Tag Archives: oracle

Will Blockchain End Up Like 3DTV?

When technology is baked into a device, we rarely give it much thought. We buy a smartphone for its utility – not its operating system. Sometimes a new technology dramatically changes how everyone does things; the internet is a good example. Some plausibly great innovations, such as 3D television, just never gain traction. Which of these outcomes will blockchain have?

Recently, blockchain has emerged as a technology that will potentially transform industries in a way similar to what the Internet did a couple of decades ago. Still a nascent technology, its many uses have not yet been discovered or explored.

Most people know a little about blockchain:

    • It lets multiple parties agree on a common record of data and control who has access to it.
    • Its platform makes cryptocurrencies like bitcoin possible.
    • Movement of cryptocurrency verified by blockchain allows peer-to-peer cash transfers without involving banks.
    • Blockchain is a permanent, auditable record, so any tampering with it is obvious.

Some people think blockchain will transform security in financial services and fundamentally reshape how we deal with and trust complex transactions, though this could be a response to hype or a fear of missing out. Many other people ask why and how they should use blockchain.

On the face of it, using a shared (or distributed) ledger to process multiple transactions doesn’t seem so revolutionary. Blockchain is essentially a recordkeeping system. Perhaps its association with cryptocurrency – such as bitcoin – lends it a darker, more enigmatic edge than the software traditionally used for processing multiple transactions. One way or another, insurers face pressure to update antique systems with new ones that can compete with the demands of a digital world, and that means incorporating blockchain technology.

A distributed ledger of transactions

A blockchain can be seen as an ever-growing list of data records, or blocks, that can be easily verified because each block is linked to the previous one, forming a chain. This chain of transactions is stored on a network of computers. For a record to be added to the chain, it typically needs to be validated by a majority of the computers in the network. Importantly, no single entity runs the network or stores the data. Blockchain technology may be used in any form of asset registry, inventory and exchange. This includes transactions of finance, money, physical property and intangible assets, including health information.

Because blockchain networks consist of thousands of computers, they make any effort to add invalid records extremely difficult. Every transaction is secured using a random cryptographic hash, a digital fingerprint that prevents its being misused. Every participant has a complete history of the transactions, helping reduce the chance of transactions being corrupted. Simply put, a blockchain is a resilient, tamper-proof and decentralized store of transactions.

Complex processing and automation with smart contracts

Blockchain ecosystems enable a large number of organizations to join as peers to offer services, data or transactions that serve specific customers or complex transaction workflows transparently. These ecosystems can automatically process and settle transactions via smart contracts that encapsulate the logic for the terms and triggers that enable a transaction.

Smart contracts are created on the blockchain and are immutably recorded on the network to execute transactions based on the software-encoded logic. Transparency through workflows recorded on the blockchain facilitate auditing. Peers and partners within a blockchain ecosystem independently control their business models and the economics without the need to use intermediaries.

Self-executing smart contracts can be used to automate insurance policies, with the potential to reduce friction and fraud at claim stage. A policy could be coded to pay when the conditions are undeniably reached and decentralized data feeds verify that the event has certainly occurred. The blockchain offers enhanced transparency and measurable risk to this scenario.

Parametric insurance, which operates through smart contracts with triggers that are based on measurable events, can facilitate immediate payments while decreasing the administrative efforts and time. Effectively, the decision to pay a claim is taken out of the insurer’s hands. Other possible models are completely technology-based without the need for an actual insurance company. The decentralized blockchain model lends itself well to crowd-sourced types of insurance where premiums and claims are managed with smart contracts.

See also: Blockchain’s Future in Insurance  

Blockchain-based insurance

New insurers using blockchain are emerging and offering increased transparency and faster claims resolution. Here are some examples:

    • Peer-to-peer property and casualty insurer Lemonade uses an algorithm to pay claims when conditions in blockchain-based smart contracts are met.
    • Start-up Teambrella also leverages blockchain in a peer-to-peer concept that allows insured members to vote on claims and then settles amounts with bitcoin.
    • Dynamis provides unemployment insurance on a blockchain-based smart contract platform.
    • Travel delay insurer insurETH automatically pays claims when delays are detected and verified in a blockchain data ledger.
    • Etherisc is another new company building decentralized insurance applications on blockchain that can pay valid claims autonomously.

Traditional insurance companies, such as AXA and Generali, have also begun to invest in blockchain applications. Allianz has announced the successful pilot of a blockchain-based smart contract solution to simplify annual renewals, premium payments and claims submission and settlement.

Blockchain has the potential to improve premium, claim and policy processing among multiple parties. For example, in the last year the consultancy EY and data security firm Guardtime announced a blockchain platform to transact marine insurance. This platform pulls together the numerous transactional actions required within a highly complex global trade made up of shipping companies, brokers, insurers and other suppliers.

A consortium of insurers and reinsurers, the Blockchain Insurance Industry Initiative (B3i), has piloted distributed ledger technology to develop standards and procedures for risk transfer that are cross-market compatible. Whether or not the outcome is adopted industry-wide, it seems important for digital solutions to be created with this transparency and inclusiveness in mind.

