B2G: The Excitement Of An Old-Line Industry

Joe|October 15, 2013

“It is not ‘Can any of us imagine better?’ but ‘Can we all do better?’
Object whatsoever is possible, still the question recurs, ‘Can we do better?’”

– Abraham Lincoln, Second Annual Message to Congress, 1862

Government represents one of the most challenging sectors in which to build a business. Yet the challenges represent opportunities for those bold enough to tackle them. Winning requires patience, deep pockets, and cutting-edge technology.Below we discuss four key points that indicate dramatic upside for the best companies: 1) Old technology provides opportunities for order-of-magnitude improvements; 2) Big institutions signal huge markets; 3) Industry pressures demand new efficiencies; and 4) Challenging sales cycles increase barriers to entry and foster customer retention. One can expect similar dynamics across other old-line industries like finance, energy, healthcare, and education.

1. Old Technology Provides Opportunities for Order-of-magnitude Improvements

Government information technology is notoriously antiquated. Interfaces stem from the 1980s and 1990s. Code-bases in most enterprise platforms stem from the 1970s. There’s paper everywhere. Most major deployments are customized monstrosities built by paid-by-the-hour engineers from giant consultancies. Dissatisfied customers represent the norm.

Why is this exciting? Because chances for radical improvement lay around like gold nuggets in 1849. New technologies can streamline basic workflows across whole enterprises, and create transparency and intelligence where little exists. Collectively, this represents an opportunity to fix the world’s most important and pervasive industry by shining a light on inefficient structures and enabling insights and comparisons that are impossible with current IT.

Consider a basic question that the CEO of a city (called a City Manager) might ask: “How much have we spent on police pensions in the last five years?” Finding that answer in most cities constitutes a research project. One might call “IT” to run reports from the accounting system, scroll through Excel spreadsheets with tens of thousands of rows to find a few disparate lines, or sift through a 300-page budget PDF.

With new reporting technology, that question and others like it now require five clicks and about 15 seconds. The answer comes with manifold visualizations, each of which can be exported and shared digitally or in print.

More complicated workflows result in more dramatic gains. Comparing actual operating expenses to budget, for instance, requires hours each month from department, division, and program directors across a city. Rather than catch bad guys, the police chief must sift through Excel spreadsheets to see whether his units are spending according to plan. Some governments forego certain analyses altogether, waiting until the end of the year to evaluate performance.

These workflows can now take minutes, and department heads and finance professionals can complete them on the web from their laptops in their pajamas over the weekend (rather than the customary in-office desktop log-in). For its part, the City Council (like a Board of Directors) can prepare for weekly and monthly meetings without bothering senior staff for expenditure reports.

Man-machine symbiosis, which we have described in The Coming Transformation, reaches its apogee in the government space. Hard, zero-sum decisions present themselves weekly, and highly trained and experienced managers make million-dollar decisions as a matter of course. The best technology enables better policy analysis and trade-offs, while increasing the accuracy of, and reducing the time required to, pull data and crunch it.


Even small governments make for big customers. By revenue, many cities and counties would rank in the Fortune 500. These massive institutions, the number of them, and the need for productivity and technology gains means that extracting value is possible at scale.

The U.S. boasts 19,000 cities and towns, and twice that number of Special Districts. (Cities are typically general-purpose governments that provide a range of services like fire, police, library, and parks, whereas special districts are special-purpose governments that serve one function like the provision of water, sewers, or flood control). There are 12,000 school districts, 3,000 counties, and 50 states, each with hundreds (or thousands) of separate agencies and departments.

The United States has 50 states, 3,000 counties, 12,000 school districts, 19,000 cities and towns, 38,000 special districts, and tens of thousands of state agencies and departments.

The nearly $60 BN spent in the U.S. by these 80,000 state and local governments on IT will grow around the rate of inflation (3%+). Software sales will grow faster both nominally and as a percentage of the pie. Spending on hardware and consulting will shrink. Whether one looks to create a niche business or accrue a big chunk of the market, opportunities are ripe for software-as-a-service (SaaS) models, business intelligence, and waste and fraud prevention technology.

Equity opportunities may be significant for early employees and investors in major enterprise endeavors. (Opportunity costs for those focused on games, mobile apps, or new social networks may be significant as well). We see an additional element of social responsibility involved, however. Our society and the large institutions that direct its course suffer from a decaying IT infrastructure. New advances in technology make possible a reformulation of sprawling bureaucracies and their workflows. This will result in years of time-savings, improved decisions, and a stronger cultural fabric based on value creation and productivity gains.

3. Industry Pressures Demand New Efficiencies

Three cities in California fell bankrupt in 2012. In 2013, Detroit set the record for the largest Chapter 9 filing. With tax revenues just returning to pre-2008 levels, governments need to do more with less. Accordingly, products that can increase “top line” revenues or reduce “bottom line” costs will win customers and build value.

New technologies will enable cities large and small not only to produce insights from their own data, but also to compare spending trends to those in other cities. Performance benchmarks or “apples-to-apples comparisons” have been called the “holy grail” of municipal finance, because present capabilities force cities to call neighboring cities to gather data or hire expensive consultants to prepare reports that go out of date by the time they print.

In addition to comparative analytics, cities will take advantage of financial trend monitoring and drill-downs to the “checkbook level.” Imagine seeing not only a budget category, like uniforms for the fire department, but also the payments for the boots, pants, and belts. This will result in cost savings through comparisons with purchases from other municipalities and improved competition among vendors in bidding.

Immense technical challenges present themselves. Platforms will leverage natural language processing to map the ontology of charts of accounts (the financial structure of a government), machine learning to recommend quality comparisons and throw up flags for financial trend monitoring (“your reserve balances have declined for three years in a row — might want to check that!”), and rapid processing and searching of massive transactional data sets to answer questions on and find efficiencies in vendor payments (for example, to show all payments between $25,000 and $50,000 out of enterprise funds and help evaluate them against market metrics).

Initially, this type of technology saves time for government knowledge workers accessing and analyzing data. It can then grow into software that will save billions in the aggregate by improving decisions and offering intelligent comparisons and recommendations across the expenditure spectrum. The challenges require rare engineering expertise across a variety of subfields; the solutions will come from true technology companies, not large consultancies.

4. Challenging Sales Cycles Increase Barriers to Entry and Foster Customer Retention

Government purchasing processes are cumbersome. Governments frequently require “wet-signatures” on snail-mailed “hard-copies” of contracts. Vendors have to pay for business licenses, show proof of insurance policies, and file extensive (even notarized) disclosures. Organizational cultures reward risk-aversion and conservative leadership.

The weeks or months spent in the government sales process explains why so many smart technologists focus on the consumer space. Entrepreneurs launch start-ups so they can avoid bureaucracies. But this gap between consumer and enterprise in the startup world gives the best enterprise startups room to run.

In the mobile world, a startup might expect 5% attrition per month. In the government space, expect less than 5% attrition per year. Provided one keeps improving, serving, and building value, “once you’re in, you’re in” and customers may stay customers for years.

With officials recognizing the imperatives of innovation and embracing the Open Government movement in particular, a new generation of leadership will emerge. This leader, like many before her, is highly trained and educated. Yet she carries a tolerance for risk. She sees value in new technology, prizes its acquisition, and remains open to iterating on business processes. She champions innovation within the organization. And, by force of will and repeated wins (and mistakes), she infuses a culture of agile decision-making.

Managers like Jim Keene in Palo Alto and Joni Patillo in Dublin, CA; Finance Directors like Matt Pressey in Salinas and John Adams in Thousand Oaks, CA; and Mayors like Alex Torpey in South Orange, NJ and Mike Kasperzsak in Mountain View, CA demonstrate these qualities. These elected and appointed officials see value in cutting new paths based on better tools. They build trust in their communities and engage other administrators and electeds in the business of politics.

Most startups won’t find these visionaries. Most startups will wither and die for lack of deep pockets. Or they’ll just give up. Selling to bureaucracies often requires creating a network effect, because so few purchasers will go near the bleeding-edge. This is why “red tape” actually excites us with respect to the business we are building at OpenGov.com. The bureaucracy obscures the changes taking place, makes it hard to find the early-adopters and reach critical mass, and ensures that winners take all.

Other important industries promise similar problems and opportunities. In finance, for example, Addepar has battled its way into elite institutions with the promise of improving the financial reporting landscape. Other success stories are emerging in energy, education, healthcare, logistics, and construction.

