Continues to Ride the Big Data Tailwind
We initiated coverage on Palantir on October 13, 2014. Since then, a number of developments have taken place, both company specific and industry related. This update captures the incremental information since our initiation and provides an updated valuation analysis. We reiterate our positive thesis on Palantir on the back of our belief that the company is well positioned in the sweet spot of spending.
Our research process involves proprietary channel checks with users, competitors, and industry experts, and synthesis of publicly available information from the company and other reliable sources.
Exhibit 1: Palantir Booking ($B)
Source: Manhattan Venture Research
Exhibit 2: Palantir Revenue ($B)
Source: Manhattan Venture Research
Big Data is Still Big
Data sets have become increasingly complex. Three secular trends are driving the rapid adoption of Big Data/Smart Data: (1) Explosive growth of unstructured data; (2) The availability of innovative and cost-effective software and hardware tools; and (3) The wide applications of Big Data/Smart Data analytics across verticals that are facilitating proactive and data-driven business decision-making. In particular, the availability of open source software frameworks, commodity hardware, and the improvements in the price performance of memory and processing power. Together they have been instrumental in lowering the cost and improving the scale of the architecture. This will increase the appeal of Big Data to a wide range of verticals – beyond the financial services and other IT-intensive verticals.
One favorable aspect of Big Data development has been the prominence of open source software frameworks. In particular, the Hadoop platform has become synonymous with Big Data, and the focal point of the movement and spawned innovation, which is spreading through the broader technology industry. Other frameworks driving Big Data development are in memory architecture stores and specialized databases such as NoSQL.
Today, roughly 95% of data generated is unstructured, driven by humans and machines – a stark contrast to the data generated from the traditional enterprise business applications (e.g., ERP, CRM, SCM). The key drivers of this change have been a combination of machine data, mobile traffic growth, and social media. The traditional relational databases and IT infrastructure, which were designed for structured data, cannot process the enormous volume and complexity of today’s data.
Data, for all practical purposes, has become the lifeblood of almost all verticals, as data-centric decisions become the norm and not the exception. Every enterprise needs and wants to control, learn from and exploit the potential value of the data it collects and proliferates. Few are able to do so. Search for needles in an exponentially growing, unstructured haystack is a great challenge. From manufacturers looking to gain greater insights into streamlining production, to financial services firms seeking to proactively detect fraudulent transactions and government agencies using complex data sets to pinpoint national security threats, the operative term is predictive analytics. Palantir has emerged as a leader in providing solutions to this definitional problem of the 21st Century.
Industry projections for the market for Big Data software and analytics is estimated at $98.6B for 2019 in the US and $187 billion worldwide, growing over 50% by over 50% from 2015 (IDC). Consensus estimates for Palantir’s peers, which include Hortonworks , Tableau Software and Splunk, are 30-50% growth, showing the rising tides in the industry and near –term opportunity.
Figure 1: Global Big Data/BI Market ($B)
Big Data firms are showing divergence based on their business models. Open-source platforms like Hortonworks have been challenged, while more specialized companies like Ayasdi (initially focused on healthcare) are rapidly scaling revenues. Ayasdi’s CEO has publicly stated he expects the company’s valuation to cross $1 billion next year. Proprietary technology and access to client data are the major moats separating the emerging leaders.
Our core investment thesis on Palantir remains positive and rests on the three central pillars outlined below. Additionally, we believe two concerns should be factored in to form a balanced view of the company:
Automated and scalable handling of machine and sensor data is the looming challenge of the near future. Palantir has been a leader in melding structured and unstructured databases and gleaning usable patterns from either or both. We see a constant proliferation of raw machine data. There is a foot race to gain dominance in systematizing and harvesting insight, pattern and clarity from these mounting zettabytes. Palantir is well positioned to win this race.
Ability to Maintain the Value Proposition. A constant risk for Palantir is its ability to stay at the cutting edge of technological innovations to tackle the increasingly sophisticated nature of threats to sensitive national security databases and installations –Palantir’s core competency. The company’s steep price tag of $1.0 million per installation in some cases – higher in a few cases – will be unsustainable if it cannot prove its value proposition, which is scalable, secure and user-friendly solutions. At a time when cost cutting is the mantra at all institutions, and new and innovative companies are always at your heels, no lead is permanent.
Palantir has two main product lines, Gotham and Metropolis. In the face of ubiquitous unstructured data coming from all types of machines and devices, the two products “tag and organize” the data, perform analytics, and find answers to critical questions. The key focus of all Big Data analytics platforms is to find the answers to three core questions: what happened in the past (descriptive analytics), what’s happening now (real-time analytics), and what will happen in the future (predictive analytics). Gotham addresses the first two, Metropolis all three.
