Banana Bread

  • Student

Activity Feed

Wow sorry, I didn’t mean for this comment to turn into a mini-essay. Apparently I am very passionate about the MBTA 😛

Thanks for a well-written, engaging article! I was living in Boston during the 2015 record-setting snowfall, and while I’m sure many of us would have been happy without a snowpocalypse, it’s great that the MBTA used the negative impacts of it as impetus to launch its open innovation platform. So many people take public transportation every day that I think this platform has huge potential to crowdsource a greater numbers of fantastic ideas from a wide base of consumers. In mind, what’s missing here is appropriate incentives. To encourage submissions beyond from for-profit entities, I would recommend the MBTA consider running its open innovation platform in a drastically different way.

One idea: Instead of an ongoing portal for submissions, the MBTA could host limited time contests. People are moved to action when they see specific deadlines; otherwise, they may lack the urgency to act. Each of these contests should have a specific prompt to spur people’s brainstorming, and each contest should also offer a small prize. I understand the MBTA may not be able to afford a big cash prize, but in my experience running promotions/contests at my previous job, people are motivated by the excitement of the contest and being recognized for their win and less by the actual prize. Running these contests less frequently would also help the MBTA save the time and time-related costs associated with reviewing proposals constantly. Instead, they could designate this contest to happen in months where they could get temporary labor to help run the process and review entries, such as over the summer.

I would hesitate to recommend running an open, collaborative platform; this requires a lot of monitoring and facilitation in order to make the experience a great one that people would want to engage in. Based on your article, it sounds like the MBTA is short on people resources/time so this doesn’t feel feasible.

Lastly – both of your questions were around how the MBTA should move forward with its open innovation platform. I would like to pose a question back to you – do you think they *should* continue running it? Do you feel they are getting the return from the time and money they put into running the platform? While it’s encouraging that 111 individuals/organizations care enough to submit something, how much extra effort and resourcing would it take to drastically increase this number? Additionally, you mentioned the MBTA has implemented only 3 of these ideas; I would be curious to know what the return on these ideas has been for the MBTA. Were these truly novel ideas that encourage the MBTA to continue believing in the power of crowdsourcing? Open innovation is not for everyone. While it can be great for cash-strapped organizations in some ways, building and fostering an engaging platform may actually end up being more work and money than the benefit it brings to your organization.

On November 15, 2018, Banana Bread commented on Modern Meadow: Using Additive Manufacturing to Reimagine Fashion and Food :

Super cool topic!

I’m having trouble visualizing what ‘inputs’ you feed the 3D printer to engineer tissues and organs like you mention. It’s so beyond the scope of my understanding and imagination, which is what made this article topic so intriguing!

I’ll comment on your second question: I think it would take a HUGE shift in mindset for consumers to become open to eating biofabricated foods. It sounds like the major benefit to eating biofabricated foods is environmentally motivated (i.e., saving the planet). Without a differentiable taste or cost (in fact, I would imagine it would be less tasty and more expensive relative to farmed food, at least at first), consumers will be hesitant to buy and try. Additionally, consumers already have a way to consume ethically (both in terms of being environmentally responsible and avoiding animal abuse) by consuming foods that are organically grown and free-range, as well as being a vegetarian. Current trends in the food industry like “farm to table” and “made from scratch” are here to stay at least for a while longer, so I would guess that consumers will view biofabricated foods as “fake” and “unhealthy.”

That being said, there IS a population out there who will be early adopters. I point to Soylent, the meal replacer, as an encouraging signal that people may be willing to try out novel “foods” that bring you adequate nutritional value even though seemingly strange at first. [1]


On November 15, 2018, Banana Bread commented on Betabrand: Too Much Open Innovation? :

Really enjoyed this, Aparna! I actually just walked by the San Francisco BetaBrand store this past summer, and have been intrigued by the concept since hearing about it.

I appreciate your skepticism around BetaBrand’s success, especially given it can be seen as “trendy” for the moment and may not hold long-term appeal and viability. However, I actually don’t agree that the companies you mentioned, Threadless and Adidas, are competitors, so also don’t buy the argument that open innovation in clothing is becoming widespread (at least not the way BetaBrand is pursuing it). BetaBrand is for the fashion-forward and fashion-conscious, and part of the appeal is in it being “special” and rare. My understanding of Threadless (mostly just t-shirts) and Adidas (athletic/athleisure) is that these are mass consumer brands. BetaBrand can capture and keep a more specific and selective portion of the market that wouldn’t be lured away by Threadless or Adidas products; I believe these consumers wouldn’t even be considering a decision to spend their dollars there. The downside is that this market can be quite small; the upside is they could choose to continue playing at higher price points (and I believe they should!) so they can make up for small volumes.

