The Face of the New Enterprise. Market Overview and Proprietary Financial Intelligence

Transcription

1 The Face of the New Enterprise Market Overview and Proprietary Financial Intelligence

2 SVB Analytics provides business analytics solutions to every stakeholder in the venture capital ecosystem. 6,000 Valuations completed since ,200 Active clients in 2012 Advisory Services: Due diligence support Valuation Guidance Proprietary market intelligence Valuation Services: 409A Valuations (Stock Options) Purchase Price Allocation (post-m&a Accounting) Goodwill and Intangible Asset Impairment Research: Proprietary Research and Data Customized Studies Thought Leadership Client Focus: Corporate venture, innovation and development groups Client Focus: Venture-backed companies Client Focus: Corporate and venture ecosystem 2

3 Table of Contents The Face of the New Enterprise 6 Characteristics, Tools and Competencies 7 Market Forces Shaping the New Enterprise Exploring the Data 11 Sector / Niche Segmentation 13 Exploring and Interpreting the Data Summary 22 Final Thoughts 23 Bios and Contact Information 24 Glossary 3

4 Table of Contents The New Enterprise is adopting new tools and technology that utilize data, mobilize their workforce, and increase collaboration throughout the organization. The Face of the New Enterprise 6 Characteristics, Tools, and Competencies 7 Market Forces Shaping the New Enterprise Exploring the Data 11 Sector / Niche Segmentation 12 Segmentation 13 Exploring and Interpreting the Data Summary 22 Final Thoughts 23 Bios and Contact Information 24 Glossary 4

5 The Face of the New Enterprise Work-life Blur More Mobile Collaborate Online Multiple Devices Social Bring Your Own Everything

6 Characteristics, Tools and Competencies The New Enterprise Has unparalleled, predictive insight into its key operating metrics internal and external Tools and Competencies Big Data Collection, Harmonization, Storage, Predictive Analytics and Business Intelligence Has an increasingly mobile workforce needing to work where they go and access internal resources Virtualization of the IT stack, BYOD, Consumerization of IT, Security Is becoming flatter and more transparent, with self organizing teams and an increasing share of knowledge workers Social Collaboration, Distributed Workforce Increasingly blurs boundaries between employees, vendors, and customers Social CRM, PaaS, Value Chain Collaboration 6

7 Market Forces Shaping the New Enterprise Big Data, Predictive Analytics and Business Intelligence By 2005 the world had generated a total of 130 Billion GB of data a level expected to increase to 40 Trillion GB by Companies in all industries have a Big Data Problem Only 0.5% of 2.5B GB of data generated every day is examined for its analytic value 1 The Big Data Industry will grow from $3.2B in 2010 to almost $17B by the end of Missed opportunities to not only know why it happened, but predict what will happen Significant early-stage investment happening in this space 1 IBM Research 7

8 Market Forces Shaping the New Enterprise Virtualization of the IT stack, BYOD, Consumerization of IT, Security More than 200M mobile workers will be using mobile business apps 1 60% of North Americans use their smartphone for work 2 BYOD in the enterprise: multiple device, OS support costs plus security and compliance challenges At least 72% of companies report increased productivity as a direct result of flexible working practices 3 68% claim it has led to increased revenue 3 Productivity trade-offs include information security, device management and administration costs Gartner sees BYOD programs as the single most radical shift in the economics of client computing for business since PCs invaded the workplace. 1 Strategy Analytics, ipass Mobile Workforce Report Regus/Mindmetre

9 Market Forces Shaping the New Enterprise The Social Enterprise Enterprise Social Networking market is forecast to grow at a CAGR of 52% from 2012 through Social technologies can increase brand awareness by 36% and customer conversions by 20% 2 Heavy competition amongst large and small companies to offer unified social communication technologies 83% of companies are using at least one social technology 73% of companies leverage social technology internally 74% customers 48% external partners 2 Social and Collaborative tools must work inside and outside the enterprise and enable data sharing without compromising security 1 MarketResearchReports.biz 2 Evolution of the Global Enterprise, McKinsey Global Survey 9

10 Table of Contents We took a bottom-up approach when segmenting the underlying industry sectors supporting the Face of the New Enterprise. We examined the business models of the companies in our data set, and characterized them by granular focus ( Niche ), which were then organized into four primary business functions ( Sector ). The Face of the New Enterprise 6 Characteristics, Tools, and Competencies 7 Market Forces Shaping the New Enterprise Exploring the Data 11 Sector / Niche Segmentation 13 Exploring and Interpreting the Data Summary 22 Final Thoughts 23 Bios and Contact Information 24 Glossary 10