The right path for a startup-company in an old-line industry is arduous and immensely rewarding. Conventional wisdom says that it’s too hard to build a business in government (or other major industries), and this has kept many from trying. Grand outcomes await for those top young companies bold enough to venture and win.

Zac Bookman
CEO, OpenGov
Advisor, 8VC

Joe Lonsdale
Partner, 8VC

Platform Plays

Joe|June 1, 2013

“If you don’t have a competitive advantage, don’t compete.”
– Jack Welch

How does one build a defensible business? In today’s startup ecosystem, where seed financing is abundant and the barriers to building scalable IT tools are steadily diminishing, the question of how to maintain a competitive advantage is one that must be at the top of every entrepreneur’s mind.Over the past 15 years the consumer space has consolidated around a few massive companies: Google, Facebook, Apple, and Amazon. Even in the face of tens of thousands of would-be competitors with low distribution costs, these players maintain large, loyal user bases and consistently generate billions of dollars in revenue. They accomplish this by strategically controlling the most valuable commodity in the Twenty-First century economy — information.

There is still a massive untapped opportunity to build these kinds of data platforms in the enterprise space. Today, most enterprise IT businesses continue to rely on linear-growth, relationship-driven sales, and payment-for-product monetization models. Owning workflows, not data, is their strategic goal. The largest players in enterprise IT are worth tens of billions of dollars, yet the gap in capabilities between enterprise and consumer software grows wider every year. This is an unsustainable paradigm — one that will be resolved by entrepreneurs who understand and apply the key lessons from the great consumer wins of the last decade.

In The Smart Enterprise Wave, we discussed how an explosion in the size of data sets is overwhelming the antiquated systems of enterprise IT incumbents. New technology solutions are emerging to provide more powerful tools to knowledge workers in major industries like Finance, Healthcare, and Business Services. Owning customer workflows is still essential, but as the core technology behind enterprise and consumer software converges — and as the key value of enterprise software becomes the ability to aggregate and leverage data as opposed to automating basic tasks — a high-touch sales force will become less relevant to business success. In the world of Smart Enterprise, the main imperative for software businesses is to capture information — and thus users — by building defensible product platforms.

Already, we are seeing a preponderance of innovative young companies utilizing data to make enterprises more efficient. We are excited by this development — which we take as an early validation of our thesis — but we caution entrepreneurs breaking new ground to think carefully about whether their product and business strategy is truly defensible. Many companies are building useful tools that will undoubtedly save customers time and money. However, without control over the underlying data these “enterprise apps” are destined for a life that is nasty, brutish, and short. The only way to escape this Hobbesian world is to become the platform that owns the users and the data — the infrastructure upon which the ecosystem is built.

Detailed below are some lessons gained from our partners’ years of experience building technology platforms, as well as some common strategic mistakes entrepreneurs should avoid.

Joe Lonsdale
Partner, 8VC
Founder, Palantir and Addepar

Jon Hollander
Senior Associate

Key Aspects of an Enterprise Data Platform

1. Transforming Workflows and High Engagement.
Disruptive technology platforms become an essential part of an individual’s daily workflow and cannot be easily replaced. The product’s benefits must be transformative, not incremental (i.e. minimum of several hours saved per week per user, or gross margin improvement of 15% or greater). The best way to track success here is to closely follow product engagement metrics, such as number of visits per user or average time spent per week using the product. Having this kind of direct connection also enables platforms to turn their users into a valuable asset for third party developers. Traditional enterprise middle-ware and backend solutions don’t have these innate features and should be avoided.

2. Generate and Capture Proprietary Data.
In the Smart Enterprise world, Data Is King. Having proprietary data that is user-generated and owned by the platform is becoming a pre-requisite to building a defensible business. LinkedIn, for instance, encourages users to publish content about themselves that cannot otherwise be found online. This pulls other professionals (and recruiters) onto the platform. The data is also highly structured, giving it valuable second order applications, such as targeted advertising. The most successful platforms will be open to third party development, but in order to be valuable, consumers and businesses must be forced to come to you for data that they cannot get elsewhere.

3. Network Effects and Infrastructure.
The value of the platform (to the end user) should grow with the number of users in a virtuous cycle that encourages adoption virality. Ebay, Microsoft Office, and Visa are all classic examples of this phenomenon. As a general rule, a system that controls the reciprocal exchange of information, goods, or money will tend to gain network effects. The largest and most enduring Smart Enterprise platforms will likely have B2B marketplace and communication/collaboration features at their core. Enterprise applications that leverage data and user engagement to act as infrastructure for a robust third party development ecosystem will also tend towards winner-take-all dynamics, as occurred with the Microsoft Windows operating system.

4. Owning the End Consumer.
The trend of the “consumerization of the enterprise” is not just about designing better user interfaces for employees; it involves engaging consumers directly, since they are a valuable source of data for companies. This phenomenon will become particularly apparent in Healthcare, Finance, and Government. Smart Enterprise software will change the dynamics of enterprise-consumer interaction by bringing the two parties onto the same data platform. For instance, consumers might use an online tool to track their health information and set fitness goals. Physicians could then utilize this data to monitor their patients’ ongoing health, while insurance companies are able to reduce claims by offering premium discounts to consumers who exercise regularly.

5. Building a Brand.
Winner-take-all-players often become brands that perpetuate their market position. This becomes especially relevant once you move outside of the early adopter subset and into the mass market. Professionals (especially in Medicine and Law) often place a high degree of importance on a product solution’s status as “the gold-standard”, or trusted authority. There will undoubtedly be Smart Enterprise content companies that leverage new analytical and data collection techniques (such as using mobile devices to crowd-source consumer good pricing data in the developing world) to build the next-generation of defensible content businesses to compete with existing brands like Nielson and Thompson Reuters.

Common Pitfalls & Signs of an App, Not a Platform

1. Sales vs. Product-Driven Leadership.
Successful technology platforms require a degree of long-term planning and vision that sales organizations are not well suited to deliver. Sales teams can be great at building a market for a new technology, but as customer needs evolve beyond linear software tools and SaaS pricing models shorten commitment periods, product and data strategy will become a critical part of gaining lock-in and winning a space. Box, for instance, is using a sales team to gain ground in enterprises, with the intent of scaling back these efforts once it achieves critical mass in specific industry verticals. LinkedIn also relied on an early sales team to jump-start engagement from recruiters and companies, which increased adoption by professionals and strengthened the data platform.

2. Product Only Ingests Public Data.
The novel acquisition of public data can be an effective way to create an initial value proposition, but it is not defensible over the long term. We have seen many enterprise applications pull in data from social networks like LinkedIn and Twitter and then run analytics on it — “machine learning”, “semantic analysis”, and “natural language processing” are the new buzz words of this current technology wave. This might be a “Big Data” play, but the critical question that must be asked is where is the defensibility? If the product is simply pulling in the same data that anyone else can extract via public APIs, what stops another team from doing the same thing incrementally better?

3. Reliance on Technology Over Strategy.
In today’s competitive environment, technological prowess is a pre-requisite to business success. However, technology is not a defensible attribute over the long-term. Technology (such as a more intelligent data parsing or prediction algorithm) can help create an initial value proposition, but given the current velocity of innovation, the competition is never that far behind. Software patents don’t hurt, but they shouldn’t be considered core to the business model. Ultimately, unless you capture valuable proprietary data or become an irreplaceable part of the customer’s workflow, you have not achieved defensibility. Historically, the most successful companies — like Google or Apple — use technology to create disruptive value but then quickly build a defensible platform and network around it to protect their position (such as app ecosystems reliant on the platform’s proprietary data).

4. Claims That “Data Scale” Is a Platform Effect.
Many companies — especially tools that rely on prediction and recommendation algorithms — will claim that by increasing the volume of data being captured by their application, they will be able to use machine learning to improve product quality and gain an edge over the competition. Scaling data is certainly important, but once you hit the point of statistical significance we believe the advantage tends to wear off and you need other elements of defensibility — like proprietary data or network effects — in order to win a market. The exception may be in networks where a high degree of value is created by outliers (such as in scientific or medical research communities) and it is important to capture the long tail.

Joe Lonsdale

General Partner, 8VC

The Smart Enterprise Wave

Joe|January 1, 2013

“One must put themselves in the path of giants.”
– Lillian Cauldwell


Over the last hundred years, five major trends have dominated Silicon Valley (SV): “Electronic Tools,” “Semiconductor,” “Enterprise,” “Telecom,” and “Consumer.” A sixth trend has emerged. We call it “Smart Enterprise.”