There is clear potential for blockchain in reinsurance where large amounts of data are moved between reinsurers, brokers and clients, requiring multiple data entry and individual reconciliation. Evaluating alternative ways of conducting business is one reason for the collaboration of Gen Re with iXledger, which can explore ideas while remaining independent.

Handling of medical data and other private or sensitive information

Individuals will generate increasing amounts of personal data, actively and passively, from using phones and Internet of Things (IoT) devices, and processing digital healthcare solutions. Increasingly, consumers will want control of this scattered mass of digital data and share it with whomever they choose in exchange for services. This move aligns perfectly with the concept of a “personal data economy.” Think of information as currency and think about using blockchain to secure private data and reveal it in a secure and trusted manner to selected parties, in exchange for something.

Electronic health records are now common. Several countries use blockchain to secure patient data held digitally. This helps counter legitimate concerns about how sensitive personal data can be kept secure from theft or cyber-attack. Code representing each digital entry to the patient record is added to the blockchain, validated and time-stamped. A consortium of insurers in India is using blockchain to cut the costs of medical tests and evaluations, and to ensure the data collected is kept secure, along with other benefits including identification of potential claims fraud.

Looking to leverage the data economy, companies may employ innovative insurance propositions to engage people. Because the propositions will rely on shared data, people may be put off, fearing a loss of control over their personal information. While this fear poses a huge challenge for an industry seeking to improve its reputation for trust, blockchain technology may help insurers to reassure customers the digital data they share with them is safe.

Verification of documents

Verification of the existence and purpose documents in banks and insurance companies relies on storage, retrieval and access to data. A blockchain simplifies this process with its open ledger, cryptographic hash keys and date-stamped transactions. Actual hard copies of documents are not stored; instead, the hash represents the exact content in a form of scrambled letters and numbers. A change in a document will be exposed because it will not match the encoded one. The effect is an immutability that proves the status of the data at an exact moment and beyond doubt.

Blockchain technology is a “trustless” system because nobody has to trust anybody else for the system to function; the network of users acts together to vouch for the accuracy of the record. Examples of blockchain protecting patient records demonstrate its potential to implement other trusted and secure transactions with less bureaucracy.

There are other opportunities for insurers to move to a digitized paradigm and catalyze efficiency gains; blockchain need not be reserved for cross-industry platforms, and it’s not only useful in multiparty markets with high transaction volumes and significant levels of reconciliation; smaller-scale solutions can bring benefits, too.

Features that ensure privacy and data security

Beyond driving efficiencies, blockchain employs agreed standards for data care, which reduce the vulnerability of data that arises with the mass of sensitive data that digital connectivity creates. Other features that enhance privacy and data security include the contract process: Transactions are not directly associated with the individual, and personal information is not stored in a centralized database vulnerable to cyber-attack. Insurance companies, as well as technology companies, are accountable to their users for the security of their devices, services and software, and hackers are less likely to target enterprises with strong security.

Multiple participants and the removal of a central authority

Transparency, audit-ability and speed are standard requirements for any organization to successfully compete and transact in an increasingly complex global economy. Data is a valuable catalyst to that process and is complemented by blockchain’s ability to organize, access and transact efficiently and compliantly.

Trusted transactions require access to valuable data, and blockchain facilitates efficient access across multiple organizations. The economics for data usage will drive new business models fueled by micropayments, which will require efficiencies to scale. Business models based on data aggregation by third parties in centralized repositories with total control and limited transparency will be replaced by distributed blockchain-enabled data exchanges where data providers are peers within the ecosystem.

Decentralized peer organizations can use the blockchain for permission access, and for facilitating payments, to ensure total control of their economic models, without having a centralized authority. Data access and transactions are controlled directly by each member of the ecosystem, with complete transparency and immediate compensation.

Token economies

Ecosystems supporting peer organizations that transact or share data will require an effective mechanism for micropayments. These business models require efficiency, with less overhead than traditional account payable and account receivable workflows.

Event triggers, cryptlets that enable secure communication between blockchain, and external verification sources (oracles) will execute based on predetermined criteria, and token payments will be made simultaneously. Counterparty agreements may initially define the relationships between parties on the network, but payments are executed within the smart contract transactions.

See also: How Insurance and Blockchain Fit  

The elimination of a time delay in payments acts as a stimulant for economies; tokens earned can immediately be spent, increasing the speed at which organizations will earn and spend. Traditional delays and fees that occur throughout accounting workflows and through intermediary banks that process payments can be eliminated.

Cross-border processing

Currently, global payments involving foreign exchange introduce complexities in addition to time delays. Economic indicators and political events dramatically affect the exchange rates and profitability of transactions. Cross-border payments require access to the required currencies by intermediary banks, which can cause additional delays beyond the internal accounting workflows.

With blockchain technology, using a token-enabled economic layer simplifies the payments to support micropayment efficiencies. Participants on the blockchain network will be able to efficiently use the preferred fiat currencies to acquire or sell tokens without using intermediaries, banks or currencies.

