The forthcoming wave of Web 3.0 goes far beyond the initial use case of cryptocurrencies. Through the richness of interactions now possible and the global scope of counter-parties available, Web 3.0 will cryptographically connect data from individuals, corporations and machines, with efficient machine learning algorithms, leading to the rise of fundamentally new markets and associated business models.
The future impact of Web 3.0 makes undeniable sense, but the question remains, which business models will crack the code to provide lasting and sustainable value in today’s economy?
We will dive into native business models that have been and will be enabled by Web 3.0, while first briefly touching upon the quick-forgotten but often arduous journeys leading to the unexpected & unpredictable successful business models that emerged in Web 2.0.
To set the scene anecdotally for Web 2.0’s business model discovery process, let us not forget the journey that Google went through from their launch in 1998 to 2002 before going public in 2004:
After struggling for 4 years, a single small modification to their business model launched Google into orbit to become one of the worlds most valuable companies.
The earliest iterations of online content merely involved the digitisation of existing newspapers and phone books … and yet, we’ve now seen Roma (Alfonso Cuarón) receive 10 Academy Awards Nominations for a movie distributed via the subscription streaming giant Netflix.
Amazon started as an online bookstore that nobody believed could become profitable … and yet, it is now the behemoth of marketplaces covering anything from gardening equipment to healthy food to cloud infrastructure.
Open source software development started off with hobbyists and an idealist view that software should be a freely-accessible common good … and yet, the entire internet runs on open source software today, creating $400b of economic value a year and Github was acquired by Microsoft for $7.5b while Red Hat makes $3.4b in yearly revenues providing services for Linux.
In the early days of Web 2.0, it might have been inconceivable that after massively spending on proprietary infrastructure one could deliver business software via a browser and become economically viable … and yet, today the large majority of B2B businesses run on SaaS models.
It was hard to believe that anyone would be willing to climb into a stranger’s car or rent out their couch to travellers … and yet, Uber and AirBnB have become the largest taxi operator and accommodation providers in the world, without owning any cars or properties.
While Google and Facebook might have gone into hyper-growth early on, they didn’t have a clear plan for revenue generation for the first half of their existence … and yet, the advertising model turned out to fit them almost too well, and they now generate 58% of the global digital advertising revenues ($111B in 2018) which has become the dominant business model of Web 2.0.
Taking a look at Web 3.0 over the past 10 years, initial business models tend not to be repeatable or scalable, or simply try to replicate Web 2.0 models. We are convinced that while there is some scepticism about their viability, the continuous experimentation by some of the smartest builders will lead to incredibly valuable models being built over the coming years.
By exploring both the more established and the more experimental Web 3.0 business models, we aim to understand how some of them will accrue value over the coming years.
Bitcoin came first. Proof of Work coupled with Nakamoto Consensus created the first Byzantine Fault Tolerant & fully open peer to peer network. Its intrinsic business model relies on its native asset: BTC — a provable scarce digital token paid out to miners as block rewards. Others, including Ethereum, Monero and ZCash, have followed down this path, issuing ETH, XMR and ZEC.
These native assets are necessary for the functioning of the network and derive their value from the security they provide: by providing a high enough incentive for honest miners to provide hashing power, the cost for malicious actors to perform an attack grows alongside the price of the native asset, and in turn, the added security drives further demand for the currency, further increasing its price and value. The value accrued in these native assets has been analysed & quantified at length.
Some of the earliest companies that formed around crypto networks had a single mission: make their respective networks more successful & valuable. Their resultant business model can be condensed to “increase their native asset treasury; build the ecosystem”. Blockstream, acting as one of the largest maintainers of Bitcoin Core, relies on creating value from its balance sheet of BTC. Equally, ConsenSys has grown to a thousand employees building critical infrastructure for the Ethereum ecosystem, with the purpose of increasing the value of the ETH it holds.
While this perfectly aligns the companies with the networks, the model is hard to replicate beyond the first handful of companies: amassing a meaningful enough balance of native assets becomes impossible after a while … and the blood, toil, tears and sweat of launching & sustaining a company cannot be justified without a large enough stake for exponential returns. As an illustration, it wouldn’t be rational for any business other than a central bank — i.e. a US remittance provider — to base their business purely on holding large sums of USD while working on making the US economy more successful.