11 Exploring the Data Sector / Niche Segmentation Enterprise Operations Enterprise Mobility Network Security Content and Collaboration Supply Chain Management Human Resources IT Infrastructure Cloud Infrastructure Network Management Software Communications Technology Software Defined Networking Systems Management Storage Technology Data Analytics & Business Intelligence Big Data Business Intelligence External Engagement Application Development/PaaS Consumer Payment Systems Social Media CRM Marketing 11

12 Exploring the Data Sector / Niche Distribution Distribution of companies by sector and niche 26% 32% 22% 19% Enterprise Operations and IT Infrastructure show the highest concentration of companies comprising the new enterprise. The following analysis indicates that this is a reflection of the maturity of these sectors (relative to DA/BI and EE), and the myriad opportunities to improve security and efficiency and reduce costs. Data Analytics and Business Intelligence External Engagement Enterprise Operations IT Infrastructure Parent Sector Top Niches DA and BI Business Intelligence 12% IT Infra Storage Technology 11% Ent Ops Network Security 10% DA and BI Big Data 10% 12

13 Exploring the Data VC Funding Distribution Distribution of financing by sector 5% 3% 9% 9% 7% Three of the four sectors profiled exhibit strong concentrations in Series A and Series B stage companies. 22% 32% 42% 28% 18% 33% Series D Series C Series B Series A Enterprise Operations, however, exhibits a comparatively higher concentration of Series C and Series D companies, indicating a relatively mature sector. 32% 41% 45% 30% 42% Data Analytics and Business Intelligence External Engagement Enterprise Operations IT Infrastructure 13

14 Exploring the Data The Age of the New Enterprise Distribution of companies by year founded 30% 22% 9% 14% Sixty percent of Enterprise Applications companies were founded between 2000 and 2007, compared to 72% of Data Analytics and Business Intelligence companies founded in 2008 or later. 42% 50% 32% 37% 47% 27% By examining both series of funding and years since founding, it is clear that Data Analytics & Business Intelligence and External Engagement are in the early years of market development relative to Enterprise Operations and IT Infrastructure. This highlights that the New Enterprise may increasingly adopt tools and technology within these sectors going forward. 23% 5% 19% 8% 23% 12% Data Analytics and Business Intelligence External Engagement Enterprise Operations IT Infrastructure 14

15 Exploring the Data Revenue Run Rate Distribution of average trailing 12 months revenue by sector 8% 11% 18% 3% 14% 11% 14% 25% 8% 12% 9% 17% 9% 30% $20M+ $10M-$20M $5M-$10M $1M-$5M One quarter of all Enterprise Operations companies generated more than $20M on a trailing 12-month basis. 72% of DA/BI companies are Series A or B, and 63% of these companies generate less than $1M in revenue. 87% of EE companies are Series A or B, and 57% of these companies generate less than $1M in revenue. 63% 57% 22% <=$1M 62% of EO companies are Series A or B, and 33% of these companies generate less than $1M in revenue. 33% 36% 75% of ITI companies are Series A or B, and 36% of these companies generate less than $1M in revenue. Data Analytics and Business Intelligence External Engagement Enterprise Operations IT Infrastructure This confirms that DA/BI and EE are in relatively nascent stages of development compared to EO and ITI. 15

16 Exploring the Data Revenue Generation by Stage and Sector TTM Revenue by Round ($M) Examining trailing 12-months revenue by round shows that revenue generation is minimal at the Series A and B; however, at Series C, a large chasm develops between Enterprise Operations/IT Infrastructure and Business Intelligence/External Engagement. $6.9 $9.6 Series C Series B Series A The compression of the Value-to-Capital ratio from the previous page in Business Intelligence and External Engagement mirrors the comparative lower revenue of companies in these spaces relative to Enterprise Operations and Infrastructure. $1.9 $0.4 $0.2 $3.7 $1.0 $1.0 $0.6 $0.8 $1.4 $0.1 This may be a reflection of more developed markets in EO and ITI, or that buyers of enterprise solutions are more likely to purchase more traditional solutions versus newer solutions. Data Analytics and Business Intelligence External Engagement Enterprise Operations IT Infrastructure 16

