Learning
GM
Posted on November 12, 2018 at 4:13 pm
While machine learning and artificial intelligence technologies enable the CIA to process vast amounts of information, algorithms are far from replacing human spies. James Bond will still have his job.
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
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