The Smart Enterprise wave will disrupt nearly every major sector of the global economy and dramatically improve productivity within those sectors, because it disrupts non-linear decision-making processes that are central to how major industries conduct business and create value. These decision-making processes have been complicated over the last two decades by the vast growth of digital information. In the past five years alone, the amount of data in existence has grown nine-fold, to over 2 trillion gigabytes. This increase has brought a corresponding increase in data complexity, formats, and silos that require sophisticated technology platforms to help knowledge workers process and leverage the information effectively.

Emerging Smart Enterprise platforms represent a significant investment opportunity. Companies can now measure, analyze, and aggregate large data sets to inform mission critical projects. Examples of digital data that were not previously accessible include energy consumption and production data from sensor networks; data on government expenditures and transactions; exposure and transaction data from institutional and private wealth portfolios; genomic IT data and information-related outcome analysis in healthcare; logistics and network distribution information; and personalized education data on student cohorts. At 8VC, our investment thesis involves identifying, building, and investing in the most value-creating platforms, especially in these industries with inherent winner-take-all dynamics.

Old Enterprise to Smart Enterprise

Companies like Oracle and SAP led the first enterprise wave by streamlining back-office processes to make corporations more efficient. Enterprise software helped push paper faster and speed up routine business tasks; think of “TPS reports” from the movie “Office Space”. Large, big-box software solutions streamlined the “assembly line” and brought basic automation to linear processes, such as payroll, accounting, supply chain and inventory management.

Although pioneering in its time, innovation in this space grew stagnant. Existing technology infrastructure is ill-equipped to address the novel information challenges that major industries face, making the process difficult and error-prone to append new features and add-ons. Clunky and dysfunctional user interfaces demand lengthy employee-training sessions and CTOs pay IT consultants large contracts just to create reports from the data. Implementation of the systems themselves can take months and sometimes years. The biggest companies devote much of their resources to sales and marketing efforts rather than serious innovation. Perhaps for these reasons, Y-Combinator once wrote: “If you don’t think you’re smart enough to start a startup doing something technically difficult, just write enterprise software.

In the Smart Enterprise space, companies are re-inventing and replacing the decades old technology infrastructure behind major industries. To accomplish this, engineers are solving hard technology problems involved in integrating disparate data into conceptual structures that knowledge workers can intuitively access and manipulate. Valuable, machine-generated data resides in diverse sources: databases, excel spreadsheets, and other unstructured forms on the internet. By unlocking the patterns in and usability of the data, knowledge workers will solve problems the creators of the software did not even foresee. For example, in the intelligence community, analysts can complete complex tasks — like tracking international moneylaundering schemes or re-building communities in war-torn areas — that require connections across networks informed by structured and unstructured data. The same goes for global bankers, multinational lawyers, retailers with distributed supply chains, medical researchers, and other professionals who face complex challenges.

Defining Smart Enterprise

1. Integrate heterogeneous big data and empower knowledge workers to solve non-linear problems.

2. Leverage recent IT advances — chiefly from the consumer wave — to solve critical challenges in major industries.

3. Potential to harness network effects within industry verticals and become platforms, increasing innovation by enabling novel applications to quickly spread throughout the industry.


Platforms typically begin as useful applications to solve single problems, such as electronic healthcare records, student information services, or energy consumption reduction. As the platforms gain access to increasing amounts of data, the owners of the platform may build additional applications and eventually an open infrastructure to allow third party developers to innovate as well. These vertical platforms can enable application developers to reach tens of thousands of users without having to re-create the application for each medical office, school system, or energy grid.

At present, for instance, if a developer builds a market-changing technology to improve operations at a municipal water facility, the facility owner can apply the product in that locale only. However, developing a standardized platform across water districts will exponentially increase the platform’s value, by simplifying complexity in huge networks of information. For another example, consider the mobile space, where extensive software and hardware ecosystems have grown around the Android and iOS platforms. An iOS developer can build one application and potentially reach over 400 million iOS devices.

This openness pushes new waves of innovation as go-to-market costs plummet for application developers. The owners of the platforms, in turn, capture winner-take-all dynamics. In major old-line industries, where incumbent players feed off of closed infrastructure, market shifts will be especially pronounced for those smart enterprise technology companies able to insert themselves into the technology infrastructure and integrate disparate data sets.


The major enterprise industries, including government, energy, finance, healthcare, and business services, comprise 70% of industry value as a percent of GDP. Each of these industries suffers deep inefficiencies. To see some of these problems and the solutions underway, consider the following examples from companies in the 8VC portfolio and investment pipeline.


Problem: State and local governments spend more than $30 billion on old enterprise software, built for the paper environment. Knowledge workers cannot derive insights, ask relevant questions, or manage information flow. Sometimes they cannot even tell how much money their entity spends. As a result, cities across America find themselves in financial crisis — in California alone, three cities filed for bankruptcy in 2012.

Solution: The platform being built by OpenGov allows governments to visualize critical financial data; analyze the data to flag waste; perform cross-city comparisons and benchmarks to find best practices and new efficiencies; and share financial transactions and budget colloborations to improve transparency and workflows.


Problem: Energy consumption in developed and emerging markets continues to rise while production becomes more challenging. As easily accessible sources are depleted, producers must target more technically complex fields to extract natural resources. For example, more than 50% of original U.S. oil reserves remain down hole leaving 100 billion barrels ($10 trillion) which are not economically recoverable today.

Solution: Equipping production wells with sensors and big data applications could drive 100% improvements in efficiency and extraction. Through novel sensor technology and software, NeoTek optimizes production and reservoir models to overcome the problem of leaving much of the oil within the reservoirs behind. Taxon Biosciences utilizes a proprietary bioinformatics approach to develop and identify microbial species that accelerate the conversion of unconventional energy sources (heavy oil, coal, shale oil.) to natural gas.

Financial Services

Problem: Private wealth management firms spend more than $10 billion to separately create and maintain their financial aggregation, reporting, and analysis infrastructure. Innovation is slow because no single platform exists. Millions of people receive PDFs from funds and manually enter data into their systems from a variety of schemas, causing confusion, enabling fraud, and inhibiting sophisticated analysis. itinfrastructure

Solution: Addepar is building an open platform to help investors access and understand their information. Addepar aggregates disparate sets of data, reconciles and augments that data, and provides best-in-class analysis and reporting for large private banks and registered investment advisors (RIA). For the first time, investors see all their data in real time, allowing them to perform lightning-fast analysis to address concerns while they are manageable and relevant. As an open platform, Addepar will foster an ecosystem of applications and fundamentally change how a large segment of the financial sector sells products and services. For example, a company selling tax deferral insurance products could write an application for the platform to empower an advisor to see exactly which of his clients could save money with its products and how it would work. Rather than being re-written and customized for every RIA or family office, an open platform allows the application to automatically and intelligently manage trillions of dollars of capital.

The IT infrastructure that runs major industries has been kludged together in pieces in vain attempts to keep up with the demands of big data analyses, and is ready to be replaced.


Problem: The healthcare industry remains largely paper-based, and current systems are ill-equipped to handle transformational innovations, such as electronic medical records, cheaper testing solutions, and full genetic sequencing for individuals.

Solution: Innovation from startups like Health Tap, Palantir, and Practice Fusion may save hundreds of billions of dollars, by bringing data and doctor interaction online and then enabling patients and doctors to make informed decisions. Leveraging these interactions and data with insurance companies and healthcare organizations will add massive value per patient and simultaneously lower costs.

Business Services

Problem: Although many functions, such as sales, recruiting, and business development, have transitioned into the cloud, data analysis still requires manual collection and input. Volume, accuracy, and timeliness of information are compromised in the process, which reduces the value of the information in these digital systems.

Solution: RelateIQ is transforming the CRM space by building a technology solution to collect data automatically from available sources to enable intelligent insights for sales, recruiting, investor management, and other critical business pipelines. With access to communication data within and between organizations, RelateIQ leverages advances in data science to create advanced, real-time collaboration tools to dramatically improve key business functions.


