I see this as a fascinating article but difficult to scale to the point where it would be able to shift the needle on the overall efficiency of food production. The model (which, as mentioned in some of the source article) includes manual planting is labour-intensive and requires high initial capex investment. The point at which ‘green’ greenhouse farming is economical compared to making conventional farming greener is in a marginal number of cases near cities.
More worryingly, it cannibalises the markets in big cities where people are most likely to put a premium on buying organic/ethically-sourced/environmentally friendly. This scale on the consumer demand side could be what is needed to shift mass producers to go to more environmentally-friendly production options.
This was a very interesting paper, Sam, that makes a lot of great points – but I take some issue with one of the proposed solutions: the suggestion that the ‘FDA enact policies to force companies to geographically diversify the locations of their production facilities, particularly for products that are life-saving and have no substitutes’.
Given the power of the pharma lobby, such a costly measure would be difficult to implement – and given the nature of the current supply chains for pharma companies, would take years to enact. But the main reason for my oppositions stems from the fact that the proposal would drive up the every day prices of drugs for consumers by requiring more expensive geographically diverse supply chains and would lead to worse outcomes for the majority of the consumers. Every dollar of incremental price passed on to consumers or insurers correlates to worse health outcomes – that is certain, while disaster frequency is fundamentally uncertain.
Instead the government should prepare better for emergency situations rather than passing that burden to private companies. For example the government could have stores of medicine that can be deployed in emergency situations or they could have an emergency factory with capacity to devote to drug production if a major facility is taken offline. This would seem to be a way to mitigate the risks of the problem with fewer of the downsides.
Thanks for the article outlining an interesting example of protectionism. The biggest way this plays out for most global companies is in China – they have the unique distinction of being one of the world’s biggest markets but the one that is mostly likely to disguise protectionism as ‘necessary censorship’ – and has victims from Netflix to Facebook to small-scale chat apps.
For Netflix, it had to sign a deal with iQiyi to gain any distribution foothold in China (see source below). The government-imposed delay and this insufficiencies of the iQiyi solution has given competitors and free alternatives to Netflix in China their chance to develop so that Netflix/iQiyi will not have the same potential as if they were able to enter earlier and uninhibited. The second-order consequence is a growing divergence between the compatability of technology ecosystems coming out of China and America – such as the Ali and Amazon ecosystems – and as globalisation will eventually lead to their collision, this divergence will be an interesting trend to watch.
Source: Jing, M. Netflix, South China Morning Post, Netflix extends its global reach to China – but not on its own terms, 26 April, 2017 accessed at http://www.scmp.com/tech/china-tech/article/2090853/netflix-extends-its-global-reach-china-not-its-own-terms on 12/01/2017
This is an interesting take on the implications of Brexit. My perspective is that Deutsche should worry about taking actions prematurely when there are available options to ‘hedge’ risk until the type of Brexit that will occur become clearer. As the above comment points out, the worst case scenario is they act in preparation for a hard Brexit but a soft Brexit occurs. Instead, Deutsche has strategic options that let it hedge risk until the situation becomes clearer. For example it can make trades to reduce currency fluctuation risk and begin improving its recruitment/talent pipeline in Germany. But taking irreversible steps before it becomes clear if there is a hard or soft Brexit coming from the UK Government could lead to the company to be vulnerable.
I think the last question you raise is critical: legal accountability. Jasmyn’s comment correctly identifies some follow-on questions from identifying some of these concerns. My perspective on the second-order effects of this transformation begins from the premise that medicine is different to producing widgets in a factory; any ‘failure rate’ or ‘quality control’ issue in the process is unacceptable and needs to be eliminated, rather than being something that can be acceptably priced in to the cost of doing business.
Once the failure rate of these diagnostic tools have been established, the likely outcome is that hospitals will use their asymmetric power over patients to inform them about this failure rate and make them waive liability for the risks of this type of diagnosis – and accept that failure rate as the norm, rather than investing more and more to get diminishing returns on decreasing the failure rate.
Great article, Jordan.
One thought I would offer is around how mass transit (buses, trams, etc.) will be disrupted by this shift to driverless technology. At the moment the private sector is unwilling to take on mass transit because of high costs and the fact that governments have taken the niche of cross-subsidising these costs as transport, even along unprofitable routes, is a public good.
As driverless technology and big data enables better route planning and more cost-effective vehicles, there would be an opportunity for companies or the government to act as an insurgent by applying these technologies to mass transit. Big data and driverless cars could see perfect synching of demand for travel along most routes with a technology that diffuses cost over more users, challenging the private transport model that is developing in the first generation of driverless vehicles.
Thanks for your post about Lazada, one of the most interesting businesses in South-east Asia. I worked there over the last year and was involved in the strategic preparation for Amazon’s arrival. I believe this is a battle Lazada will win (and at worst, Alibaba – now 2 billion deep into Lazada and running out of parts of the world in which to reach its next billion customers – will not allow Lazada to lose).
The article is perfectly correct in it’s argumentation but wrong in the framing of its implications as it overstates the strategic importance of Amazon’s technology advantage in areas like anticipatory shipping as determinative in the outcome of the fight between the two companies. The article is premised on an example from Singapore having Prime Now while in reality Singapore is unique in South-East Asia; a tiny, well-developed city-state and the only part of the region with a sophisticated logistics infrastructure make it possible to launch Prime Now there. For the rest of the key countries in the region (Indonesia, Malaysia, Philippines, Thailand and Vietnam, where 90%+ of GMV typically comes from), the challenges of building a logistics business are many years behind a state where anticipatory shipping would shift the needle on results – especially in a low-cost labour environment. Lazada often had to develop logistics networks entirely from scratch as most parts of the region were so underserved. Developing warehouses and an entirely fresh logistics capability (including in two nations that are almost entirely islands) will require years of investment and hard work on the part of Amazon – while Lazada is using those years to increase its technological capability or leverage Alibaba’s.
In those first years the real challenges will come down to Amazon’s ability to match the existing network effect that Lazada has (in terms of having the largest variety and best prices for consumers), developing basic logistics infrastructure to cover the region and essentially a spending contest in commerical and marketing to win a dedicated customer base. Amazon is a Goliath of an organisation but is starting significantly behind a strongly-backed David.