Extremely interesting look in a high-barrier industry, thank you. I was particularly intrigued by manufacturers’ use of offshoring to combat supply chain isolationism–this response is not intuitive, and mirrors a similar trend seen in a few other sectors like cloud computing. Given the possibility of protectionist tariffs in countries with nascent domestic aircraft producers, it seems like diversifying the supply chain is inherently risky–what if China imposes those tariffs tomorrow to protect its industry? On top of that such diversification leads to a risky and complex supply chain that is harder to manage and subject to more individual jurisdictions. However, I agree with you that there seems to be no better choice for the time being.
I think the critical next question is what kind of demand Airbus and Boeing are forecasting that those new airline manufacturers will see in the next 10-20 years. Presumably in some countries–like China–there will be incredible incentives to buy the domestically-produced, Chinese-owned airplane. Other countries may not erect such difficult barriers. Either way, a critical piece of this analysis is what impact the airlines expect those new players to have and their competitive responses. How much investment is there in new technologies like electric planes? Or moonshots/outside-the-box ideas like reintroducing supersonic flight? These are not revolutionary ideas, but clearly Airbus and Boeing must differentiate themselves somehow.
Extremely interesting read on how oil companies themselves are responding to climate change. As others wrote, I am a little curious about the motivations–I am willing to concede that motivations may include humanitarian, climate reasons, but I suspect there is a deeper business proposition buried in this data somewhere.
On that note, I would be extremely interested to learn more about the economics of the changes you highlight. You mention a 75% decrease in energy used for heating bitumen, but how does that translate to a dollar or GHG emissions number? What is the overall cost of the changes, eg, in autonomous vehicle technology? I wonder if there is an opportunity there to engage with autonomous vehicle researchers to develop systems tailored to the oil industry’s needs.
More generally, though, at this point it seems that conformism is not only the default option but possibly necessary–public backlash over oil projects continues to grow (eg, recent pipeline demonstrations), and although the US lags in implementation the larger perception battle has already turned against oil companies. I wonder how successful a social media campaign can be in that environment, and if people will find it believable. Regrettably I have no better recommendation.
Very interesting read, thank you!
Fantastic article that educated me on the implications of US isolationism on the smaller players in TPP.
My biggest question, and suggestion for Vietnam, is: why not China? Given the United State’s clear reticence to incentivize pacific countries to align with US interests, surely the Chinese are happy to step into the economic void. I thus suspect, given China’s ever-more-prominent role, that Vietnam could gain some significant trade concessions with China using the resurgent TPP as leverage. I do not know the tradeoffs, but there must be an opportunity to align with China at minimal domestic risk. China has certainly shown a willingness to provide high-quality FDI, and if Vietnam is willing to align itself I suspect that China would be happy to direct investment to Vietnam that it is losing to lower-cost countries anyway (eg, apparel, as the author notes, going to Myanmar).
Wonderful article about a highly innovative company, and I appear to be much more bullish on OpenDoor’s prospects than the other commentators.
First, I do agree with all of the stated caveats–yours and the commentariat’s–and OpenDoor certainly has its challenges. However, I don’t think those concerns are markedly different from a house sold by a traditional owner or agent. Nobody is very good at assessing the market price of a house, and my own experience buying a home suggests that valuations even among well-respected assessors can vary by as much as 3-6% using the same data. I do agree that scalability is a particular challenge, and that they must be careful to learn the nuances of each individual market. However, housing prices vary on fewer variables than many other products, and housing prices are typically fairly predictable over longer periods of time (recent bust excepted). Given that OpenDoor will try to sell its houses quickly, I am not convinced that their own auto-generated valuations will be too divergent from market realities, and they can quickly adjust prices if they are obviously wrong.
I also see a lot of potential in the business model itself. As much as it pains me to jump to blockchain, I can certainly see the potential to turn sales in a matter of a few days whenever governments adopt the technology. Moreover, I could see OpenDoor using its platform not just for the narrow market of single family homes in a certain age/price range, but also expanding to, eg, the luxury apartment rental market. It will be difficult, but they have only just begun to scratch the surface of this business opportunity, and technologies like blockchain could revolutionize the model by cutting out processing time and rendering agents entirely obsolete.
I really appreciated the perspective in this article, particularly because it focused on digital optimization of a supply chain that did not simply jump straight to blockchain as a cure-all.
In the 3M case the most fascinating part of complex supply chain management is the inability to test or see all possible supply chain states. With so many different products, how can 3M tell if it chooses the right suppliers for each? And what if it made Post-Its side by side with paper, or does it make sense to manufacture those with tape? It is not economically or chronologically feasible to test all combinations or optimize all potential supplier combinations and sourcing. Thus the 3M challenge is similar to the New Zealand boat design tradeoff: 3M can intelligently “parachute” into a particular solution and then optimize, but who knows if a more efficient system exists?
The above commentator rightly points out that comparisons to competition are a critical benchmark and perhaps the most important one. A slightly loftier goal is to use machine learning to discover the true drivers of supply chain cost in such a complex system–machine learning and business analytics were invented for this purpose, although I have never heard of them being applied on this scale. I would not be surprised if a thoughtfully designed ML program could discover some substantial cost savings among 3M’s supply and distribution channels–the Post Office and UPS have used similar programs to great success on a network that is more complex but with fewer SKUs.