Merging blockchain and data

Today, there are more connected IoT devices than there are people on the planet, and the data generated is growing at an exponential rate. Various sources have predicted that the number of connected devices will grow to more than 70 billion by 2025; the numbers are almost irrelevant.

IoT devices are used in homes, transportation, communities, urban planning, environment, consumer packaged goods, services and soon in human bodies. A number of insurance companies use these devices to assess driver habits and usage. Autonomous cars and changing ownership and usage models are creating a generation of insurance products that can be facilitated through IoT-collected data. Home devices can detect leaks, theft and fire damage – capabilities that reduce risk. Shipping companies use the IoT for fuel and cargo management, which offers operating efficiencies, transparency and loss prevention.

Merging the mass of IoT data with the blockchain is not without challenges, but this combination can provide a completely new way of creating an insurance model that is far more efficient and faster, and where data flows directly from policyholders to the insurer.

Summary

Interest in the trinity of bitcoin, blockchain and distributed ledger technology has significant momentum. However, the technology is not magic or a panacea for every corporate woe. It has disadvantages and limitations, and there are situations where it would even be the wrong solution. There is enough about it, though, to merit continued closer investigation – the many emerging cases of its application bear testament to that – but in place of hype we still need answers.

How to Move to the Post-Digital Age?

We are in the midst of the shift from the information age to the digital age, which is realigning fundamental elements of business that require major adjustments to thrive, let alone survive.

As we noted in our new report, Greenfields, Startups and InsurTech: Accelerating Digital Age Business Modelsnew greenfield and startup competitors are rising from within and outside of every industry, including insurance, to capture the post-digital age business opportunities of the next generation of buyers. By shifting to meet the forces of change, these companies are positioning themselves to be the market leaders in the post-digital age. Those that do not make the shift risk not only the loss of customers but also market share and relevance in the coming new age of insurance.

See also: 6 Charts on Startups, Greenfields, Incubators  

Sometimes, the next big thing isn’t easy to spot. The disruption of the insurance industry is in the early days, so predictions are difficult. Will the new greenfields and startups become the next market leaders? If history is a guide, the answer is yes … some will. Just consider Progressive and how many dismissed it early on. Now it is a top 10 insurer in the U.S. Or consider what has happened in other industries with companies that are defunct because they missed the shift:

  • Streaming video: Blockbuster failed to see this trend. It filed for bankruptcy in 2010 and Netflix is now worth more than $61 billion.
  • Mobile games: In 2011, the president of Nintendo North America suggested that mobile game apps were disposable from a consumer perspective. Today, Pokemon Go has 65 million users. Is that disposable?
  • Apple iPhone: Former Microsoft CEO Steve Ballmer reportedly commented that the first Apple iPhone would not appeal to business customers because it did not have a keyboard and would not be a good email machine. Apple iPhone single-handedly disrupted and redefined multiple industries and continues to do so.
  • Autonomous vehicles: In 2015, Jaguar’s head of R&D stated that autonomous vehicles didn’t consider customers’ cargo. Since then, Jaguar Land Rover has invested $25 million in Lyft to join the autonomous trend.
  • On-premise enterprise software vs. cloud-based SaaS platforms: In 2003, Thomas Siebel of Siebel Systems said Microsoft would roll over Salesforce in the CRM market. In 2005, Oracle acquired Siebel Systems for $5.85 billion. Salesforce’s market cap, in contrast, is more than $60 billion.

Insurance Industry Change and Disruption

At no time in the history of insurance can we find as many game-changing events and a rapid pace of advancement occurring at the same time. At the forefront is the increased momentum for insurtech, and the greenfields and startups within, creating high levels of activity, excitement and concern on the promise and potential of insurance disruption and reinvention.

When you add it all up, the insurance industry has many characteristics that make it an attractive target for aggressive investments in innovation. First, its size is enormous – based on industry data, it is estimated that premiums written are more than $4.7 trillion globally. Second, it faces multiple challenges that offer opportunities for exploitation by nimble, efficient and innovative competitors.

Insurtech advancements and the forces of change see no significant slowdown. The momentum for change that has been building is unstoppable. Industry advancements, cultural trends and IT reactions are gaining speed as they gain strength and a framework for stability and growth. It is pushing a sometimes slow-to-adapt industry by challenging the traditional business assumptions, operations, processes and products, highlighting two distinctively different business models: 1) a pre-digital age model of the past 50-plus years based on the business assumptions, products, processes and channels of the Silent and Baby Boomer generations and 2) a post-digital age model focused on the next generation including the Millennials and Gen Z, as well as many in Gen X.

Greenfields and Startups Make the Boardroom Agenda

The market landscape is rapidly changing. During 2016, Lemonade launched. Metromile decided to become a full-stack insurer, leaving its MGA days behind. New MGAs entered the picture, including Slice, TROV, Quilt, Hippo and Figo Pet Insurance, to name a few.  Existing insurers made market debuts with new startups including Shelter’s Say Insurance with auto insurance for millennials, biBerk from Berkshire Hathaway for direct small commercial lines and Sonnet Insurance as the digital brand from Economical Insurance in Canada, among others.

