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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)

Rome Wasn’t Built in a Day (Neither was Toronto)
UrbanTalker
Posted on November 13, 2018 at 6:15 pm
Google's building a new city and using the power of the crowd to do it. Begs the question - is open innovation the future of city planning?
Boston Red Sox, Beacon, and Buy-In
Colin E Ryan
Last modified on November 15, 2018 at 4:15 pm
The Boston Red Sox upgraded their machine learning capabilities to provide user-friendly data to management and players. Management and players bought-in to the system, and many wins ensued.
Machine Learning at Wayfair
Litmus
Posted on November 12, 2018 at 6:33 pm
As e-commerce continues to grow rapidly, data on online customer shopping habits and behaviors also continues to expand. Customers are typing in millions of searches an hour, and each results page is a data point that can be fed back [...]
A Bridg to Nowhere?
anonymous123
Posted on November 13, 2018 at 7:13 pm
In a world where Amazon seems unstoppable, traditional brick-and-mortar retailers are pinning their hopes on Bridg, a company with thirty employees and one powerful algorithm.
Alibaba & the future of retail
AFM
Posted on November 13, 2018 at 8:08 pm
Alibaba's data dominance and omni-channel strategy
Adding Value across the Value Chain — Additive Manufacturing at Siemens
James
Posted on November 13, 2018 at 5:53 pm
Siemens is leveraging additive manufacturing to create value across its value chain -- from equipment manufacturing to repair, maintenance, and services.
The Missing Piece: How Lego Found Open Innovation at a Critical Time
thisisapseudonym
Posted on November 13, 2018 at 6:28 pm
Lego was facing financial distress in the mid-2000s. In this time of turmoil, it turned to open innovation to restart its business.
Machine Learning and Radiologists: Friends or Foes?
Tom
Posted on November 13, 2018 at 3:15 pm
Machine learning and artificial intelligence are looming disruptors in the field of radiology. What are leading health systems doing to tackle this issue?
Eyes on the Road: Deep Learning and Real-time Crowdsourcing at Mobileye
Thomas T. Tommerson III
Posted on November 13, 2018 at 5:32 pm
Mobileye uses deep learning and crowd-sourcing to sense, map, and navigate the road. New ownership under Intel can help provide the processing and connectivity needed to take this technology to the next level, but with data being the driver of [...]
1-800-Flowers And IBM Watson Take On The Future Of Gifting, And The Future Of Relationships
Rose S.
Last modified on November 13, 2018 at 4:39 pm
How will machine learning impact gifting as a retail business? 1-800-Flowers is partnering with Watson to innovate their customer experience.
Bracing for impact: the additive effect of Invisalign on manufacturing
Brian Westlake
Last modified on November 12, 2018 at 11:12 pm
Align Technology (AT) is a manufacturer of 3D digital scanners and clear aligners (marketed through the brand ‘Invisalign’) used in orthodontics. AT is perhaps the most prolific user of an additive manufacturing (AM) process called stereolithography that converts liquid materials [...]
Flipkart: Using Machine Learning to solve unique problems in Indian E-commerce
SAML2020
Posted on November 13, 2018 at 2:02 pm
Home addresses in India pose a uniquely Indian problem- lack of standardization. This poses a challenge to e-commerce players whose success relies on efficiencies in last-mile logistics. This post talks about how Flipkart, an Indian e-commerce major is using Machine [...]
It’s all open at Wikimedia Foundation
LoremIpsum
Last modified on November 13, 2018 at 7:21 pm
“Imagine a world in which every single human being can freely share in the sum of all knowledge.”
Closed Innovation at Facebook
Sgt. Piggy
Last modified on November 14, 2018 at 12:31 am
In 2010, Facebook introduced the “Open Graph”. In Mark Zuckerberg’s own words: “Today the web exists mostly as a series of unstructured links between pages. This has been a powerful model, but it’s really just the start. The Open Graph [...]
Juul Labs: Transforming Vaping through Open Innovation
IloveML
Posted on November 12, 2018 at 3:48 pm
In greater public scrutiny and regulation risk, Juul needs to use Open Innovation to create healthier and safer vapor products.
GE Digital: Can Machine Learning Be the Key to Turning GE Around?
John Doe
Posted on November 13, 2018 at 10:11 pm
In 2011, General Electric (GE) made a big bet on machine learning and AI with the creation of what would become GE Digital. In a time of great flux at GE, will Digital survive? What will be its role be [...]
When Chanel trades sewing machines for 3D printers
Rim Bensouda
Posted on November 13, 2018 at 7:53 pm
Can you imagine a future where you could download a suit design from your favorite brand and immediately print in at home?
Great Scott! What’s next for open innovation at LEGO?
HK
Posted on November 13, 2018 at 7:11 pm
LEGO has been using open innovation for the past 10 years to bring new playsets to market. As they strive to stay relevant while the line between toys and consumer electronics starts to blur, how will they revamp their strategy [...]
Is Gucci’s Fad Shopper Dilemma a Predictive Analytics Opportunity?
Jayne Mathias
Posted on November 12, 2018 at 11:51 pm
Gucci's runaway growth has largely stemmed from first-time, millennial customers – a notoriously fickle client demographic with little brand loyalty and tall customer experience demands. Will Gucci's hesitance to deploy machine learning be what proves it a fad, rather than [...]
WeWork: Machine Learning meets Real Estate
lee3
Posted on November 13, 2018 at 2:58 pm
Machine Learning + Real Estate = An Optimal Workplace Solution.
Beyond Bureaucracy: Open Innovation in the U.S. Government
hbs_tom_rc
Posted on November 13, 2018 at 5:58 pm
Could open innovation initiatives allow U.S. governmental agencies to tackle intractable problems more quickly and cost effectively? Could the U.S. government effectively transition to open platforms to address its most contentious and politicized challenges?
Roche: Machine Learning Brings a Big Pharma Business Model Under Siege
hbs_2020_student
Posted on November 13, 2018 at 7:41 pm
Roche, the Swiss pharmaceuticals giant, is caught in a race against time. After making a big bet on breakthrough drugs and personalized medicine, the company has spent much of the last 18 months thinking ahead to the challenges that machine [...]
Is the Navy’s Additive Manufacturing Strategy Bold Enough?
Devin
Posted on November 13, 2018 at 1:09 pm
The line between disorder and order lies in logistics… - Sun Tzu
From the #1 CRM to the smartest CRM: How Salesforce is bringing machine learning to the world of sales
JT
Posted on November 10, 2018 at 11:12 am
Salesforce is changing the game of sales again with its predictive intelligence system "Einstein" that helps to boost the efficiency and efficacy of sales representatives. Learn how the company is innovating on this front and applying machine learning solutions to [...]
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