Startups will play an important role in the Smart Enterprise wave. This is not obvious to many outside of Silicon Valley. For most of the twentieth century, innovation came from large corporations, including places like Bell Labs, GE, Xerox PARC, and HP. Those companies invested large sums into innovation; because innovators had to build everything from the ground up, large corporations were among the few entities that could afford to outfit competitive technology teams. They also supported cultures that attracted brilliant people. But the financial cost to innovate has decreased in the last few decades, and it continues to fall. Today’s computers and software systems support rapid conceptual iteration orders of magnitude more powerful than those at the disposal of scientists at Bell Labs. In an inter-temporal hackathon competition, a couple of today’s top engineers would run circles around a team of top talent from 20 to 30 years ago, in any area and at a fraction of the cost.

Technology startups maintain other advantages. Incentives in a focused technology culture are better aligned, because the upside for a particular project is shared among the value-creators. Smaller teams can also maintain more nimble development cycles, flexible work environments, and an absence of politicking and bureaucracy. For these reasons, Smart Enterprise startups attract the top talent now. Palantir, for instance, is regularly cited as attracting the top engineers and other companies like Box, Addepar, and RelateIQ attract top engineers as well.

Given this powerful dynamic, many talented young technologists and entrepreneurs sense the startup opportunity and write off large corporations completely. This is misguided. The global marketplace is an evolving ecosystem, with startups and large corporations playing increasingly complementary roles. To address the world’s hard problems and drive progress, startups need corporations and corporations need startups.

Corporations have scale, existing relationships, and distribution advantages in large, established industries such as energy, education, healthcare, logistics, financial services, and government services. Corporations also possess latent knowledge and expertise by virtue of past work on major problems. They may know better than startups the next complex, valuable problems likely to emerge. Accordingly, and notwithstanding that they may have an advantage on the innovation side, many Smart Enterprise startups would do well to partner with large corporations that control the data, the knowledge workers, and the distribution channels. These partnerships will prove especially valuable in industries that require significant upfront capital investments.


Despite crises in governments and other important institutions, we believe that the Smart Enterprise wave will fundamentally disrupt key sectors of the economy and enable a prosperous 21st century. 8VC invests in new technology platforms that transform how critical industries tackle increasingly difficult challenges. These emerging platforms will re-invent the core intelligent infrastructure of major industries and create out-sized economic value for those who use the platforms, create them, and invest in them. As Smart Enterprise platforms become widely deployed over the coming decade, entrepreneurs will shift their effort toward developing applications on these vertical platforms. Platform-enabled application ecosystems will positively impact global productivity and growth.

At its core, innovation is about solving hard problems that matter to the industries that run our world. Startups will solve these problems. But they, and those that support them, will succeed by understanding the industries dominated by established players and, in many cases, by learning how to work well with industry leaders to solve hard problems and scale the solutions. For their part, large corporations must partner well and share the upside with innovative Smart Enterprise companies, or they will fall behind.

We have many reasons to remain hopeful and must work together to solve the world’s biggest problems. More people aspire to entrepreneurship today than at any point in the past century. Costs to innovate have plummeted. Engineers have the opportunity to build and focus their talent and energy on major global problems. Together, we will confront difficult technology challenges to help knowledge workers operate more efficiently within the largest industries. These tasks are worthy of our top entrepreneurial and engineering talent, and it is the role of the top technology funds to support and nourish these emerging ecosystems.

Joe Lonsdale
Partner, 8VC
Founder, Palantir and Addepar

Angel Investing

Joe|July 1, 2012

“Aut viam inveniam aut faciam.”
(I will either find a way, or make one.)
– Hannibal

Dear Friends,

Please see the attached notes on seed-stage or “angel” investing. I hope this document proves a useful guide and perhaps it will help you avoid a mistake, especially those of you in New York where the technology-investing culture is taking off.

As many of you know, my current fund, Formation | 8 Partners, focuses on early-growth investing. This investment mandate offers the best risk-reward, because my connections in LA and New York and those of my partners with Asian Conglomerates add the most value to early-growth stage companies. Yet, because access to growth companies does not happen automatically, my fund also allocates a portion of its investments to early stage companies. These seed and series A rounds create optionality to gain access to some of the best early-growth deals.

Early-growth investing and angel investing present different challenges. At the early growth stage, one can measure the existence of a strong technology culture and see other business metrics before success is priced in. The business fits into its ecosystem, engages customers, and builds distribution channels. An investor may even gain a feel for what margins might look like later. Put simply, growth investing involves real businesses that show early signs of greatness and traction. These are the most sought after companies and it’s a full time job to find access to them, invest in them on good terms, and give them advantages to make sure they win.

At the early stages, companies have overcome some market, technical, and management challenges, yet they still face obstacles in scaling and solidifying the early momentum. Investors do not know, and usually can’t tell, what margins, engagement, and distribution will look like. They may not even know if the product will fit the market. Fortunately, these factors are not dispositive for angel investing.

To see what truly matters, please open the attached document and enjoy. Please also feel free to ask me before investing in a seed deal. I’m happy to give you my feedback and I won’t steal your deal. In fact, such early investing benefits from collaboration and it’s a usually a positive sum game. Although the majority of seed investments underperform, it’s great for the technology ecosystem to have so many people involved. And it can be an exciting and high-return area if done with discipline and with the right deal flow.

Best regards,
Joe Lonsdale

Ten Principles for Angel Investing

1. Invest in the very best engineers. At least one of the founders should be a technologist. There should be more than one founder if possible. Founders should have a loyal early team that they have known or worked with before. Design cultures are very helpful, but engineers matter most. All the returns in angel investing come from the top companies and virtually all the top tech companies are built by the best engineers.

2. The team should have a concise, inspiring vision. The vision should be unique and ambitious. A smart person who hears about the company should get excited and want to be a part of it.

3. Salaries should be low and upside for employees should be high. This holds especially for the founders and the first few employees. If possible, see that great engineers are willing to come on board for low salary and high upside after the initial team. In Silicon Valley in 2012, low salaries means 40k to 75k. In New York, it might mean 50k to 85k.

4. Invest in a team that creates a top technology culture. In addition to the points just discussed, a) the company should be based in one place without multiple locations, b) people should work late at night and on weekends much of the time, and c) employees should generally display passion for what they are doing and near-obsession with their mission. Perhaps most important, an engineering culture means that engineers should determine the scope of the problem and the approach to solving it. The product guys should not dominate decisions, nor should the business guys. If the company consists of business guys trying to find an engineer to get something done or, worse, ordering engineers to build something, run.

5. The company should focus on a small, well-defined target market. The company should achieve a creative monopoly somewhere. If the team wants to conquer everything in a big area out of the gate, help them narrow it down. Attacking an underplayed or heretofore ignored niche in a large space allows the business to grow without sacrificing future market opportunity. All great entrepreneurs have an expansive bias, but they also know how to apply discipline to focus.

6. Great companies work on really hard problems. They take top technology cultures and expose them to a known problem in a valuable area of the economy. The idea itself is not the value. “Stealth” companies or those that don’t want to reveal their technology almost never win. Rather, teams that create new technological solutions, produce big insights every day for breakfast, and take on and solve really hard problems are the companies to bet on. Incremental improvements are not sufficient when investing in seed companies, because, by the time they reach market, incumbent technology may have improved enough to eliminate seed company advantages.

7. The best teams collect the best directors and advisors. A good company should attract top people from the industry to help it grow. If the company can’t raise money from key people in the industry, that’s a bad sign. Consider bringing in a friend from the industry to invest along with you as a bar.

8. Good teams honestly revise their timelines. Most teams constantly change their timelines and want to forget what they promised in the past. Almost all startups miss their timelines, but those that are honest and adapt and learn from their misjudgments outperform.

9. Don’t invest in me-too commerce, payments, deal-related companies, and media plays. These areas are over-crowded. Unless you have an unfair advantage on your side and know that you have found one of the very best teams in the world, back off. Similarly, don’t invest in tricks. Tricks may include companies in China giving distribution, special deals with a big pharmaceutical group or mobile phone company, or a patent licensing or litigation scheme. These methods may add advantages at the right time, but a company’s team and its principles are what matters early-on. Finally, always ask, “why is this deal coming to me?”

10. I will either find a way, or make one. Everything else aside, you are betting on their drive / determination to succeed … that is perhaps the most important quality, and as far as we know it’s an art to measure this. If you are the militant type, ask yourself: would I go to war with these guys at my back? Don’t bet on any team, or any fund for that matter, that is not obsessed and determined to prevail.