Add to this the projected shrinking of insurable risk pools due to the emergence of autonomous vehicles, connected homes and wearables and the domino effect of these on other industries, and it’s not hard to imagine a future with traditional carriers fighting over a much smaller pool of customers where only the most efficient, effective and innovative will survive.

As a result, discussion surrounding greenfields, startups and insurtech moved into the board room of every insurer and reinsurer trying to understand how to leverage the shift to the digital age and develop strategies and plans to respond. Yet some insurers have a blind spot in recognizing the competition both from outside and within the industry, and the critical need to begin planning a new post-digital age business model. The result is a growing gap between knowing, planning and doing among leaders and fast followers or laggards, which is rapidly becoming insurmountable due to the pace of change.

Closing the Gap with Greenfield and Startup Business Models

Assuming that most insurers grasp the need for a greenfield and startup mentality to grow, what remains is to aim all efforts toward accomplishing an organizational shift. How do you move your company from the pre-digital age to the post-digital age and close the gap?

It requires leadership to build consensus. It requires vision to aim in the most market-ready direction. And it requires a new business paradigm that will allow for change. We must redefine and re-envision insurance to enable growth and remain competitive.

While many have made progress in replacing legacy systems and traditional business processes, this is not enough. These systems, while modern, were built around pre-digital age business assumptions and models, not to support the range of needs in a post-digital age model driven by a new generation of customers. Like other industries, today’s insurance startups and greenfields need and want options that do not require investment in significant infrastructure or upfront costs and therefore seek a cloud business platform solution to maximize options and minimize costs and capital outlay.

See also: How to Plant in the Greenfields  

A modern cloud business platform provides an advantage for greenfields and startups, breaking down traditional boundaries, IT constraints and age-old business assumptions about doing business, while building up the ability to rapidly develop and launch new products and services. The platform is a robust set of technology, mobile, digital, data and core capabilities in the cloud with an ecosystem of innovative partners (many insurtech technology startups) that provides the ability to launch and grow a business rapidly and cost effectively.

Will established insurers suffer at the hands of tech-savvy, culture-savvy competition? Some may, but only if they allow themselves to. There will be constant pressure from greenfields and startups to outdo each other in the race to better meet the needs and demands of a new generation of buyers in a post-digital age for insurance.

For traditional insurance companies, the need to re-invent and transform the business is no longer a matter of if, but of when.  Insurance leaders should ask themselves: Do we have a strategy that considers transformation of both the legacy business and creation of a new business for the future? Who are our future customers and what will they demand? Who are our emerging new competitors? Where are we focusing our resources…on the business or on the infrastructure?

A new generation of insurance buyers with new needs and expectations creates both a challenge and an opportunity that a greenfield and startup business model can capitalize on to incubate, launch and grow. The time for plans, preparation and execution is now — recognizing that the gap is widening and the timeframe to respond is closing.

New Era of Commercial Insurance

Despite a generally soft market for traditional P&C products, the fact that so many industries and the businesses within them are being reshaped by technology is creating opportunities (and more challenges). Consider insurers with personal and commercial auto. Pundits are predicting a rapid decline in personal auto premiums and questioning the viability of both personal and commercial auto due to the emergence of autonomous technologies and driverless vehicles, as well as the increasing use of alternative options (ride-sharing, public transportation, etc.).

Finding alternative growth strategies is “top of mind” for CEOs.  Opportunities can be captured from the change within commercial and specialty insurance. New risks, new markets, new customers and the demand for new products and services may fill the gaps for those who are prepared.

Our new research, A New Age of Insurance: Growth Opportunities for Commercial and Specialty Insurance at a Time of Market Disruption, highlights how changing trends in demographics, customer behaviors, technology, data and market boundaries are creating a dramatic shift from traditional commercial and specialty products to the new, post-digital age products redefining the market of the future.

See also: Insurtechs Are Pushing for Transparency

Growth Opportunities

New technologies, demographics, behaviors and more will fuel the growth of new businesses and industries over the next 10 years. Commercial and specialty insurance provides a critical role to these businesses and the economy — protecting them from failure by assuming the risks inherent in their transformation.

Industry statistics for the “traditional” commercial marketplace don’t yet reflect the potential growth from these new markets. The Insurance Information Institute expects overall personal and commercial exposures to increase between 4% and 4.5% in 2017 but cautioned that continued soft rates in commercial lines could cause overall P&C premium growth to lag behind economic growth.

But a diverse group of customers will increasingly create narrow segments that will demand niche, personalized products and services. Many do not fit neatly within pre-defined categories of risk and products for insur­ance, creating opportunities for new products and services.

Small and medium businesses are at the forefront of this change and at the center of business creation, business transformation and growth in the economy.

