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 noteFor 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)

Grupo Aval: Utilizing open innovation to build a new business model
Ignacio L
Last modified on November 13, 2018 at 7:14 pm
Grupo Aval, the largest financial group of Colombia, is using open innovation to counter emerging fintech competition.
Equipping the Revolution: Hardware Wars in the Age of Machine Learning
John Keck
Last modified on November 12, 2018 at 5:11 pm
In the machine learning gold rush, Amazon, Google, and Microsoft are competing for cloud computation dominance. Currently second in the market, Microsoft is poised to gain significant market share through its major investment in FPGAs (field-programmable gate arrays) for advanced, [...]
Deep Genomics – can a machine learning start-up accelerate drug development?
Posted on November 12, 2018 at 9:52 pm
Today, it costs billions of dollars and many years to commercialize a novel drug. Can Deep Genomics leverage machine learning to reduce these cost and time requirements?
It’s all up from here! Machine Learning & Predictive Maintenance in Elevator Service
Posted on November 13, 2018 at 2:25 pm
ThyssenKrupp’s MAX is on the rise
Open Innovation at the Bank of Canada
Last modified on November 12, 2018 at 10:27 pm
The Bank of Canada's implementation of open innovation through PIVOT.
Rio Tinto – Mining Data like Diamond
Posted on November 12, 2018 at 8:16 pm
When surviving competitively afloat the mining industry’s ocean of high and low tides seemed impossible, Rio Tinto leveraged Big Data and Machine Learning to revolutionize the mining industry over the past decade, through its state-of-the-art autonomous operations.
JP Morgan COIN: A Bank’s Side Project Spells Disruption for the Legal Industry
Legal ML
Posted on November 13, 2018 at 7:34 pm
JPMorgan has begun to automate the work of its law firms using machine learning. It'll save time and money, but the bank shouldn't write off human analysis just yet.
Flotek – Drilling Into The Fracking Data With Machine Learning?
John S.
Posted on November 13, 2018 at 4:40 pm
The management team of Flotek is facing pressure from public market short-sellers and using fracking data to build a new machine learning tool that helps differentiate its specialty chemicals product in the marketplace.
To Infinity and Beyond – 3D Printing in Space
Buzz Lightyear
Posted on November 13, 2018 at 12:59 am
They say it is not about the destination, but about the journey. What if that journey is designed to last forever?
The Unilever Foundry – bringing innovation to 400 brands, under one roof
Posted on November 13, 2018 at 1:08 pm
Can a 90-year old company learn to behave like a start-up? Slow growth, ever-changing consumer tastes and the rise of digitally native upstarts are threatening the traditional consumer-packaged goods industry. Unilever’s significant investment in open innovation intends to challenge this [...]
How can ML help Fox predict box office performance?
Miguel Dysenhaus
Last modified on November 12, 2018 at 5:06 pm
Fox is introducing machine learning to try to estimate box office performance and make business decisions on their movies. Can an algorithm understand something as subjective as whether movie goers enjoy a film?
Valve using machine learning and deep learning to catch cheaters on CS:GO (794 words)
Last modified on November 13, 2018 at 5:19 pm
CS:GO is one of the most popular and competitive video games worldwide. In the past few years, reports of players using "hacks" in the game were increasing, negatively impacting customer satisfaction of CS:GO's user base. To counter this rampant cheating, [...]
Spotify is better at picking your music than you are, but will they always be the best?
Posted on November 14, 2018 at 6:11 am
Machine learning at Spotify is a source of product differentiation in the music streaming industry.
For Boeing, not even the sky is the limit for 3D printing.
Raleigh Werner
Last modified on November 13, 2018 at 1:27 pm
As Boeing invests more heavily in additive manufacturing for its satellite business, will customers accept uncertainty around the long-term reliability of 3D-printed components?
3D Printing the Future of Rail at Deutsche Bahn
Posted on November 13, 2018 at 4:59 pm
Deutsche Bahn is investing heavily in additive manufacturing. How can they best incorporate this technology into their future supply chain?
Dangerous Innovation – Defense Distributed and the Democratization of Weapons Manufacturing
Edmond Dantes
Posted on November 13, 2018 at 6:44 am
Additive manufacturing shows tremendous potential for commercial and humanitarian applications, but it also presents ethical questions and the potential for unintended consequences. 
A Better Brain: Machine Learning in Guided Meditation
Keagan Pang
Posted on November 12, 2018 at 8:34 pm
Meditation, with its many mental benefits, has remained an elusive skill to master. While there has been a surge in the number of guided meditation mobile apps available, none offer any real insight to the most common question that beginner [...]
The democratization of energy: How machine learning is empowering both the consumer and the utility
Rocco Puno
Posted on November 13, 2018 at 7:54 pm
The advent of technological advancements in the power industry is fundamentally changing how we produce and consume electricity, improving grid management as well enabling the creation of new business models: Enel Green Power ('Enel') is at the forefront of this [...]
Siemens Mobility going digital
Posted on November 13, 2018 at 3:19 pm
Additive manufacturing is threatening to change the competitive landscape of the multi-billion dollar spare part market. Will current players be able to embrace 3D printing as a new opportunity, or are new competitors set to outcompete traditional manufacturers?
Artificial Intelligence Could Become Your Surgeon’s Best Friend: Why Should You Care?
Aditya V. Karhade
Last modified on November 15, 2018 at 6:31 pm
Machine learning can improve the quality of surgical care while reducing the cost - how is this possible and what should you expect in the next decade?
Using Machine Learning for Crime Prediction
Amina E
Posted on November 13, 2018 at 7:19 pm
Police departments are increasingly using predictive algorithms to determine "hot spot" potential crime areas.
SenseTime and Public Safety
Toni Campbell
Last modified on November 14, 2018 at 9:38 pm
Cities and countries already have begun to deploy AI and ML technologies for public safety and security. On one hand machine learning applications in image and video recognition can help law enforcement officials in detecting criminal activities and efficiently prevent [...]
Is SigTuple positioned to disrupt medical diagnostic space in India: Can Data become Doctor?
Posted on November 13, 2018 at 5:40 pm
With AI and machine learning overtaking every facet of millennial industry revolution, Healthcare AI application has far-reaching potential. With advances in image recognition, improvement in robotics, Medical startups are revolutionizing the diagnostic space but are we ready for such a [...]
WinSun – Print into the Future
Posted on November 12, 2018 at 7:21 pm
Can we build future cities like building LEGO Land?
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