The Coming Transformation

Joe|June 1, 2012

“How can I live among this gentle obsolescent breed of heroes and not weep?
Unicorns, almost, for they are fading into two legends in which their stupidity and chivalry are celebrated. Each, fool and hero, will be an immortal”
— Keith Douglas, Aristocrats, 1943

The Decline and Fall of the American Aristocracy

The global economy will transform in the next decade. The present post-industrial economy, in which developed countries experience the limits of extensive growth, will give way to a digital global economy that requires different skills for workers and investors. Fortunes are at risk. Last-generation business models will collapse and a new generation of investors and entrepreneurs will create value across old-line industries through new trends in Information Technology (IT).

The Second Industrial Revolution serves as a guide for the disruption ahead. In the early 1880s, the British aristocracy, which controlled immense wealth built on generations of land ownership and agricultural production, felt assured of its economic dominance for generations. Yet by the mid-1890s, agricultural incomes had dropped due to increased competition spurred by improved transportation and production methods. Land prices fell precipitously, and fortunes collapsed.

Rather than keep pace with technological change, aristocrats bought land in Australia, Canada, and the United States. They used the land to pursue familiar business practices like cattle ranching, mining, and agriculture. Not only were economic conditions for these industries as bad, if not worse, overseas as in the U.K, but also cultural values so misaligned that, according to one commentator, “the Englishman” became synonymous with “inefficiency, unhandiness, inadaptability,” and “irritating, repetitious cocksureness.” By WWI, the aristocrats had lost hundreds of years of accumulated family wealth due to a basic ignorance of the forces shifting wealth up the value chain from landowners and commodity producers to industrialists with optimized manufacturing and operational systems.

In the present age of creative destruction, trillions of dollars will be lost by institutions and families that cling to the cornerstones of traditional wealth management practices. Those that survive and flourish in the coming transformation will leverage innovation, adapt practices to new standards, and address global challenges by applying new technology to the worlds of energy, finance, government administration, healthcare, education, and commerce. Businesses in which MBAs outnumber technologists, that reward age and connections over ideas and ethics, and that propagate the mindset that lawyers and consultants dictate value and deserve control face a painful decline. Product superiority will reign.

II. Understanding the Coming Transformation

Like the aristocrats of the nineteenth century, family offices and private wealth managers today hold wealth preservation as their primary goal. They seek allocation diversity, flocking to “safe” investments in big banks and large-cap multinationals. These investments are not safe. Ignoring Mike Markkula’s advice to Steve Jobs that long-term corporate survival requires continual reinvention or “metamorphoses,” most banks and large public companies adhere to business practices because those practices worked a generation ago. They fail to see that preserving wealth in the coming transformation will require family offices and private wealth managers to bet intelligently on a macroeconomic landscape subject to technological disruption.

Investors must understand the principal themes at work in the coming transformation. These themes include: (i) Open platforms that promote transparency and information sharing; (ii) a trend toward higher-level conceptual work and man-machine symbiosis; and (iii) applications that enable personalization and customization across business-to-business and business-to-consumer transactions.

1. Open Platforms that promote transparency and information sharing
Old-economy businesses from encyclopedias to airlines have depended for generations on fractured communications to preserve information asymmetries, skewed pricing, and limited choice. This will change. To see why, consider an operating system like Android, now the best-selling smartphone platform in the world with over 300 million devices in use and 850,000 activations every day. Instead of internal content generation, the system enables and encourages application developers to create and offer content on the Android platform. Handset customers choose among hundreds of thousands of applications, from Yelp to IMDB to Chess, which the platform owner (Google in this case) did not create.

iOS, Apple’s competing product, works the same way, although it is not quite as open. This will prove a disadvantage for iOS and Android will emerge as the dominant operating system (Android is expected to be operating 31.1% of the 1.84 billion smart devices by 2016, whereas iOS will operate 17.3% of the devices in 2016). These open operating systems compete with one another for users and for content. Companies like Nokia ignore this strategy, relying instead on closed platform operations. Closed platforms will lose. Capturing upside by boxing out competitive innovation cannot compete, whether in smartphones or in other systems, because open platforms will out-develop closed platforms.

2. Higher-level conceptual work and man-machine symbiosis
Increased conceptualization and abstraction will drive value to businesses that leverage high-level and abstract thought while decreasing reliance on rote work. Man-machine symbiosis, the idea that people drive strategy while machines calculate, will direct work according to comparative advantage.

Increasingly, machines do well-defined rote work better than people, but machines do not write code or articulate ideas better than people. J.C.R. Licklider articulated this idea in the 1960s: “Man-computer symbiosis is an expected development in cooperative interaction between men and electronic computers. . . . Computing machines will do the routinizable work that must be done to prepare the way for insights and decisions in technical and scientific thinking.”

This phenomenon has surfaced, and not just in the sciences. Palantir Technologies, for example, helps analysts in certain areas of finance and government spend 95% less time doing rote work, meaning that the best analysts spend more time iterating on their hypotheses and sharing results rather than manipulating spreadsheets in Excel, cleaning data, or writing code. Apple’s new app, Siri, which seeks to replace basic assistant work, provides a similar illustration. As people increasingly do what people do best, combined with machines doing what machines do best, value propositions change dramatically.

3. Applications to enable personalization and customization
Information technology that enables personalized solutions will turn twentieth-century mass production techniques into relics. This trend portends much more than the ability to pre-order a custom BMW (or modify it after market) or have initials stitched onto a French cuff. It means that rather than a single vineyard running a wine club and determining what bottle to send according to availability, a recommendation algorithm will direct a “hand-picked” bottle from a range of vineyards based on a detailed assessment of tastes. Programs will “learn” an individual’s interests and even basic decision-making biases — based on, for example, where one walks, drives, or flies, or who one connects with on social media platforms. That learning will inform target advertisements, suggest charities, and make vacation recommendations. As technology intelligently engages with consumers and purchasers based on personality, history, and loyalties, businesses will capture more of the long-tail. This is not the case just for retail; in industries as diverse as healthcare, wealth management, and B2B services, processing relevant contextual information will lead to tailored products and services that are far superior to those presently available.

These themes will engender social and political challenges, as well as investment risk. First, unemployment will rise as automation and off-shoring squeeze the middle class and as skills fail to match the needs of a changing economy. Income will move in a ‘sociological butterfly’ where the middle is hollowed and the very high-end and the lower-middle socioeconomic classes continue to grow. Global competition will keep unemployment and under-employment high for a protracted period, leading to disenchantment with markets, dubious legislative proposals to stanch job losses, and social unrest.Power players, like bank leaders, will seek to influence policy. Governments will accrue more debt. Countries that want to compete, including the U.S., will have to fight hard to keep a level playing field for new IT-enabled businesses to compete against established players who may argue that disruption brings unbearable political difficulty.

Second, and related, wealth stratification will grow by virtue of the high stakes — the fortunes created by new technology winners will be immense. Indeed, the present age is a sort of twenty-first century gold rush, in which technology entrepreneurs and their backers seek to claim the many platforms that should, but do not yet exist. More wealth will be created than lost as the economy becomes more efficient, but much of the wealth will reside in illiquid investments, not public equities. The most connected investors, those who work most closely with the best technologists and entrepreneurs, will reap outsized gains. This trend buttresses the likelihood of widespread disenchantment, political volatility, and social unrest.

Third, public and credit markets will experience continued volatility as new platforms and innovations wipe out established companies. Markets will not easily process the uncertainties, particularly where icons of twentieth-century technology, like HP and Kodak for instance, must steer massive organizations toward new business lines that leverage intellectual property portfolios and software development. The prospects for start-ups and young companies may engender optimistic valuations, subject to wild swings as the market receives product iterations and sales figures. As industries transform, major winners and losers will emerge over short periods of time and markets will rewrite valuations more rapidly than in the past.

Fourth, as certain types of information increase in value, the amount and severity of cyber attacks will increase. Nearly every Fortune 500 company has suffered data theft, and governments in particular are subject to compromise and scandal from a range of attackers from basement-dwelling teenagers to international syndicates like Wikileaks. With increased reliance on IT, companies will have to invest in costly protections. Prophylactic technologies will become cheaper, better, and more broadly adopted over time, but attacks also will grow in sophistication, perpetuating an arms race of sorts.