Very insightful article, and I am extremely intrigued by one theme in particular: why is HEI relying so heavily on third party, private, and individual power generators within the grid?
As you discuss, electricity grids are notoriously difficult to manage. Incorporating so many suppliers, especially rooftop solar panels over which HEI has little control, seems like a strategy that will cause a significant increase in management difficulty and overhead. Individuals can choose to connect or remove their panels at will, and coordinating many corporate suppliers is difficult. You advocate to continue that approach, and I am certainly convinced that they have little choice in a resource-constrained environment like Hawaii. One wonders what impact that may have on reliability and management and whether a buffering system like batteries is sufficient to smooth those variations in supply.
I also wonder how to assess the riskiness of PPAs. Renewable projects have certainly become more viable in the last 10 years, but the industry is still replete with stories of companies going bankrupt or pulling out of certain markets. How does Hawaii mitigate the risk that its PPA partner will remain in business? The cost and time to replace supply is not small.
Overall, I thoroughly enjoyed your analysis and agree with your conclusions. Hawaii is in a difficult position, however, and I hope that they can find ways to address management issues and risk.
This is a great article focused on the printing industry, but I think its implications are far broader: how can companies leverage IoT to create value for consumer goods? Not just for my printer, but also for laundry detergent, orange juice, etc. And second, is HP the right partner to deliver ink? Would, eg, Amazon be a better option?
I personally think that HP is right to adopt this technology. Not only does it give them perfect data about consumers’ printing needs, it also gives them demand information before the demand actually materializes! HP can watch as ink levels dwindle and predict, probably very accurately, exactly when a customer will need a new cartridge. I think that will be the greatest factor in eliminating the bullwhip effect you ask about–in this case, not only does HP have PoS visibility, it has visibility into demand before it even materializes. HP could use that information to pre-stock needed cartridges in strategic locations and really smooth manufacturing and distribution demand over time, eliminating the bullwhip effect.
More generally, I think using IoT to add value to consumer goods is likely to become normal, as everyone has an incentive to participate. Corporations love the idea because, as in the HP case, it gives them perfect information about usage, behavior, etc. and even demand before it materializes, thus reducing distribution complexity, the bullwhip effect, and in turn cost. Companies can then pass some of those savings on to consumers, who would then be incentivized to participate. One could even see advertisements or promotions being pushed through the IoT channel to reduce costs even further.
Of course, there is a privacy tradeoff, and many consumers will be reluctant to allow HP or other companies such intimate access to their data. I think those concerns will diminish over time as the normalization of IoT progresses and cost savings materialize.
Great article with fantastic broader implications!
I am extremely interested to see how transparency and trust technologies like blockchain will influence consumer behavior, and I really enjoyed reading how WalMart is using the tech to remedy important problems.
First, I wonder how this information will be made available to the consumer. For example, let’s say I buy a salad from WalMart. There are likely more than 20 ingredients–am I allowed to see the provenance of each? And trace those supply chains? I suspect that many stores–including WalMart–will be extremely hesitant to share that information, preferring to keep it proprietary to themselves and their supply chains. Publishing supply chain information could potentially give the competition insight that could help to hurt the company.
Second, I wonder whose trust issue we are really solving in using blockchain in this scenario. Do consumers trust WalMart to properly source goods? If so, then the trust question being solved is if the manufacturer (or grower, producer, farmer, etc.) is trustworthy–and I am not sure that blockchain can help that far down the supply chain. At the end of the day, as soon as the blockchain technology must interact with the physical world, trust can be broken–eg, I can swap one crate of oranges for another and switch the barcodes, and you will be none the wiser, regardless of blockchain.
In short, I think there is great potential for blockchain and public ledgers in the food space and WalMart in general. I would caution, though, that companies and consumers need to give the technology a little more thought and decide what level of transparency is appropriate, and whose trust we are truly buying by using blockchain.
Fascinating article covering a topic that we don’t normally see in the context of digital revolutions.
I think a critical dimension of your question is just how far the digital transformation will reach into insurance companies. Can blockchain and its guarantees of property or transaction history eliminate or substantially reduce the underwriting effort required for an average policy? If so, then I think you are correct: the insurance tech startups are likely to claim an ever larger part of the market given their highly democratized usage and low cost structure. If not, it’s anyone’s game.
I further suspect that the future also depends heavily on the type of insurance a company sells. My impression is that consumer insurance (eg health, auto, etc.) is becoming commoditized, especially in the post-GEICO insurance world. A standard-ish contract should be sufficient for nearly any customer, meaning that digital could conceivably cut out the agents, brokers, and underwriters. Medium, large, and enterprise business accounts, however, likely require a degree of specialization and human review that a computer cannot perform–assessing complex risk models, estimating fair values, etc. Thus I suspect that the business and premium ends of the insurance market will not die, as it would be difficult for a machine to make those assessments or arbitrate more complex claims.
Either way, I think we can agree that brokers and agents are exiting quickly as the internet levels the information field. Thank you for the insight into how this industry is changing!