  • By 2020, more than 60% of small businesses in the U.S. will be owned by millennials and Gen Xers — two groups that prefer to do as much as possible digitally. Furthermore, their views, behaviors and expectations are different than those of previous generations and will be influenced by their personal digital experiences.
  • The sharing/gig/on-demand economy is an example of the significant digitally enabled changes in people’s behaviors and expectations that are redefining the nature of work, business models and risk profiles.
  • The rapid emergence of technologies and the explosion of data are combining to create a magnified impact. Technology and data are making it easier and more profitable to reach, underwrite and service commercial and specialty market segments. In particular, insurers can narrow and specialize various segments into new niches. In addition, the combination of technology and data is disrupting other industries, changing existing business models and creating businesses and risks that need new types of insurance.
  • New products can be deployed on demand, and industry boundaries are blurring. Traditional insurance or new forms of insurance may be embedded in the purchase of products and services.

Insurtech is re-shaping this new digital world and disrupting the traditional insurance value chain for commercial and specialty insurance, leading to specialty protection for a new era of business. Consider insurtech startups like Embroker, Next Insurance, Ask Kodiak, CoverWallet, Splice and others. Not being left behind, traditional insurers are creating innovative business models for commercial and specialty insurance, like Berkshire Hathaway with biBERK for direct to small business owners; Hiscox, which offers small business insurance (SBI) products directly from its website; or American Family, which invested in AssureStart, now part of Homesite, a direct writer of SBI.

The Domino Effect

We all likely played with dominoes in our childhood, setting them up in a row and seeing how we could orchestrate a chain reaction. Now, as adults, we are seeing and playing with dominoes at a much higher level. Every business has been or likely will be affected by a domino effect.

What is different in today’s business era, as opposed to even a decade ago, is that disruption in one industry has a much broader ripple effect that disrupts the risk landscape of multiple other industries and creates additional risks. We are compelled to watch the chains created from inside and outside of insurance. Recognizing that this domino effect occurs is critical to developing appropriate new product plans that align to these shifts.

Just consider the following disrupted industries and then think about the disrupters and their casualties: taxis and ridesharing (Lyft, Uber), movie rentals (Blockbuster) and streaming video (NetFlix), traditional retail (Sears and Macy’s) and online retail, enterprise systems (Siebel, Oracle) and cloud platforms (Salesforce and Workday), and book stores (Borders) and Amazon. Consider the continuing impact of Amazon, with the announcement about acquiring Whole Foods and the significant drop in stock prices for traditional grocers. Many analysts noted that this is a game changer with massive innovative opportunities.

The transportation industry is at the front end of a massive domino-toppling event. A report from RethinkX, The Disruption of Transportation and the Collapse of the Internal-Combustion Vehicle and Oil Industries, says that by 2030 (within 10 years of regulatory approval of autonomous vehicles (AVs)), 95% of U.S. passenger miles traveled will be served by on-demand autonomous electric vehicles owned by fleets, not individuals, in a new business model called “transportation-as-a-service” (TaaS). The TaaS disruption will have enormous implications across the automotive industry, but also many other industries, including public transportation, oil, auto repair shops and gas stations. The result is that not just one industry could be disrupted … many could be affected by just one domino … autonomous vehicles. Auto insurance is in this chain of disruption.

See also: Leveraging AI in Commercial Insurance  

And commercial insurance, because it is used by all businesses to provide risk protection, is also in the chain of all those businesses affected – a decline in number of businesses, decline in risk products needed and decline in revenue. The domino effect will decimate traditional business, product and revenue models, while creating growth opportunities for those bold enough to begin preparing for it today with different risk products.

Transformation + Creativity = Opportunity

Opportunity in insurance starts with transformation. New technologies will be enablers on the path to innovative ideas. As the new age of insurance unfolds, insurers must recommit to their business transformation journey and avoid falling into an operational trap or resorting to traditional thinking. In this changing insurance market, new competitors don’t play by the rules of the past. Insurers need to be a part of rewriting the rules for the future, because there is less risk when you write the new rules. One of those rules is diversification. Diversification is about building new products, exploring new markets and taking new risks. The cost of ignoring this can be brutal. Insurers that can see the change and opportunity for commercial and specialty lines will set themselves apart from those that do not.

For a greater in-depth look at the implications of commercial insurance shifts, be sure to downloadA New Age of Insurance: Growth Opportunities for Commercial and Specialty Insurance at a Time of Market Disruption.

The Incredible Impact From Superbosses

Please join me for “Path to Transformation,” an event I am putting on May 10 and 11 at the Plug and Play accelerator in Silicon Valley in conjunction with Insurance Thought Leadership. The event will not only explore technological breakthroughs but will explain how companies can test and absorb the technologies, in ways that then lead to startling (and highly profitable) innovation. My son and I have been teaching these events around the world, and I hope to see you in May. You can sign up here.