The subsequent generation of business models focused on building the financial infrastructure for these native assets: exchanges, custodians & derivatives providers. They were all built with a simple business objective — providing services for users interested in speculating on these volatile assets. While the likes of Coinbase, Bitstamp & Bitmex have grown into billion-dollar companies, they do not have a fully monopolistic nature: they provide convenience & enhance the value of their underlying networks. The open & permissionless nature of the underlying networks makes it impossible for companies to lock in a monopolistic position by virtue of providing “exclusive access”, but their liquidity and brands provide defensible moats over time.
With The Rise of the Token Sale, a new wave of projects in the blockchain space based their business models on payment tokens within networks: often creating two sided marketplaces, and enforcing the use of a native token for any payments made. The assumptions are that as the network’s economy would grow, the demand for the limited native payment token would increase, which would lead to an increase in value of the token. While the value accrual of such a token model is debated, the increased friction for the user is clear — what could have been paid in ETH or DAI, now requires additional exchanges on both sides of a transaction. While this model was widely used during the 2017 token mania, its friction-inducing characteristics have rapidly removed it from the forefront of development over the past 9 months.
Revenue generating communities, companies and projects with a token might not always be able to pass the profits on to the token holders in a direct manner. A model that garnered a lot of interest as one of the characteristics of the Binance (BNB) and MakerDAO (MKR) tokens was the idea of buybacks / token burns. As revenues flow into the project (from trading fees for Binance and from stability fees for MakerDAO), native tokens are bought back from the public market and burned, resulting in a decrease of the supply of tokens, which should lead to an increase in price. It’s worth exploring Arjun Balaji’s evaluation (The Block), in which he argues the Binance token burning mechanism doesn’t actually result in the equivalent of an equity buyback: as there are no dividends paid out at all, the “earning per token” remains at $0.
One of the business models for crypto-networks that we are seeing ‘hold water’ is the work token: a model that focuses exclusively on the revenue generating supply side of a network in order to reduce friction for users. Some good examples include Augur’s REP and Keep Network’s KEEP tokens. A work token model operates similarly to classic taxi medallions, as it requires service providers to stake / bond a certain amount of native tokens in exchange for the right to provide profitable work to the network. One of the most powerful aspects of the work token model is the ability to incentivise actors with both carrot (rewards for the work) & stick (stake that can be slashed). Beyond providing security to the network by incentivising the service providers to execute honest work (as they have locked skin in the game denominated in the work token), they can also be evaluated by predictable future cash-flows to the collective of service providers (we have previously explored the benefits and valuation methods for such tokens in this blog). In brief, such tokens should be valued based of the future expected cash flows attributable to all the service providers in the network, which can be modelled out based on assumptions on pricing and usage of the network.
A wide array of other models are being explored and worth touching upon:
With this wealth of new business models arising and being explored, it becomes clear that while there is still room for traditional venture capital, the role of the investor and of capital itself is evolving. The capital itself morphs into a native asset within the network which has a specific role to fulfil. From passive network participation to bootstrap networks post financial investment (e.g. computational work or liquidity provision) to direct injections of subjective work into the networks (e.g. governance or CDP risk evaluation), investors will have to reposition themselves for this new organisational mode driven by trust minimised decentralised networks.
When looking back, we realise Web 1.0 & Web 2.0 took exhaustive experimentation to find the appropriate business models, which have created the tech titans of today. We are not ignoring the fact that Web 3.0 will have to go on an equally arduous journey of iterations, but once we find adequate business models, they will be incredibly powerful: in trust minimised settings, both individuals and enterprises will be enabled to interact on a whole new scale without relying on rent-seeking intermediaries.
Today we see 1000s of incredibly talented teams pushing forward implementations of some of these models or discovering completely new viable business models. As the models might not fit the traditional frameworks, investors might have to adapt by taking on new roles and provide work and capital (a journey we have already started at Fabric Ventures), but as long as we can see predictable and rational value accrual, it makes sense to double down, as every day the execution risk is getting smaller and smaller
Source : https://medium.com/fabric-ventures/which-new-business-models-will-be-unleashed-by-web-3-0-4e67c17dbd10
In the aftermath of the 2001 internet bubble, Carlota Perez published her influential book Technological Revolutions and Financial Capital. This seminal work provides a framework for how new technologies create both opportunity and turmoil in society. I originally learned about Perez’s work through venture capitalist Fred Wilson, who credits it as a key intellectual underpinning of his investment theses.
