Kariba Voy's Profile

With regards to the first question it seems FBN will continue to build farmer trust — and therefore scale their crowd-sourced data further — by maintaining their commitment to their core value of putting farmers first (https://www.fbn.com/about#farmer-experience). Their commitment to this value drives internal company decisions from seed pricing to launching new business lines e.g. crop marketing. Where they may be put in a position to think more deeply about what farmers first really means is when they may choose to diversify their revenue streams in the future. As a growing business they may face choices along the lines of whether to provide data to suppliers and manufacturers further upstream. While this could provide revenue opportunities for them they’d also need to balance their commitment to maintaining farmer trust.

In terms of question two — FBN currently provides farmers with relevant data but they do not provide recommendations to the farmer based on this data. In addition to data transparency, FBN is also committed to providing unbiased and independent information to farmers. FBN will need to weigh the incremental benefit to farmers by providing them prescriptive recommendations against the cost of any perceived bias or loss of independence (based on an interview with an FBN employee).

Thanks for sharing!

This is a very interesting way of getting around the traditional inputs for determining the riskiness of a loan recipient. As noted in the piece above, the traditional inputs don’t tend to be effective in this region. Specifically, the fact that this system uses customer behavioral patterns to discern whether someone may default is very thought provoking. They gave online activity as an example of behavior that would be used by the algorithm. I wouldn’t have expected someone’s browsing history to be a reliable indicator of whether they could be trusted with a loan. Of course there are certain activities (searching “How can I get away with not paying back a loan?” for example) that would give some insight into this directly, but for majority of online activity I hadn’t realized there would be a direct-enough/meaningful link. Though of course they are pulling this along with other inputs such as personal loan history so perhaps once all these entities are packaged together it tells a more thorough story. If people start to learn what inputs the company is using I wouldn’t be surprised if they became very cognizant of what information they are allowing it to get hold of/how they change their behavior in order to seem like as good a candidate as they can.

To provide a thought on your second question — I think a market that will be very happy with this made-to-order, good quality shoe are people with different sized feet! While most people have feet of slightly different sizes (see sources such as [1] and [2]) for some it’s more significant than others either because the size difference is large or because they play a sport where fitting into your shoes/boots perfectly is important for performance (even at college level for example). Most people just end up buying a size to fit the larger of their feet (though a small minority have to go to the extent of buying two different pairs of shoes [1]). If these folks had the option to buy one pair of shoes that fits both feet well I imagine they’d be very happy, and become repeat buyers. While it may not be a daily pain point that people contemplate, reminding these folks of their different sized feet and providing this exciting solution could be an unusual and untapped market!

Sources:
[1] https://corewalking.com/one-foot-bigger/
[2] https://www.indiatimes.com/health/healthyliving/are-your-feet-two-different-sizes-242389.html

I’ve been keeping an eye on this exciting use of 3D printing for a little while as it’s got the potential to change home-building as we know it. I do find it interesting that companies like Contour Crafting or another I’ve been following called ICON (https://www.theverge.com/2018/3/12/17101856/3d-printed-housing-icon-shelter-housing-crisis) both look to building in space when there’s so much need for housing right here on earth. It makes sense that companies should have big aspirations and think big… as long as it doesn’t distract them from all the incredible opportunities they have in front of them right here. Being from Africa my mind quickly starts wondering how and when technological jumps like these will be available in areas with particularly dire need. One company that’s thinking a lot about this — to the extent of building the homes out of mud instead of concrete — is an Italian company called Wasp (https://www.iflscience.com/technology/3d-printer-uses-mud-natural-fibers-make-homes-impoverished-areas/). Mud and natural fibers are likely available in developing areas, cutting costs and making the homes even more affordable to build. All these companies can make a big difference! It’ll be exciting to see where this goes.

Reading this piece I found it interesting to reflect on which types of problems are best solved through innovation and which are not. Or, perhaps rather, what ways of employing open innovation would save NASA more R&D costs compared to others. For example, when it was posed that open innovation could be used to source novel ideas I agreed that this would be a great use of crowdsourcing. However, I don’t think this would save NASA a large amount of R&D costs because crowdsourcing ideas is replacing the “brainstorming” phase of a project which, at least in my experience, costs less than researching and developing that idea. A use of crowdsourcing mentioned in this essay that would on the other hand save a lot of R&D time is the example of looking for movement against a motionless background. As stated in this reference (https://consumervaluecreation.com/2018/02/12/nasa-crowdsourcing-the-universe/) this saved NASA a lot of time, and therefore, money. So it appears not all crowdsourcing opportunities are created equal and some will save NASA more money than others. While gaining novel ideas from space enthusiasts would broaden the ideation funnel, if they end up needing to select some use-cases over others, the R&D cost saving spectrum will likely be a useful gauge to use.

For Quirky, crowdsourcing product ideas did in some instances result in a successful product in the market. For example Quirky’s “Pivot Power Outlet”(https://www.amazon.com/Quirky-Pivot-Outlet-Flexible-Protector/dp/B004ZP74UA) came out in 2010 (https://www.businessinsider.com/quirky-reborn-new-ownership-business-model-2017-9) and (at least this version) has in aggregate an almost perfect rating from over 950 customers as well as being named one of “Amazon’s choice” products. So while in this case the process of crowdsourcing to product launch was a successful one, it seems Quirky’s downfall was in missing the step of product-market fit or effectively assessing demand for that product before developing it further. Perhaps they did do research but it wasn’t rigorous enough, they used the wrong customer segment to test on, or they fell in to the trap of conformation bias. Either way, better demand-side research would likely have helped prevent the high inventory costs that were mentioned in this essay — costs that they incurred when products didn’t move at partner retailers like Target and Bed Bath & Beyond.