“I don’t care if you have to take drugs, you have to build it in six months,” said my boss, Khurshed Birdie, when I told him that he was on drugs if he thought my team could create a software development tool set in less than three years. This was in 1986 at Credit Suisse First Boston, one of New York City’s top investment banks. We were rebuilding the company’s trade processing systems to run on a client–server model of computing. This technology is common now, but then it was as futuristic as “Star Wars.”

My team worked day and night to build a technology that became the foundation of the company’s information systems. It gave Credit Suisse First Boston a competitive edge and led IBM to invest $20 million in a spinoff company that was formed to market the tools we had developed.

I was a lowly computer programmer, an analyst when Birdie hired me, a computer geek who didn’t own any three-piece suits, white two-ply cotton shirts or wing-tipped Oxford shoes — the uniform of investment bankers. Yet I was hired on the spot. I had some far-out ideas about how computer systems could be built but didn’t believe for a second that I could implement them. My boss did: He believed in me more than I did, and he bet a $100 million project on my vision.

He allowed me to expand my team from four to 54 people and shielded me from criticism by other teams who had to use my tools to build their systems — and who thought I was crazy. There were a lot of problems along the way, and Birdie allowed me to learn from my mistakes. And then he promoted me to vice president of information technology when I achieved success.

Birdie was what Sydney Finkelstein, a Dartmouth business professor, in his new book, Superbosses: How Exceptional Leaders Manage the Flow of Talent, calls a “superboss.”

As Finkelstein explains, superbosses take chances on unconventional talent. Oracle’s founder, Larry Ellison, hired candidates who had accomplished something genuinely difficult, rather than those with formal qualifications, because he believed they would rise to the technical challenges. Designer Ralph Lauren offered jobs to strangers whom he met while dining in New York City restaurants. Superbosses take raw talent and build self-confidence. They hire for intelligence, creativity and flexibility — and are not afraid of people who may be smarter than they are.

Under Finkelstein’s definition of superbosses, Birdie would be categorized as a “glorious bastard”: someone who cares only about winning. Deep down, he had a good heart —  but was ruthless in setting expectations and driving people to work extremely hard. I’ll never forget him telling me that “Christmas was an optional holiday.” These bosses realize that, to get the very best results, they need to drive people to perform beyond what seems reasonable and achievable.

Even though I achieved a lot, I hated working for Birdie, because I had to neglect my family for months on end. This isn’t something I would ever do to my employees. My next boss, Gene Bedell, was very different. He left his job as managing director of information technology to found Seer Technologies, the start-up that IBM had funded. Bedell convinced me to leave my high-paying investment-banking job to join him in a No. 2 role, as chief technology officer, at the low-paying, high-risk, start-up.

Bedell was what Finkelstein calls a “nurturer”: someone who coaches, inspires and mentors. These superbosses take pride in bringing others along and care deeply about the success of their protégés; they help people accomplish more than they’d ever thought they could.

Bedell managed by a method he called “outstanding success possibilities.” He challenged his executives to set ultra-ambitious goals and then find unconventional ways to achieve them. Instead of managing to what was achievable and possible, we shot for the impossible. And then did whatever it took to get there — without worrying about failure or looking back. It is amazing what you can achieve when you have a single-minded focus. We took Seer Technologies from zero to $120 million in annual revenue and an IPO in just five years — faster than any other software company of that era, including Microsoft and Oracle.

Superbosses create master–apprentice relationships. They customize their coaching to what each protégé needs and are constant fonts of practical wisdom. Bedell taught me how to sell. A year after the company was formed, he sent me to Tokyo to sell IBM-Japan on an $8.6 million deal to fund the creation of a Japanese version of our product. I didn’t think that a techie like me could do these things; he taught me that selling was an art that could be learned and perfected. I helped our salespeople close more than $200 million in software deals. And that is another skill that superbosses have, building what Finkelstein calls the “cohort effect”: teamwork and competition combined. Lorne Michaels, for example, who created “Saturday Night Live,” judged writers and performers by how much of their material actually went to air — but they had to do it with the support of their coworkers, the people they were competing with.

A common trait of superbosses is the ability to delegate work and build jobs on the strengths of their subordinates. They trust subordinates to do their jobs and are as supportive as can be. They remain intimately involved in the details of the businesses and build true friendships. Bedell often invited my family to his vacation home near the Outer Banks of North Carolina. He took me to Skip Barber Racing School to learn how to race a Formula Ford and built a gym in his basement so that his executive team could lift weights together.

You will find the alumni of our project at Credit Suisse First Boston and Seer Technologies in senior leadership roles now, at companies such as IBM, PayPal, American Express and every one of the top investment banks. Many started their own companies, as I later did. There are literally hundreds of people who built successful careers because of my two superbosses. When I became an academic later in life, I was fortunate to have two superboss deans at Duke’s Pratt School of Engineering, Kristina Johnson and Tom Katsouleas, who nurtured me. Superbosses aren’t just in corporations — they can be found everywhere.

Yes, I know that I got lucky in having good bosses; most are jerks who demotivate employees, slow their growth, backstab and take credit for others’ work. You are usually stuck with whomever you get. But there is nothing that stops you from being a superboss. As you begin to achieve success, start helping others and nurturing your colleagues and subordinates. Show the leadership qualities that you’d like your own boss to have. You will gain as much as the people you help — and build a better company.