The real question for me is whether this is sustainable beyond the early adopters. It sounds like BetaBrand has been successful in attracting many early adopters who buy into this open innovation model, but I’m curious to what extent other consumers will be interested in trying this out. I don’t believe Betabrand should increase its brick & mortar presence, since the open innovation process can all happen online and also since I’m not sure the capital investment for more in-person stores would pay off. I’m intrigued by your idea of how they could make this “hybrid” retailer model work; it seems to me that once they incorporate more “traditional” retail and start appealing to mass consumers, they may be well on their way to losing their competitive advantage.

First off – as a pretty frequent flyer, I really enjoyed reading about machine learning + JetBlue; you know your audience ;-).

While I agree that implementation of initiatives/products driven by machine learning will be challenging, due to the competitive environment, I’m not sure I agree with your hypothesis that the root of the challenge is based on inadequate infrastructure and distribution channels. I may be misunderstanding your wording, but to my understanding, airlines can sell an intelligent, individualized ticket-buying experience like you showed in exhibits 1 and 2 using their existing websites, and possibly even on platforms like Kayak or Priceline. What, in your opinion, is particularly challenging about the existing infrastructure/distribution channels? Did you have something else in mind besides what I listed?

I would venture to guess that Jetblue’s (and other airlines’) biggest challenge with rolling out an initiative, product, or process driven by machine learning is the difficulty of gathering (and using) consumer data. For this to be actually impactful, it would require consumers to opt in to their data being shared (or, if it’s already being shared, then it would require social approval by the consumer for the company to use it without being shamed). As a consumer, it makes me uneasy that airlines could use data about me to offer individualized offerings, because I would be skeptical and assume they are using their algorithms to upsell me or overcharge me unnecessarily. It feels more appealing to me to be offered a predetermined set of choices (i.e., 4 different ticket fares with different associated products/services like you show in exhibit 1), but NOT individualized offerings. I would forgo a personalized airline ticket shopping experience to protect my data.

On November 15, 2018, Banana Bread commented on Building a Better Future – 3D Printed Housing at WinSun :

Wow. I am in awe of the way WinSun is using 3D printing to build houses! I never could have imagined a printer could create something as sturdy and large as a house. I’m having trouble imagining what a 500-feet printer looks like. I love how you outline 2 country and culture-specific major issues WinSun could help address: pollution and corruption. There is a clear need and impact for this product/process.

To achieve broad impact, I agree with you that the manufacturing process must be made more efficient and cheap. In terms of how, I would suggest looking at other players who have been successful. Cazza has developed technology to automate its own construction processes, and has made their machines more portable (which they say is their differentiator) [1]. Even if WinSun invested in making their PROCESS more efficient/cheaper, this will be all for naught if their shipping costs are extremely high. Therefore, in my eyes it’s essential that WinSun prioritizing making their machine and process compatible with portability, especially as they consider expanding all around the globe.

As for your second question, I think WinSun’s ability to capture a new market will depend on how they can meet consumer preferences in various geographies around the globe. Thus far, from your article, it sounds like the only material they use is concrete, which may not meet the preferences of consumers or companies building homes in various places. Additionally, I worry how many new designs, molds, etc. WinSun would have to make to meet different tastes, preferences, and demands, and wonder how difficult this would be. Given the machine is 500 feet long, I have no idea how flexible it is; if there are not several flexible settings, I could see it being hugely capital-intensive to invest in building too many different styles of homes. To me, that begs the question of whether they should focus initially on the Chinese market while they hone their product + processes, or if they should continue with their ambitious global growth goals.


On November 15, 2018, Banana Bread commented on VIPKID: Machine Learning in Online Education :

Coming from another Education Tech start-up prior to HBS (more focused on K-12 though), I loved reading about VIPKID and its mission to revolutionize learning. My start-up similarly had a sales/services-heavy business model, especially as we scaled. While I’m fascinated by applying machine learning to personalized learning, I’m especially intrigued by the idea to use machine learning to help sales/customer success teams serve customers even better. I know there was a lot of manual, tedious work required by our staff in order to provide the best customer experience possible, and machine learning could help innovate ways of working within the company.

To answer your question, I strongly believe machines/robots will never (and should never) replace teachers. The teacher’s role in a classroom is not just a content/knowledge deliverer; if this were the case, they would definitely be replaceable with AI! The best teachers we saw using our product were amazing at facilitating learning, challenging students’, and mentoring them using personal relationships. This could never be replicated by a machine as it requires empathy and a very human approach. However, I think this argument only holds for really exceptional teachers. For the ones who are just mediocre, or even bad-quality, I’m wondering if they can easily be replaced. I thought of a question off of your question: Is it possible that schools that are under-resourced and with lower-performing teachers (those don’t always happen simultaneously, but they can) will be more likely to get their teachers replaced with machines, while this doesn’t happen on the other end of the spectrum? While this revolution in machine learning in education has the potential to decrease inequities and even the playing field, I also worry that it can further the divide.

Great article, and really thought-provoking topics. Great job!