Fifth, as IT further integrates into our lives and traditions, views of privacy, community, and identity will transform. Individuals may enjoy less personal interaction, which will contribute to feelings of depression and isolation in society. Countries like Korea already deal with high gaming and online addiction rates. In one case, a man died in an Internet café after playing games for 50 hours. Distrust of, and disaffection with, technology may grow and may result in a cultural backlash against those who research, develop, propagate, and invest in technology. In August 2011, for example, an anti-technology terrorist group in Mexico sent a parcel bomb to two university professors at one of Mexico’s leading technical research universities. The group claiming responsibility cited Ted Kaczynski, the Unabomber, who advocated for the abolition of the industrial-technological age as their primary influence..Despite the challenges, the coming transformation will be worth its costs. Better technology will enable new types of connection, creativity, and insights that will radically elevate standards of living. As explained below, software, mobile, and Internet advances will increase outputs in energy markets while lowering costs and conserving resources, add to the efficiency of governments, democratize global finance while reducing risk, improve access and outcomes in global healthcare, create more equal and optimized educational experiences, and offer more opportunity for personal joy and satisfaction.

III. Drivers of the Coming Transformation

Given the prospect of volatility from both an economic and sociological standpoint, understanding the drivers of the coming transformation and the anticipated effects on old-line industries will help mitigate individual investment risk.

IT advances have created a possibility-gap in business process efficiency that is, in most major industries, larger than it has been since the nineteenth century. Workers and managers alike spend hours daily searching for information to which they should have ready, automated access — information like the strengths and weaknesses of various teams or performance statistics on certain plants or branches. The platforms and technology-driven processes missing from major industries are especially important in areas involving large amounts of information, like energy, finance, government, healthcare, and education.

In fact, the potential for efficiency gains is so great that relatively small companies with good IT, albeit lesser scale and fewer distribution channels, will outperform larger, more-established, and better-networked businesses. In some cases, larger businesses will purchase upstarts and integrate them effectively. In other cases, new technology, particularly in the software, mobile, and Internet spaces, will redefine the core of those businesses and their cultures, forcing a transition that few companies will make.

Software, mobile, and Internet technologies will drive the trends in open sourcing, man-machine symbiosis, and customization. As these technologies rapidly deploy, the most effective business processes will require them, fueling further expansion in these areas. Consequently, the most successful applications will be those that integrate the three elements.

1. Software and new enterprise
Many of the best investments of the previous generation have been in software and this will remain true in the coming transformation. New software will support connectivity and improve data analysis, visualization, and modeling, improving efficiency across industries and industry subsectors. Following these improvements, market volume will increase from nearly half a trillion dollars in 2012 to over $640 billion by 2015.

New enterprise software — software that enables conceptual work and new networks of collaboration — holds particular promise. Traditional enterprise software has focused on well-defined processes in areas that require little conceptual thought, such as payroll, reporting, accounting, and human resource tracking. Perceived as a boring space, the prospect of iterating on esoteric data-intensive problems for the back-office failed to attract the most dynamic engineers. But now, because pervasive inefficiencies in these sectors require dynamic solutions that call on disparate domains to facilitate high-level conceptual work, many of the brightest minds work on hard problems involving enterprise software for old-line industry issues. These complicated enterprise problems will involve tremendous amounts of data, engendering a related field of innovation known as “Big Data,” discussed further below.

Good software will connect concepts and topics from disparate networks. For example, the need for collaboration in the intelligence and security domain demands that software jump across networks and gather data rather than wait for communication from specific departments. Many companies now focus on these types of solutions. The solutions will continue to improve as more of a knowledge worker’s data becomes available in application programming interfaces (APIs) hosted in the cloud, including mobile phone data, email data, and work data. New enterprise software will hold relevance to senior employees driving core business lines, not just HR staff and sales assistants. And it will provide value across organizations to people dealing with high-level policy questions.

2. Mobile platforms
Mobile platforms will accelerate internet accessibility and enable instant and low-cost access to increasing amounts of real-time and localized information. As near-field communications emerge, and apps like Ness and Any.do build intelligent profiles of what consumers want, where they go, and what they do, mobile interaction with consumers and businesses will deepen. Advances first made in the consumer space will spill into the rest of the global economy and affect thousands of businesses. Personalized information can convince people to visit their favorite restaurant and it can notify officers of a suspect’s movements.

Total global mobile traffic will grow 26x between 2010 and 2015 (from .24 to 6.3 exabytes/month). Asia shows the fastest mobile adoption rates in the world, driven by increasing wealth and openness to new technology. In 2009, Asia Pacific was the world’s largest mobile market, representing 57% of global mobile revenues. The most technologically developed regions, such as Japan and South Korea, will see increased smart phone usage — a tenfold increase by 2016 — while less developed countries will see heightened mobile penetration. Many new technologies developed in the U.S. will look to enter these Asian markets. Those that do so successfully will take advantage of a massive opportunity: By 2015, the 2.14 billion mobile users in the Asia Pacific will grow to 2.89 billion, at which time one out of every two mobile users in the world will reside in that region.

3. The Internet
Internet advances have democratized pricing, eliminated middlemen, and reduced the need for capital intensive infrastructure in markets ranging from books to stocks¬¬. The Internet also serves as the enabling infrastructure without which mobile and new enterprise software cannot function. New networks also continue to grow on the Internet and add value.

The hottest areas involve the social and interest graphs. The social graph, which refers to one’s web of relationships, has been mapped by Facebook, LinkedIn, and other social networking sites. The interest graph is less charted. The term refers to one’s web of likes or interests — or, as with the company Backplane, the web of one’s influences or inspiration. Given the huge market opportunity to tap into what people care about, as opposed to only who they care about, many of the best engineers in Silicon Valley now work in this space. Whether one hunts terrorists or sells gelato, networks offer exponentially more relevant data than do nodes. On Facebook, for example, brands already target influential people and use them to generate “likes.” Whole ecosystems of companies have emerged around this, because the winners will improve marketing and advertising by orders of magnitude.

The personal and social data referenced above speak to the broader, rapidly emerging field of “big data,” in which technologists compete to capture, store, search, analyze, and visualize massive data sets. In addition to the social and interest graphs, exploding quantities of data from other disciplines, ranging from public health to demography and polling to logistics, demand exceptional technologies that can process the data quickly and gain insight into its patterns. Companies that can map the largest data sets into conceptual structures that enable fast, intelligent data-driven decisions will create tremendous value. Companies like Relate IQ and Blend Labs work to combine social graph technology with Big Data through the empirical quantification of communication events and other markers of relationships. These companies and many other emerging newcomers will transform personal lives and disrupt established business throughout the sectors discussed below.

Again, investors must watch Asia. Global revenues in the consumer internet space are forecasted to reach $1 trillon by 2020, and Asia will account for 35% of total global spending by 2015. By 2020, Asia will account for more than 56% of global internet users. This increased internet adoption will affect not just advertising, but also many aspects of daily life, including how customers interact with businesses, how buyers and sellers of goods and services find one another, how marketplaces set prices, how individuals use and store personal and professional data, and how citizens interact with governments.

To understand the power of software, mobile, and Internet advances on old-line businesses, consider the potential effects on the multi-billion dollar cement industry. Operating plants struggle with poor communications, weak analytics, and problems in pricing, certification, customer service, maintenance, and overall profitability. One particular problem concerns the limited life of mixed concrete (concrete must be poured within a couple of hours of saturation). Expired shipments waste entire truckloads. Sometimes builders use shipments despite the loss of integrity, causing future problems or regulatory exposure. With better tracking through mobile and software platforms, site managers can charge penalties for delays or use mobile incentives or gamification techniques to save tens of millions of dollars and increase quality. Cloud-based applications will process operating data and web-based mobile applications will distribute timely information, improving efficiency and preventing disasters like the Big Dig in Boston. Targeted applications will improve communication by linking drivers, site managers, dispatchers, and mixers. Pricing will grow more accurate and personalized as customer and job information assimilate. Better data analysis will streamline manufacturing and distribution.

Similar developments in data management, analytics, information transfer, and process improvements will remake the worlds of energy, finance, government administration, healthcare, education, and commerce. In the next generation, these market segments will flatten the information landscape and gain in efficiency and cost savings, stability and security, processing power, analytical capabilities, network communications speed and depth, storage and automation, and functional abstract computing.

1. Energy
Given the size of the industry and rising demand, the energy sector holds the most potential for adoption of high-impact IT innovation. States increasingly recognize, particularly in the Asia-Pacific region, that economic stability and growth require optimization of current power assets and new energy. The main opportunities for addressing these needs involve technologies that 1) increase efficiency of existing energy infrastructure; 2) improve energy generation through better exploration or alternative sources, and 3) create and improve methods to store energy.