This article first appeared at the Washington Post.

What Is and What Isn’t a Blockchain?

I Block, Therefore I Chain?

What is, and what isn’t, a “blockchain”?  The Bitcoin cryptocurrency uses a data structure that I have often termed as part of a class of “mutual distributed ledgers.” Let me set out the terms as I understand them:

  • ledger – a record of transactions;
  • distributed – divided among several or many, in multiple locations;
  • mutual – shared in common, or owned by a community;
  • mutual distributed ledger (MDL) – a  record of transactions shared in common and stored in multiple locations;
  • mutual distributed ledger technology – a technology that provides an immutable record of transactions shared in common and stored in multiple locations.

Interestingly, the 2008 Satoshi Nakamoto paper that preceded the Jan. 1, 2009, launch of the Bitcoin protocol does not use the term “blockchain” or “block chain.” It does refer to “blocks.” It does refer to “chains.” It does refer to “blocks” being “chained” and also a “proof-of-work chain.” The paper’s conclusion echoes a MDL – “we proposed a peer-to-peer network using proof-of-work to record a public history of transactions that quickly becomes computationally impractical for an attacker to change if honest nodes control a majority of CPU power.” [Satoshi Nakamoto, Bitcoin: A Peer-to-Peer Electronic Cash System, bitcoin.org (2008)]

I have been unable to find the person who coined the term “block chain” or “blockchain.” [Contributions welcome!] The term “blockchain” only makes it into Google Trends in March 2012, more than three years from the launch of the Bitcoin protocol.

Blockchain

And the tide may be turning. In July 2015, the States of Jersey issued a consultation document on regulation of virtual currencies and referred to “distributed ledger technology.” In January 2016, the U.K. Government Office of Science fixed on “distributed ledger technology,” as does the Financial Conduct Authority and the Bank of England. Etymological evolution is not over.

Ledger Challenge

Wuz we first? Back in 1995, our firm, Z/Yen, faced a technical problem. We were building a highly secure case management system that would be used in the field by case officers on personal computers. Case officers would enter confidential details on the development and progress of their work. We needed to run a large concurrent database over numerous machines. We could not count on case officers out on the road dialing in or using Internet connections. Given the highly sensitive nature of the cases, security was paramount, and we couldn’t even trust the case officers overly much, so a full audit trail was required.

We took advantage of our clients’ “four eyes” policy. Case officers worked on all cases together with someone else, and not on all cases with the same person. Case officers had to jointly agree on a final version of a case file. We could count on them (mostly) running into sufficient other case officers over a reasonable period and using their encounters to transmit data on all cases. So we built a decentralized system where every computer had a copy of everything, but encrypted so case officers could only view their own work, oblivious to the many other records on their machines. When case officers met each other, their machines would “openly” swap their joint files over a cable or floppy disk but “confidentially” swap everyone else’s encrypted files behind the scenes, too. Even back at headquarters, four servers treated each other as peers rather than having a master central database. If a case officer failed to “bump into” enough people, then he or she would be called and asked to dial in or meet someone or drop by headquarters to synchronize.  This was, in practice, rarely required.

We called these decentralized chains “data stacks.” We encrypted all of the files on the machines, permitting case officers to share keys only for their shared cases. We encrypted a hash of every record within each subsequent record, a process we called “sleeving.” We wound up with a highly successful system that had a continuous chain of sequentially encrypted records across multiple machines treating each other as peers. We had some problems with synchronizing a concurrent database, but they were surmounted.

Around the time of our work, there were other attempts to do similar highly secure distributed transaction databases, e.g. Ian Griggs and Ricardo on payments, Stanford University and LOCKSS and CLOCKSS for academic archiving. Some people might point out that we weren’t probably truly peer-to-peer, reserving that accolade for Gnutella in 2000. Whatever. We may have been bright, perhaps even first, but were not alone.

Good or Bad Databases?

In a strict sense, MDLs are bad databases. They wastefully store information about every single alteration or addition and never delete.

In another sense, MDLs are great databases. In a world of connectivity and cheap storage, it can be a good engineering choice to record everything “forever.” MDLs make great central databases, logically central but physically distributed. This means that they eliminate a lot of messaging. Rather than sending you a file to edit, which you edit, sending back a copy to me, then sending a further copy on to someone else for more processing, all of us can access a central copy with a full audit trail of all changes. The more people involved in the messaging, the more mutual the participation, the more efficient this approach becomes.

Trillions of Choices

Perhaps the most significant announcement of 2015 was in January from IBM and Samsung. They announced their intention to work together on mutual distributed ledgers (aka blockchain technology) for the Internet-of Things. ADEPT (Autonomous Decentralized Peer-to-Peer Telemetry) is a jointly developed system for distributed networks of devices.