Palantir’s technology has helped locate terrorists, prevent bank fraud and track disease outbreaks using data-mining tools that allow for users to comb through and make connections in massive sets of disparate data.
Palantir has updated its target markets to address the following use cases:
The growing number of applications indicate both increasing brand penetration and a scalable product with an ever-expanding addressable market. Early adopters in each channel have shown to be successful test cases for Palantir’s bespoke approach. This careful calibration has led to several new product joint ventures with customers, including Signac, a joint venture with Credit Suisse to proactively identify insider trading, and Insightics, a product built with First Data that uses payments information to provide recommendations to small businesses. Other prominent companies known to be using Palantir’s products include Hershey’s analysis for product placement on shelves; Santander, JPMorgan for finding fraud and enhanced compliance controls; Bridgewater Associates for sorting proprietary data on investments.
Palantir enjoys a technologically driven advantage over competitors. Best of breed learning algorithms require vast data sets to process and learn from. As an early player in Big Data/Smart Data, Palantir has been learning and iterating longer than many others. Additionally, the size, scope, and nature of Palantir’s large clients have allowed the company to process and learn from unique and vast caches of data.
To date, the company has assembled a broad roster of clients that range from the NSA and the FBI to JPMorgan Chase and News Corp. Other significant clients include Axa SA, Bridgewater Associates, Credit Suisse Group and First Data Corp. In November 2014, Palantir signed British Petroleum (BP), its biggest client worth $1.2 billion over 10 years, plus bonus payments as determined by executives from both companies, according to media reports.
Most recently (May 26, 2016), Palantir landed a $222 million firm-fixed-price contract from the U.S. Special Operations Command for the delivery of All Source Information Fusion software licenses and associated support services. The Defense Department said that Palantir will provide ASIF licenses to support SOCOM’s Special Operations Forces Acquisition, Technology and Logistics. SOCOM will obligate $5 million from fiscal 2016 operations and maintenance funds along with additional funding as it becomes available. DoD added the company will perform work in several locations within and outside the continental U.S. throughout the base year and three additional option years if exercised. The contract is a sole-source award for analytics software that will work to support intelligence analysis and production.
Commercial Contracts on the Rise
Palantir’s customer mix is shifting more and more toward commercial enterprises. The company now reports roughly 85% of its revenues from enterprise customers, doubling over the prior year, highlighting the company’s drive to diversify its revenue base and, more importantly, reduce its reliance on government contracts.
A key attribute of Palantir’s offering is its stickiness. This is a function of the company’s “total integration” approach where engineers are embedded on-site for six months or more. Typical commercial contracts with customers often last five to 10 years, though CEO Karp says clients are not locked in: “We believe that a good partnership is one where a client can leave.” “Deep” customer relationships have led to some new products/JVs as noted above and often lead to demand for additional user licenses, based on public contract histories available such as the LAPD.
Possible Pent-up Demand?
Palantir also subjects new customers to an approval process, including total information access for its engineers. The company offers two products, Gotham and Metropolis, which can be used for multiple industries and applications as seen below:
Now we can try to understand the Palantir product offering by spending hours trying to regurgitate their marketing material or by interviewing one of their PR people to get the canned media spiel, but instead we’ll give you an example of what they can do.
In a demonstration of how powerful their platform is, the Company put together a Palantir Gotham instance that integrated anonymized data from Medicare and various other data sources to show the potential of a fully integrated, interactive system. The instance integrated the 6 following data sets:
Can you even imagine how tough it would be to link all these datasets? If you were building a data warehouse, you could just import all the databases into a master database and begin to query it. The problem here is that these aren’t all databases. Dataset #3 listed above consists of 22 million biomedical journal articles. How do you even begin to analyze those? That’s where Palantir’s tools can add value. And this example is just 6 datasets. The U.S government has made public almost 200,000 datasets from 170 different sources which they have posted for public access. There is an incredible amount of “big data” available for free and the first company that can start to link all these data sets and learn from them will have the one ring that rules them all. Palantir Gotham allows you to do this.
After you’ve created your ginormous Big Dataset, you can then use Palantir Metropolis to analyze the data and learn from it. Examples given by Palantir include tracking and analyzing insurance claims data, network traffic flow, and financial trading patterns:
Metropolis ingests terabytes of claims data from Fortune 500 payers to identify plan members in need of critical services like immunization and chronic disease screenings. End-to-end workflows in Palantir lead to direct action to connect these members intelligently with providers based on distance, barriers to service, and provider quality.
Palantir has made five acquisitions since February 2013, including two since our initiation in October 2014. The two most recent include Kimono Labs on February 15, 2016 and FT Technologies on February 6, 2015. The other three acquisitions were Propeller on July 31, 2014, Poptip on July 29, 2014, Voicegem on February 16, 2013. None of these 5 acquisitions seem to qualify as large or costly transactions.