In the wake of the 2018 ICO bubble and with the purported potential of blockchain, many people have drawn parallels to the 2001 bubble. I recently reread Perez’s work to think through if there are any lessons for the world of blockchain, and to understand the parallels and differences between then and now. As Mark Twain may or may not have said, “History doesn’t repeat itself, but it does rhyme.”
In Technological Revolutions and Financial Capital, Carlota Perez analyzes five “surges of development” that have occurred over the last 250 years, each through the diffusion of a new technology and associated way of doing business. These surges are still household names hundreds of years later: the Industrial Revolution, the railway boom, the age of steel, the age of mass production and, of course, the information age. Each one created a burst of development, new ways of doing business, and generated a new class of successful entrepreneurs (from Carnegie to Ford to Jobs). Each one created an economic common sense and set of business models that supported the new technology, which Perez calls a ‘techno-economic paradigm’. Each surge also displaced old industries, drove bubbles to burst, and led to significant social turmoil.
Perez provides a framework for how new technologies first take hold in society and then transform society. She calls the initial phase of this phenomenon “installation.” During installation, technologies demonstrate new ways of doing business and achieving financial gains. This usually creates a frenzy of investment in the new technology which drives a bubble and also intense experimentation in the technology. When the bubble bursts, the subsequent recession (or depression) is a turning point to implement social and regulatory changes to take advantage of the infrastructure created during the frenzy. If changes are made, a “golden age” typically follows as the new technology is productively deployed. If not, a “gilded age” follows where only the rich benefit. In either case, the technology eventually reaches maturity and additional avenues for investment and returns in the new technology dwindle. At this point, the opportunity for a new technology to irrupt onto the scene emerges.
Within Perez’s framework, new techno-economic paradigms both encourage and discourage innovation, through an inclusion-exclusion process. This means that as new techno-economic paradigms are being deployed, they provide opportunities for entrepreneurs to mobilize and new modes of business to create growth, and at the same time, they exclude alternative technologies because entrepreneurs and capital are following the newly proven path provided by the techno-economic paradigm. When an existing technology reaches maturity and investment opportunities diminish, capital and talent go in search of new technologies and techno-economic paradigms.
One new technology isn’t enough for a new techno-economic paradigm. The age of mass production was created by combining oil and the combustion engine. Railways required the steam engine. The information age required the microprocessor, the internet, and much more. Often, a technology will, as Perez says, “gestate” as a small improvement to the existing techno-paradigm, until complementary technologies are created and the exclusion process of the old paradigm ends. Technologies can exist in this gestation period for quite sometime until the technologies and opportunities are aligned for the installation period to begin.
In many ways, the bubbles created by the frenzy in the installation phase makes it possible for the new technology to succeed. The bubble creates a burst of (over-)investment in the infrastructure of the new technology (railways, canals, fiber optic cables, etc.). This infrastructure makes it possible for the technology to successfully deploy after the bubble bursts. The bubbles also encourage a spate of experimentation with new business models and new approaches to the technologies, enabling future entrepreneurs to follow proven paths and avoid common pitfalls. While the bubble creates a lot of financial losses and economic pain, it can be crucial in the adoption of new technologies.
A quick look at Perez’s framework would leave one to assume that 2018 was the blockchain frenzy and bubble, so we must be entering blockchain’s “turning point.” This would be a mistake.
My analysis of Perez’s framework suggests that blockchain is actually still in the gestation period, in the early days of a technology life cycle before the installation period. 2018 was not a Perez-style frenzy and bubble because it did not include key outcomes that are necessary to reach a turning point: significant infrastructure improvements and replicable business models that can serve as a roadmap during the deployment period. The bubble came early because blockchain technology enabled liquidity earlier in its life cycle.
There are three main implications of remaining in the gestation period. First, another blockchain-based frenzy and bubble is likely to come before the technology matures. In fact, multiple bubbles may be ahead of us. Second, the best path to success is to work through, rather than against, the existing technology paradigm. Third, the ecosystem needs to heavily invest in infrastructure for a new blockchain-based paradigm to emerge.
2018 did show many of the signs of a Perez-style ‘frenzy period’ entering into a turning point. The best way (and ultimately the worst way) to make money was speculation. ‘Fundamentals’ of projects rarely mattered in their valuations or growth. Wealth was celebrated and individual prophets gained recognition. Expectations went through the roof. Scams and fraud were prevalent. Retail investors piled in for fear of missing out. The frenzy had all the tell-tale signs of a classic bubble.