In summer 2015, a North American energy insurer raised an interesting problem with us. It was looking at insuring U.S. energy companies about to offer reduced electricity rates to clients that allowed them to turn appliances on and off — for example, a freezer. Now, freezers in America can hold substantial and valuable quantities of foodstuffs, often several thousand dollars. Obviously, the insurer was worried about correctly pricing a policy for the electricity firm in case there was some enormous cyber-attack or network disturbance.

Imagine coming home to find your freezer off and several thousands of dollars of thawed mush inside. You ring your home and contents insurer, which notes that you have one of those new-fangled electricity contracts: The fault probably lies with the electricity company; go claim from them. You ring the electricity company. In a fit of customer service, the company denies having anything to do with turning off your freezer; if anything, it was probably the freezer manufacturer that is at fault. The freezer manufacturer knows for a fact that there is nothing wrong except that you and the electricity company must have installed things improperly. Of course, the other parties think, you may not be all you seem to be. Perhaps you unplugged the freezer to vacuum your house and forgot to reconnect things. Perhaps you were a bit tight on funds and thought you could turn your frozen food into “liquid assets.”

I believe IBM and Samsung foresee, correctly, 10 billion people with hundreds of ledgers each, a trillion distributed ledgers. My freezer-electricity-control-ledger, my entertainment system, home security system, heating-and-cooling systems, telephone, autonomous automobile, local area network, etc. In the future, machines will make decisions and send buy-and-sell signals to each other that have large financial consequences. Somewhat coyly, we pointed out to our North American insurer that it should perhaps be telling the electricity company which freezers to shut off first, starting with the ones with low-value contents.

A trillion or so ledgers will not run through a single one. The idea behind cryptocurrencies is “permissionless” participation — any of the billions of people on the planet can participate. Another way of looking at this is that all of the billions of people on the planet are “permissioned” to participate in the Bitcoin protocol for payments. The problem is that they will not be continuous participants. They will dip in and out.

Some obvious implementation choices are: public vs. private? Is reading the ledger open to all or just to defined members of a limited community? Permissioned vs. permissionless? Are only people with permission allowed to add transactions, or can anyone attempt to add a transaction? True peer-to-peer or merely decentralized? Are all nodes equal and performing the same tasks, or do some nodes have more power and additional tasks?

People also need to decide if they want to use an existing ledger service (e.g. Bitcoin, Ethereum, Ripple), copy a ledger off-the-shelf, or build their own. Building your own is not easy, but it’s not impossible. People have enough trouble implementing a single database, so a welter of distributed databases is more complex, sure. However, if my firm can implement a couple of hundred with numerous variations, then it is not impossible for others.

The Coin Is Not the Chain

Another sticking point of terminology is adding transactions. There are numerous validation mechanisms for authorizing new transactions, e.g. proof-of-work, proof-of-stake, consensus or identity mechanisms. I divide these into “proof-of-work,”  i.e. “mining,” and consider all others various forms of “voting” to agree. Sometimes, one person has all the votes. Sometimes, a group does. Sometimes, more complicated voting structures are built to reflect the power and economic environment in which the MDL operates. As Stalin said, “I consider it completely unimportant who in the party will vote, or how; but what is extraordinarily important is this — who will count the votes, and how.”

As the various definitions above show, the blockchain is the data structure, the mechanism for recording transactions, not the mechanism for authorizing new transactions. So the taxonomy starts with an MDL or shared ledger; one kind of MDL is a permissionless shared ledger, and one form of permissionless shared ledger is a blockchain.

Last year, Z/Yen created a timestamping service, MetroGnomo, with the States of Alderney. We used a mutual distributed ledger technology, i.e. a technology that provides an immutable record of transactions shared in common and stored in multiple locations. However, we did not use “mining” to authorize new transactions. Because the incentive to cheat appears irrelevant here, we used an approach called “agnostic woven” broadcasting from “transmitters” to “receivers” — to paraphrase Douglas Hofstadter, we created an Eternal Golden Braid.

So is MetroGnomo based on a blockchain? I say that MetroGnomo uses a MDL, part of a wider family that includes the Bitcoin blockchain along with others that claim use technologies similar to the Bitcoin blockchain. I believe that the mechanism for adding new transactions is novel (probably). For me, it is a moot point if we “block” a group of transactions or write them out singly (blocksize = 1).

Yes, I struggle with “blockchain.” When people talk to me about blockchain, it’s as if they’re trying to talk about databases yet keep referring to “The Ingres” or “The Oracle.” They presume the technological solution, “I think I need an Oracle” (sic), before specifying the generic technology, “I think I need a database.” Yet I also struggle with MDL. It may be strictly correct, but it is long and boring. Blockchain, or even “chains” or “ChainZ” is cuter.

We have tested alternative terms such as “replicated authoritative immutable ledger,” “persistent, pervasive,and permanent ledger” and even the louche “consensual ledger.” My favorite might be ChainLedgers. Or Distributed ChainLedgers. Or LedgerChains. Who cares about strict correctness? Let’s try to work harder on a common term. All suggestions welcome!