Following is a brief description of the acquisitions:
Palantir has raised a total of $2.69 billion in 13 rounds. The last round (Series K) was completed on December 23, 2015. The amount raised was $880 million at $11.38 per share, raising the post money valuation to $20.53 billion.
The following figure highlights all the rounds, along with the lead investor(s) in each round, amount raised, price per share and the implied post-money valuation.
Figure 2: Palantir Funding Rounds
Source: Pitchbook, Manhattan Venture Research
We have reconstructed Palantir’s financial model following newly available information from multiple sources.
Palantir’s revenue model is a combination of sales (via software solutions sold to clients) and maintenance & support services, either bundled with the contract or as after-sales services. According to our estimates, the company generates approximately 40% of its revenue through the sale of software and solutions and the balance from providing services to clients. With regard to clients, Palantir generates about 15-20% of the revenue from government clients and the balance from commercial private enterprises. The commercial contribution has been rising and we expect this trend to continue.
Based on our assumptions and checks, we believe the company exited 2015 with $1.7 billion in bookings, $420 million in revenue, and an EBITDA loss of $421 million. Looking ahead, we expect bookings to maintain its robust pace of growth on the back of new contract wins. We also expect the pace of revenue conversion to pick up in 2016 and forward, resulting in positive EBITDA in 2017.
[For a more detailed discussion with the MVR analysts on the financial model and the assumptions, please contact your sales representative]
Figure 3: Palantir Model ($M)
Source: Company reports, Manhattan Venture Research
Palantir has a unique revenue model. The company typically enters into long term contracts and recognizes revenue over time, with additional bonuses and other incentives tied to the contract. Accordingly, we believe, deriving Palantir’s valuation based on the bookings (as opposed to revenues) is justifiable. Based on this methodology, we peg Palantir’s valuation at $15.5 billion on the low end and $20.5 billion on the high end. This translates to $8.62 per share and $11.36 per share, respectively, based on 1.8 billion shares outstanding.
Figure 4: Implied Comparative Valuation – Based on EV/Bookings Multiple ($M)
Source: Manhattan Venture Research
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Manhattan Venture Partners provides clients with accurate, timely and innovative research into the companies and sectors we cover. To that end we have established an experienced team of analysts, researchers, economists and industry veterans that focus exclusively on private companies with a proven track record of success. Producing quality research on a private company is uniquely challenging. Our analysts communicate with employees, ex-employees, early investors, VCs, competitors, suppliers and others to gather valuable information about the company under coverage. This information enables us to create unique financial models that value the underlying company and provide insight to our clients and industry experts, leveraging years of experience working for bulge bracket firms.
Manhattan Venture Partners reports include business and financial aspects of late-stage companies. These reports include but are not limited to industry overviews, competitor analyses, SWOT analysis, products (existing and in development), management and key directors, risks and concerns, other propriety channels, historical financials, revenue projections, valuations (using various matrices and valuation recommendation), waterfall analysis, and a capitalization table.
About the Analysts
Santosh Rao has over 18 years of experience in equity research, primarily within the technology and telecommunications space. He started his equity research career as an Associate at Prudential Securities and later moved to Broadpoint Capital (Formerly First Albany Capital), where he was the Senior Equity Analyst, and later to Evercore Partners, where he worked with the Telecom and Data Services Group. Prior to joining Manhattan Venture Partners, he was the Managing Director and Head of Research at Greencrest Capital, focusing on private market TMT research. Mr. Rao started his career as a Financial Analyst in the Operations Groups at PaineWebber (UBS) and Prudential Securities. Santosh has an undergraduate degree in Accounting and Economics, and an MBA in Finance from Rutgers Graduate Business School.
Max Wolff is an economist specializing in international finance and macroeconomics. Before joining Manhattan Venture Partners, he was Chief Economist at Greencrest Capital, and prior to that spent four years as the senior hedge fund analyst at the Beryl Consulting Group LLC. Mr. Wolff teaches finance and statistical research methods in the New School University’s Graduate Program in International Affairs. Max’s financial markets and Macro-Economics work appears regularly in Seeking Alpha, The WSJ, Reuters, Bloomberg, The BBC, Russia Today TV, and Al Jazeera English.
I, Santosh Rao, certify that the views expressed in this report accurately reflect my personal views about the subject, securities, instruments, or issuers, and that no part of my compensation was, is, or will be directly or indirectly related to the specific views or recommendations contained herein.
I, Max Wolff, certify that the views expressed in this report accurately reflect my personal views about the subject, securities, instruments, or issuers, and that no part of my compensation was, is, or will be directly or indirectly related to the specific views or recommendations contained herein.
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