Although there are no “good bubbles,” bubbles can have good side effects. During Canal Mania and Railway Mania, canals and railways were built that had little hope of ever being profitable. Investors lost money, but after the bubble, these canals and railways were still there. This new infrastructure made future endeavors cheaper and easier. After the internet bubble burst in 2001, fiber optic cables were selling for pennies on the dollar. Investors did terribly, but the fiber optics infrastructure created value for consumers and made it possible for the next generation of companies to be built. This over-investment in infrastructure is often necessary for the successful deployment of new technologies.
The ICO bubble, however, did not have the good side effects of a Perez-style bubble. It didn’t produce nearly enough infrastructure to help the blockchain ecosystem move forward.
Compared to previous bubbles, the cryptosphere’s investment in infrastructure was minimal and likely to be obsolete very soon. The physical infrastructure — in mining operations, for example — is unlikely to be useful. Additional mining power on a blockchain has significantly decreasing marginal returns and different characteristics to traditional infrastructure. Unlike a city getting a new fiber optic cable or a new canal, new people do not gain access to blockchain because of additional miners. Additionally, proof of work mining is unlikely to be the path blockchain takes moving forward.
The non-physical infrastructure was also minimal. The tools that can be best described as “core blockchain infrastructure” did not have easy access to the ICO market. Dev tools, wallets, software clients, user-friendly smart contract languages, and cloud services (to name a few) are the infrastructure that will drive blockchain technology toward maturity and full deployment. The cheap capital provided through ICOs primarily flowed to the application layer (even though the whole house has been built on an immature foundation). This created incentives for people to focus on what was easily fundable rather than most needed. These perverse incentives may have actually hurt the development of key infrastructure and splintered the ecosystem.
I don’t want to despair about the state of the ecosystem. Some good things came out of the ICO bubble. Talent has flooded the field. Startups have been experimenting with different use cases to see what sticks. New blockchains were launched incorporating a wide range of new technologies and approaches. New technologies have come to market. Many core infrastructure projects raised capital and made significant technical progress. Enterprises have created their blockchain strategies. Some very successful companies were born, which will continue to fund innovation in the space.The ecosystem as a whole continues to evolve at breakneck speed. As a whole, however, the bubble did not leave in its wake the infrastructure one would expect after a Perez-style bubble.
The 2018 ICO bubble happened early in blockchain technology’s life-cycle, during its gestation period, which is much earlier than Perez’s framework would predict. This is because the technology itself enabled liquidity earlier in the life-cycle. The financial assets became liquid before the underlying technology matured.
In the internet bubble, it took companies many years to go public, and as such there was some quality threshold and some reporting required. This process enabled the technology to iterate and improve before the liquidity arrived. Because blockchain enabled liquid tokens that were virtually free to issue, the rush was on to create valuable tokens rather than valuable companies or technologies. You could create a liquid asset without any work on the underlying technology. The financial layer jumped straight into a liquid state while the technology was left behind. The resulting tokens existed in very thin markets that were highly driven by momentum.
Because of the early liquidity, the dynamics of a bubble were able to start early for the space in relationship to the technology. After all, this was not the first blockchain bubble (bitcoin already has a rich history of bubbles and crashes). The thin markets in which these assets existed likely accelerated the dynamics of the bubble.
In the fallout of a bubble, Perez outlines two necessary components to successfully deploy new and lasting technologies: proven, replicable business models and easy-to-use infrastructure. Blockchain hasn’t hit these targets yet, and so it’s a pretty obvious conclusion that blockchain is not yet at a “turning point.”
While protocol development is happening at a rapid clip, blockchain is not yet ready for mass deployment into a new techno-economic paradigm. We don’t have the proven, replicable business models that can expand industry to industry. Exchanges and mining companies, the main success stories of blockchain, are not replicable business models and do not cross industries. We don’t yet have the infrastructure for mass adoption. Moreover, the use cases that are gaining traction are mostly in support of the existing economic system. Komgo is using blockchain to improve an incredibly antiquated industry (trade finance) but it is still operating within the legacy economic paradigm.
Blockchain, therefore, is still in the “gestation period.” Before most technologies could enter the irruption phase and transform the economy, they were used to augment the existing economy. In blockchain, this looks like private and consortium chain solutions.