Nowhere is the need for energy innovation more pressing than in large cities. Urbanization in equatorial and other warm-weather regions will strain the energy supply. Cooling demand in metropolitan Mumbai, for example, is equivalent to 24% of the cooling demand of the entire U.S. The standard solution to increasing energy usage has been weak legislation or public service announcements imploring people to conserve. Better IT will enable more effective solutions. Office buildings will receive real-time alerts to spark short-term adjustments, like minimizing cooling and lighting during off-peak times. Automatic sensors will shut down home electronics accidentally left on. Drivers will receive up-to-date notifications of open parking spaces or uncongested roads, reducing traffic and corresponding emissions. Smart grids will analyze and respond to energy demand moment-by-moment, optimizing plant usage to reduce both cost and outages. Smart meters will provide consumers and utilities with accurate usage information, allowing utilities to set prices that more accurately reflect demand. Consumers will benefit from concrete savings analyses.

By 2020, South Korea will have erected the first “smart city,” Songdo. By 2030, total global energy infrastructure will have undergone a $20 trillion transition. Operations management necessitates strong IT, including platforms to monitor, analyze, and control power generation, distribution, and consumption; dynamic pricing models; and automated responses to system disruptions to prevent widespread outages and security scares. Distribution and grid operations will benefit from new IT platforms that will make existing energy technology infrastructure more productive and lower-cost due to improved data analytics, process optimization, and intelligent communications systems. Exploration, production, distribution, and consumption will benefit by virtue of IT advances that bolster and coordinate information flows using sensors, pulses, measurements, and statistical analyses.

2. Finance
Several million people in the financial sector spend significant time on data entry and basic data manipulation that can be done by computers. Fraud and error-rates are high. Transparency is low. Few institutions know exactly what they own and entire banks face collapse because they cannot evaluate hidden risks. Indeed, many of the worst-run firms would have been destroyed by the latest financial collapse were it not for government intervention. Open platforms and superior technology that helps information, products, and services reach needy customers with the fewest middlemen will overtake these decaying institutions.

Consider the private wealth management space, where more than one million workers manually enter information on capital calls, distributions, K-1s, and other communications between financial parties. Given the predictable ontology of this type of information, systems should talk to each other directly rather than rely on expensive and error-prone human data entry. Given multiple currencies, different asset classes, and different financial product structures, family offices and large institutions manage only limited portfolio analysis. Companies like Addepar offer open platforms to increase transparency and improve analytics. Open platforms aggregate data on a massive scale, facilitating holistic portfolio views. They also allow application developers to address a multitude of specific problems, like options pricing or currency risk, providing long-term value to customers. Reducing opacity will have spillover benefits for the industry, reducing the potential for fraud and democratizing information that will empower families and small investors in comparison to large institutions.

3. Government
As in the financial industry, the government administration and security realms rely on closed platforms with slow back-office processes and excess manual data entry. Because market-based mechanisms are limited in government, disruptive technologies must be an order of magnitude better than established competitors and they must provide solutions on a grand scale where either lives or billions of dollars are at stake. These issues come together in defense, a place where Palantir Technologies has prospered by providing platforms that connect disparate databases and provide advanced analytics to improve intelligence and transparency.

Other areas of government, particularly in state and local administration, sacrifice hundreds of billions of dollars to poor accountability and fraud. New software platforms and technology solutions will address these areas, providing holistic solutions to improve accounting, data management, and interaction between and within agencies and stakeholders. Moreover, as the paradigm in government technology solutions shifts from service-created to COTS (Commercial-Off-The-Shelf), solutions are more easily compared and the best technologies stand a better chance of dethroning old practices.

4. Health Care
The healthcare industry needs new technology platforms to share information and improve outcome analysis. Most high-level medical professionals still spend much of their time doing rote work. In fact, early electronic medical record (EMR) companies may have made things worse in healthcare in that doctors spend more time entering data and parsing details. Improved IT will free doctors and other professionals to deal with higher level conceptual work — the exceptions and unusual cases — while other forms of treatment and interaction will be pushed down and even automated.

Imagine a world in which a nurse works with a patient to enter in the patient’s key background information, and then a computer spits out a diagnosis: 87% chance the patient has the flu, 10% chance the patient has a certain type of fever, and 3% chance the patient has a more serious condition. The program may then cross-reference the patient against similar patients and ask the nurse additional questions missed in similar situations in the past. The computer compares the patient to others in the area and others across the world who, for example, had been pregnant recently and had a bad flu within the last three years. After this analysis, the computer spits a series of recommendations. A highly-trained doctor could review, modify, and approve the recommended steps. Eventually, doctors will attend to only the exceptional or unusual cases, the sort that require high-level conceptual ‘detective’ work. Companies presently work on technologies like this, and the savings will revolutionize over-strapped and under-resourced medical systems.

5. Education
As in healthcare, technology will allow educators to spend more time on high-level problems, such as research and curriculum development. Technology will also facilitate personalization. Companies following traditional enterprise models have failed in the education space, because good education requires engaging students at a conceptual level, on terms directly relevant to their interests. But software development has started to show capabilities in intelligent personalization that involves flexibly dealing with high-level context versus easily repeatable, well-defined processes.

Networks such as edModo, Shmoop, and Piazza have access to, and increase, collaboration among millions of teachers and students. Airy Labs, Ntelligent, and others use gamification to engage students in new ways. They also try to map the ontology of learning to enable personalized challenges that come from precisely measuring students’ skills. As these early efforts collect data, the technology will network to target and deliver content for each student. A technology-empowered educator will focus on a child’s weaknesses, while also gearing advanced study materials for her math prowess. These materials will interest her and engage her mind based on what she enjoys studying, say, nature, science fiction, and logic. Parents and educational institutions will pay substantial sums for technology that helps children excel in multiple aspects of their education.

The general trends in man-machine symbiosis apply. As with a doctor and patient in medicine, teachers will deal with exceptions and with iterative areas too complicated for computers to understand. The human touch will remain critical, and indeed increase in value, to complement the computer-aided educational experience. Presently, the industry suffers from weak infrastructure, incompetent IT support, and thin technology cultures. But as evidenced by initiatives at top universities to put classrooms online and by the growth of for-profit learning in general, these factors are changing. Professors and educators will focus on research, its applications, and training that requires hands-on instruction, while rote learning and numerous forms of basic instruction will be placed online or in modes of automation.

6. Media and Commerce
Media and commerce will continue radical change on the backs of companies that use technology to aggregate customers, disseminate virtual goods, improve in-app commerce, and provide access to local, personal, and real-time discounts and trends. The advertising domain shows a $50 billion dollar gap in the amount of time spent on a mobile device relative to the money spent on advertising. In entertainment, the avenues for expanding content are burgeoning–mobile entertainment grows near 20% per year and it’s expected to reach $54 billion by 2014. In retail, everything is changing. Between 1991 and 2001, U.S. retail growth maintained a 4–5 percent rate. Since Amazon.com turned its first profit in 2001, U.S. old-economy retail has grown only 1.2%, while online retail grew at close to 20% per year in the same period.

To see the reach of some of these trends, consider the impact on charity fundraising, which has been revolutionized by social networking and also mobile applications that allow for text-based donations. ONE HOPE, for example, enables charities to use its site for free to raise money with a modern point-based engine for supporters, and to use wine products as one way of doing so. Through its site, ONE HOPE gives wineries access to its national charitable networks and offer wine to millions for good causes. Charities get upside and consumers get upside; middlemen lose. With online wine sales growing steadily at over 35%, distributors and retailers should be scared. ONE HOPE even works with distributors to change the technology available to them and give them a better lock-in and value-add to retail locations with inventory management and a deal interface when it takes its brand offline.

This example speaks to the larger alcohol industry. Major distributors still reach retail and restaurants manually through face-to-face sales relationships. Distributors do not employ real-time inventory tracking and they do not use customer relationship management systems. Buyers regularly pay premiums given the inconvenience of comparative pricing. Software and enterprise platforms will remake this entire vertical, and many others like it from fashion to furniture.

IV. Navigating the Coming Transformation

To successfully navigate the coming transformation, investors must heed two important principles. First, risk-reward favors the valuable areas over the popular areas. Valuable areas include areas that remain nearly untouched by recent technology advances — massive old-line industries plagued by systemic problems and deep operational inefficiencies. Popular areas are areas in which a multitude of competitors fight for copycat victories in subsectors of industries already changed by technology and the success of companies like Amazon, Facebook, Groupon, and Zynga.