Some people in blockchain see this as a bad result. I see it as absolutely crucial. Without these experiments, blockchain risks fading out as a technological movement before its given the chance to mature and develop. In fact, one area where ConsenSys is not given the credit I believe it deserves is in bringing enterprises into the Ethereum blockchain space. This enterprise interest brings in more talent, lays the seeds for additional infrastructure, and adds credibility to the space. I am more excited by enterprise usage of blockchain today than any other short-term developments.
This was not the first blockchain bubble. I don’t expect it to be the last (though hopefully some lessons will be learned from the last 12 months). Perez’s framework predicts that when the replicable business model is found in blockchain, another period of frenzied investment will occur, likely leading to a bubble. As Fred Wilson writes, “Carlota Perez [shows] ‘nothing important happens without crashes.’ ” Given the amount of capital available, I think this is a highly likely outcome. Given the massive potential of blockchain technology, the bubble is likely to involve more capital at risk than the 2018 one.
This next frenzy will have the same telltale signs of the previous one. Fundamentals will decrease in importance; retail investors will enter the market for fear of missing out; fraud will increase; and so on.
Perez’s framework offers two direct strategic lessons for PegaSys and for any serious protocol development project in the blockchain space. First, we should continue to work with traditional enterprises. Working with enterprises will enable the technology to evolve and will power some experimentation of business models. This is a key component of the technology life-cycle and the best bet to help the ecosystem iterate.
Second, we must continue investing in infrastructure and diverse technologies for the ecosystem to succeed. This might sound obvious at first, but the point is that we will miss out on the new techno-economic paradigm if we only focus on the opportunities that are commercially viable today. Our efforts in Ethereum 1.x and 2.0 are directly born from our goal of helping the ecosystem mature and evolve. The work other groups in Ethereum and across blockchain are doing also drives towards this goal. We are deeply committed to the Ethereum roadmap and at the same time recognize the value that innovations outside Ethereum bring to the space. Ethereum’s roadmap has learned lessons from other blockchains, just as those chains have been inspired by Ethereum. This is how technologies evolve and improve.
Source : https://hackernoon.com/why-blockchain-differs-from-traditional-technology-life-cycles-95f0deabdf85
At a recent KPMG Robotic Innovations event, Futurist and friend Gerd Leonhard delivered a keynote titled “The Digital Transformation of Business and Society: Challenges and Opportunities by 2020”. I highly recommend viewing the Video of his presentation. As Gerd describes, he is a Futurist focused on foresight and observations — not predicting the future. We are at a point in history where every company needs a Gerd Leonhard. For many of the reasons presented in the video, future thinking is rapidly growing in importance. As Gerd so rightly points out, we are still vastly under-estimating the sheer velocity of change.
With regard to future thinking, Gerd used my future scenario slide to describe both the exponential and combinatorial nature of future scenarios — not only do we need to think exponentially, but we also need to think in a combinatorial manner. Gerd mentioned Tesla as a company that really knows how to do this.
He then described our current pivot point of exponential change: a point in history where humanity will change more in the next twenty years than in the previous 300. With that as a backdrop, he encouraged the audience to look five years into the future and spend 3 to 5% of their time focused on foresight. He quoted Peter Drucker (“In times of change the greatest danger is to act with yesterday’s logic”) and stated that leaders must shift from a focus on what is, to a focus on what could be. Gerd added that “wait and see” means “wait and die” (love that by the way). He urged leaders to focus on 2020 and build a plan to participate in that future, emphasizing the question is no longer what-if, but what-when. We are entering an era where the impossible is doable, and the headline for that era is: exponential, convergent, combinatorial, and inter-dependent — words that should be a key part of the leadership lexicon going forward. Here are some snapshots from his presentation:
Source: B. Joseph Pine II and James Gilmore: The Experience Economy
Gerd then summarized the session as follows:
The future is exponential, combinatorial, and interdependent: the sooner we can adjust our thinking (lateral) the better we will be at designing our future.
My take: Gerd hits on a key point. Leaders must think differently. There is very little in a leader’s collective experience that can guide them through the type of change ahead — it requires us all to think differently
When looking at AI, consider trying IA first (intelligent assistance / augmentation).
My take: These considerations allow us to create the future in a way that avoids unintended consequences. Technology as a supplement, not a replacement
Efficiency and cost reduction based on automation, AI/IA and Robotization are good stories but not the final destination: we need to go beyond the 7-ations and inevitable abundance to create new value that cannot be easily automated.
My take: Future thinking is critical for us to be effective here. We have to have a sense as to where all of this is heading, if we are to effectively create new sources of value
We won’t just need better algorithms — we also need stronger humarithms i.e. values, ethics, standards, principles and social contracts.
My take: Gerd is an evangelist for creating our future in a way that avoids hellish outcomes — and kudos to him for being that voice
“The best way to predict the future is to create it” (Alan Kay).
My Take: our context when we think about the future puts it years away, and that is just not the case anymore. What we think will take ten years is likely to happen in two. We can’t create the future if we don’t focus on it through an exponential lens
Source : https://medium.com/@frankdiana/digital-transformation-of-business-and-society-5d9286e39dbf
Moving beyond supply chain proof of concepts still requires bringing ecosystems of enterprises together
Bang on trend and with no shortage of afficiandoes; micro-brewery-made, artisinal beer proved a fitting use case for blockchain technology at Oracle OpenWorld last week.
Alpha Acid Brewing in Belmont, California was showcased as an early adopter of one of Oracle’s new blockchain based applications, Intelligent Track and Trace.
“We can now track materials and premium ingredients from our suppliers and analyse sensor data from the production process for each batch,” said Kyle Bozicevic, owner and brewer at Alpha Acid, which served up thousands of (free) cups of its beer range across the three day event.
“[The] application helps ensure that we are getting the highest quality hops, malt, and yeast, and enables us to create a strong narrative around our products for customers,” he added.
Big Red is hoping it will find an equally thirsty audience for the four supply chain focused blockchain applications it will make available through next year; Intelligent Track and Trace, Lot Lineage and Provenance, Intelligent Cold Chain and Warranty and Usage Tracking.
The use-case-specific SaaS applications are built on Oracle’s Blockchain Cloud Service launched earlier this year (itself based on Linux Foundation’s open source Hyperledger Fabric platform) and connect with its Supply Chain Management (SCM) Cloud, Enterprise Resource Management (ERP) Cloud and other applications.
“Typically when you think about the blockchain it’s about distributed ledger, it’s about digital signatures, it’s about smart contracts; but really the value proposition associated with blockchain is here,” said Rick Jewell, senior vice president, supply chain and manufacturing cloud applications, Oracle, at OpenWorld’s supply chain keynote.
Jewell pointed to a word cloud on a slide featuring phrases like: ‘reduce delays and inefficiencies’, ‘dispute resolution’, ‘proof of delivery’ and ‘expedite payments’.
“Just as we did with IoT – we didn’t stop with the IoT platform, we built IoT applications, we’ve done the same thing here. We have built form-fit blockchain applications that work on top of that,” he added.
The apps will make getting started with blockchain much easier for a business, but there are still significant challenges for them to overcome in taking the technology beyond proof-of-concept; chiefly, all the other businesses they work with.
As Gartner supply chain technology research director Amber Salley explained: “The apps will be as useful as there is an ecosystem committed to using blockchain.”
Alpha Acid is one of a number of early-adopters to get early access to the applications. Others named include Arab Jordan Investment Bank, CargoSmart, Certified Origins, Indian Oil, Intelipost, MTO, Neurosoft, Nigeria Customs, Sofbang, Solar Site Design and TradeFin.
CargoSmart is a shipment management software solutions provider in APAC, and begun its blockchain initiative for shipment documentation in July.
Since shipping document handling processes are complex, feature dated paper processes and involve many stakeholders across numerous countries, it is an ideal use case for blockchain CargoSmart CEO Steve Siu told Computerworld.
“We consider blockchain as the digital baseline for the next generation,” Siu said.
“Blockchain is something different – which is to come together to share that information in the first place then think about how the industry would take advantage of that to change the processes, to change the way they work together,” he added.
Getting all the stakeholders on to the blockchain will be a considerable challenge however.
Shipping companies have diverse technical capabilities and data standards, and currently exchange documents in many formats including email, online forms, and electronic data interchange (EDI). On average, a single shipment can involve more than 30 documents exchanged by all parties, often with multiple revisions due to human errors, before it leaves port.
These existing processes are not standardised, despite numerous attempts to do so, but would need to be if blockchain is to be used.
“To drive the industry to change is actually very difficult. That’s why we took this consortium approach, to get the industry together,” Siu added.
The sentiment was echoed by Certified Origin CIO Andrea Biagianti. His company has been using a blockchain application to trace key steps in the supply chain from Italian olive groves to the Bellucci-brand bottled extra virgin olive oil sold in North America.