To understand the popular areas to avoid, consider the areas in which the majority of talented young programmers work, such as communications, billing and payments, consumer investing, and gaming. Companies that garner attention in the press create copycat entrants, as is the case with social networking, deals sites, and local business analysis and support. To understand the valuable areas to seek out, consider the spaces still run by older executives uninfluenced by technology, like oil and gas, banking and financial services, government administration, medical practice and healthcare management, and secondary and higher education.

Along with investors, many technologists remained charmed by popular areas and choose to focus on first order problems, while failing to understand the back-end infrastructure and difficult applications of IT to business processes that make companies like Amazon successful. Investors and technologists often yearn to enable new ways for people to interact or see advertisements, but they ignore superior platforms in areas of industry like shipping or security or debt that will make the economy more efficient and solve hard global challenges.

The best entrepreneurs and investors will ask the right questions: What areas are worth billions of dollars and are important for our society, but do not currently employ advanced IT? What major areas of the economy are frustrating to work in when compared to how those areas should function?

Another important principle, and perhaps the least understood aspect of the coming transformation, is the critical element strong technology cultures. Running a business to take advantage of optimal processes enabled by advances in IT requires a meritocracy where engineers work for upside and control important parts of the company. Businesses frequently ignore or refuse to make this transition even as they are outcompeted and eliminated by new competition. Investors also fail to measure and appreciate the importance of this variable. An early-stage technology company not run by the most talented engineers has little chance of becoming a disruptive billion-dollar business. Many investors do not come from a top engineering culture and this will differentiate the elite.

The importance of a technology culture carries meaning at the macro level in addition to the corporate level. Although growth in U.S. markets may wane, the U.S. still produces the world’s best innovation because it maintains the best entrepreneurial ecosystems. Communities like Silicon Valley or Cambridge combine university research, funding, expertise, technology, and entrepreneurs in a swirling mix, valuing ideas over established hierarchies. These ecosystems will engender hundreds of new networks and platforms across global industries. On this scale, a technology culture represents the opposite of the mindset among the British aristocracy before the second industrial revolution. Wealth will not be “preserved” through “safe” investments. Technology cultures, well managed and fostered, will push expenditures on software, mobile, and Internet technologies to fill efficiency gaps in the old economy. And the creative destruction wrought by companies possessing the right mix of superior technology, market knowledge, cultural understanding, and execution will measure in the trillions of dollars.

As Henry Kissinger said: “History knows no resting places and no plateaus.” This applies to investing, where companies must create value and create it anew. The British aristocracy lost its wealth and power through complacency and a failure to adapt to coming change. America’s aristocracy will lose its wealth by virtue of a similar complacency and a similar failure to adapt to changes wrought by IT innovation. Many investors know that the world around them is changing, but they do not have the tools to translate that awareness into successful investments. A few investors, those most connected with the robust technology ecosystems that foment the changes and those best-versed in the hard and soft qualities that make an outstanding technology company, will understand the factors that expose an industry to disruptive technology. And those investors will create, and benefit from, these immense disparities.

Joe Lonsdale
Partner, 8VC
Founder, Palantir and Addepar

Zac Bookman
CEO, OpenGov
Advisor, 8VC

Lessons from Peter Thiel

Lessons from Peter Thiel

Joe|April 11, 2010

These lessons summarize what Joe Lonsdale learned from working over many years with Peter Thiel, our chairman and one of our founders. These are very much worth reading for everyone at Palantir — they will change the way you think.

The nine lessons:

1. Divide reasoning into separate parts and clearly identify the most important factor.

If there’s no single reason that can cause you to do something, you should think carefully about whether it’s important or not. Oftentimes we’ll want to do something, and we’ll give multiple reasons for it without thinking hard about them. If you can’t give a single reason that justifies doing something on its own, you should be very wary that you aren’t exercising sufficient intellectual discipline.

2. Don’t divide your attention: focusing on one thing yields increasing returns for each unit of effort.

At a micro level, an extra hour of focus on the current project has a much higher return than an hour on something new, or worse, 5 minutes each on 12 new things. Before you ever do something new, you should understand the opportunity cost vs. existing things. Don’t rationalize that something you want to do is complementary when it’s not!

At a macro level, understanding that applied effort has a convex output curve is a very useful discipline when considering new market areas. This convexity means that the opportunity cost of transferring resources from existing projects to new ones is high. Unless the new area is incredibly valuable, anything we can do to extend an existing convex curve is worth so much more.

3. In hiring, value intelligence highly. Like focus, intelligence yields increasing returns.

Like focus, intelligence has a convex output curve — the smartest people can be an order of magnitude more productive than others who are only somewhat less smart. The key in hiring is to value potential skill rather than currently existing skill — and potential skill is based on intelligence rather than training.

4. Obsess over perfection.

If you are designing something that a customer is going to use or that will represent us in public, it’s not good enough unless it’s flawless and extraordinary.

Especially in software, many situations have winner-take-all dynamics due to network effects and switching costs. Being the winner means being in the 99.99-percentile. A winner at the top takes nearly everything, and only a pittance goes to the others — so being 99.99-percentile is worth an order of magnitude or two more than being just 98-percentile. If it’s 1am and you’ve already got something that is very good, this is why it’s worth spending the next couple of hours to make it amazing.

5. Use small details as indicators to point to the larger truth — and be alert when they point to conclusions you don’t like.

Despite the danger in this approach — indicators are not always right — more often than not you can derive a lot of wisdom from subtle indicators. How competent a single person is or how hard one person is working, or what a couple smart people think, might tell you a lot about a group before deciding whether to work with them. It’s an important discipline to be open to any indicators that you find whether they confirm your biases or not. In fact, you should be open to them especially when they do not confirm your biases.Indicators can be about all sorts of things, such as about the importance of a contract, the effectiveness of our software in different scenarios, the opinions and biases of key decision makers, etc. Few people pay as close or as honest attention to them as they should.

6. Don’t waste time talking about what you plan to think about; instead, work through it immediately.

Intellectual laziness can easily sneak up on you. If you are sitting there talking about problems you plan to solve later, there’s a good chance you are being inefficient. Similarly, in GTD, you don’t put off tasks that only take a couple minutes. In many cases, you can outline and solve or at least clarify any decision or problem you’re confronted with in just a few minutes.

7. Take the time to listen to smart people with whom you disagree.

This is not easy to do. Over time, any firm will find that certain methods and biases tend to work very well, and the more successful it is, the more it will develop its own unique mindset. We couldn’t succeed without the methods and principles that we learn over time, nor can we constantly re-articulate why they are the correct approach to everyone who comes along.

A sort of pride rightly develops around the successful structure, but this mindset cannot be allowed to ossify into an orthodoxy. So we have to use our judgment to seek out intelligent people who disagree with us — or even intelligent people who have simply taken a different approach — and be open about what we might learn from them. Despite his very strongly developed and out-of-the-mainstream views, Peter does this constantly, and it makes him extremely effective.

8. Be skeptical of any sort of external allies, and don’t trust the execution of anyone outside Palantir.

In the abstract, this is because the incentives of the other company will not line up with ours, and even if they do for the moment, they no longer will once the situation changes. In specific, other companies don’t have the same culture of execution that Palantir does, and we don’t have the power to instill that culture in them. Very early on, Peter saved Palantir from a partnership that would likely have destroyed the company.

In practice, that skepticism has led us to force others to pay upfront as one of the ways of proving value, which has worked well. Ultimately, only our own execution can make us win.

9. Return to first principles and act quickly on your new conclusions.

It’s very easy to take the world as it is, as opposed to envisioning it as you want it to be. For example, when re-designing a feature, one approach is to take what you have, and imagine small changes that will solve the problems with the feature. Instead, it’s often instructive to imagine that you were working from a clean slate and design the feature from scratch. In either case, the right approach is almost always to re-use the existing codebase in your implementation — but starting from first principles frees your mind from your assumptions about implementation complexity and forces you to re-consider the assumptions that stand in the way of the best solution.

Just like questioning our own assumptions, returning to first principles and building the argument up from scratch is a very powerful intellectual device that helps us to recreate our models as you receive new information, and to uncover options and opportunities you’d otherwise miss. It is not surprising to see that the largest hedge fund in the world, now one of our customers, also emphasized this as their key methodology.

Joe Lonsdale
General Partner, 8VC