“We think that the hardest step at the beginning is to build a best practice for all the actors in the supply chain. It is difficult for them to know that they have to work all together with one final scope,” he told Computerworld.
The requirement to get multiple stakeholders behind a single blockchain solution, could be a limiting factor in the apps’ success, Gartner’s Salley explained.
“Since it is a chain there needs to be multiple parties involved to add ‘links’ to the change. That means that the multiple parties will need to have invested in the systems and processes to make it work,” she said.
Despite the distributed, multi-stakeholder nature of the technology, Oracle will charge just one party, the “top node”, for using the apps and the cost is not based on the number of users on the chain.
“We do not intend on charging based on users, but we intend on charging for the platform itself,” Oracle’s executive vice president, applications product development, Steve Miranda told media.
“And the platform – think of it as the hub – whether that hub is purchased by a single node in the supply chain, the top node, or if that gets purchased by the collective sets of nodes… but because of the nature of the application and the distributed nature of the application, charging on a per user basis like that is counter to the way we expect it to be used. We want it to be used more pervasively not less pervasively,” he said.
Above a certain scale however, Miranda indicated that additional costs could kick in.
“The scale will likely have some sort of transaction charge on top of that but that depends on the blockchain use case,” he explained.
The apps will be interoperable with other blockchain providers with HyperLedger based solutions such as SAP and IBM, Oracle said.
Gartner research into supply-chain-focused blockchain solutions has found the market to be “uncertain, confusing and overly hyped”, while many proposed use cases “may not even need blockchain in the first place”.
A September report from the analyst firm said that a lack of data and governance standards across broad ecosystems of trading partners “will inhibit multi-enterprise collaboration, therefore stalling pilots and diminishing wide adoption”.
Until 2021, 90 per cent of supply chain blockchain initiatives will be proof-of-concepts (such as Commonwealth Bank of Australia’s recent almond shipping experiment) and onboarding challenges will halt 90 per cent of the initiatives across medium to large-scale enterprises, Gartner predicts.
“Blockchain in supply chain is a technology looking for a use case. I think the apps are Oracle’s attempt to create that use case. It is hard to sell blockchain as a platform so by productising it as an app gives a business a starting point to get using blockchain,” Salley said.
Intelligent Track and Trace will be available in the first quarter of next year, with the other apps following through the rest of 2019.
Source : https://www.computerworld.com.au/article/648812/oracle-apps-make-blockchain-easier-consortium-challenges-remain/
Naval Ravikant recently shared this thought:
“The dirty secrets of blockchains: they don’t scale (yet), aren’t really decentralized, distribute wealth poorly, lack killer apps, and run on a controlled Internet.”
In this post, I want to dive into his fourth observation that blockchains “lack killer apps” and understand just how far away we are to real applications (not tokens, not store of value, etc.) being built on top of blockchains.
Thanks to Dappradar, I was able to analyze the top decentralized applications (DApps) built on top of Ethereum, the largest decentralized application platform. My research is focused on live public DApp’s which are deployed and usable today. This does not include any future or potential applications not deployed yet.
If you look at a broad overview of the 312 DApps created, the main broad categories are:
I. Decentralized Exchanges
II. Games (Largely collectible type games, excluding casino/games of chance)
III. Casino Applications
IV. Other (we’ll revisit this category later)
On closer examination, it becomes clear only a few individual DApps make up the majority of transactions within their respective category:
Diving into the “Other” category, the largest individual DApps in this category are primarily pyramid schemes: PoWH 3D, PoWM, PoWL, LockedIn, etc. (*Please exercise caution, all of these projects are actual pyramid schemes.)
These top DApps are all still very small relative to traditional consumer web and mobile applications.
Further trends emerge on closer inspection of the transactions of DApps tracked here:
Where we are and what it means for protocols and the ecosystem:
After looking through the data, my personal takeaways are:
What kind of DApps do you think we as a community should be building? Would love to hear your takeaways and thoughts about the state of DApps, feel free to comment below or tweet @mccannatron.
Also, if there are any DApps or UI/UX tools I should be paying attention to, let me know — I would love to check them out.
With all of the noise surrounding bitcoin and its underlying technology, blockchain, it’s often difficult to separate real blockchain articles from those just looking for clicks.
Here’s a list, in no particular order, of articles and whitepapers written by the people actively involved in developing this new technology. The resources below range all the way back from the 1980s to today.