17 Exploring the Data Revenue Progression Revenue by Stage of Development ($M) $29.0 $0.1 $1.5 Product Development $2.1 $0.5 $0.7 Commercialization and revenue growth Develop sales force $3.5 $4.7 $10.5 $13.6 At the early stages, most companies are focused largely on developing POC, alpha or beta product/service offerings. Cultivating a sales force and deploying it at scale generates an explosion in revenue from later stage Series C and Series D companies. There is also a larger disconnect between LTM and NTM revenue at the earlier stages. With better forecasting, later-stage companies are able to scale and forecast growth more accurately. Series Seed Series A Series B Series C Series D+ Median LTM Revenue Median NTM Revenue 17

18 Exploring the Data Investments in the New Enterprise Average Invested Capital by Stage and Sector ($M) $50.6 Looking at average invested capital by round, we notice that Series B and Series C investments are commensurately higher in EO and ITI companies. $27.8 $22.5 $45.9 Series C Series B Series A This echoes the previously identified trend of higher TTM revenue in EO and ITI companies as they likely require larger amounts of capital for product development and sales. $18.4 $15.5 $14.8 $18.0 $6.4 $7.8 $8.1 $12.2 Data Analytics and Business Intelligence External Engagement Enterprise Operations IT Infrastructure 18

19 Exploring the Data Value Progression Average Pre-Money Valuation ($M) Series D Series C Series B Series A $190.4 $137.4 $ % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Step Up Analysis 100% 86% 7% 7% 70% 73% Seed-to-A A-to-B B-to-C C-to-D Up Flat Down 73% of Series D rounds are at higher valuations than the Series C 18% 12% 27% $89.8 $151.2 $87.6 $36.3 $42.9 $30.9 $42.8 $28.3 $33.9 $12.4 $13.2 $16.8 $17.4 The relatively higher proportion of down rounds at the Series B and Series C financing again highlights the scaling and commercialization challenges mid-stage companies face. Those that successfully execute are rewarded with higher valuations in the Series D round. Data Analytics and Business Intelligence External Engagement Enterprise Operations IT Infrastructure 19

20 Exploring the Data Value Relative to Total Invested Capital Pre-Money / Total Invested Capital 1.7x 1.5x 2.0x 2.8x The ratio of the pre-money valuation divided by total invested capital enables cross-sector comparison of both valuation and capital efficiency. For instance, a Series C company that recently raised a round at a pre-valuation of $50M with total invested capital of $25M would have a ratio of 2x. 2.0x 2.3x Data Analytics and Business Intelligence 2.8x 1.7x External Engagement 1.6x 1.8x 2.2x Enterprise Operations 2.0x IT Infrastructure Series C Series B Series A Series A valuations are typically a function of capital and ownership requirements. The size of the addressable market, and strength of the team and concept also drive value. However, as the focus shifts from product development to commercialization, revenue generation begins to play a role in later-stage (Series C and beyond) valuations. To illustrate this, compare the relatively high Series A valuations in DA/BI to the relatively low Series C valuations. The inverse is true in IT Infrastructure. 20

21 Table of Contents The Face of the New Enterprise 6 Characteristics, Tools, and Competencies 7 Market Forces Shaping the New Enterprise Exploring the Data 11 Sector / Niche Segmentation 13 Exploring and Interpreting the Data Summary 22 Final Thoughts 23 Bios and Contact Information 24 Glossary 21

22 Final Thoughts Growth-Stage Focus Business models for growth-stage companies center around: Security Mobility Big Data Value and Cost Early-Stage Focus Business models for early-stage companies center around: Engagement (internal and external) Data and Intelligence Collaborations and Efficiency The New Enterprise is shaped by technologies employees pull in from their personal lives, and explosive growth in the volume of data created inside and outside the enterprise. The enterprise s boundaries melt into those of its employees, customers, and partners. Flexibility, mobility, and collaboration present significant opportunities for both entrepreneurs and investors. Later-stage companies in the market have provided the enabling foundation for this transformation, and paved the way for innovative new companies to explore and disrupt the enterprise. 22

23 SVB Analytics Contacts Steve Allan Managing Director Steve Allan is a managing director with SVB Analytics, responsible for leading SVB Analytics in executing client engagements, issuing valuation opinions for private companies, and conducting research in the technology and life science private financing arena. Allan brings a strong financial background and passion for entrepreneurship to his leadership role at SVB Analytics. Sallan@SVB.com Rob Tompkins Director Rob Tompkins is a director with SVB Analytics and leads SVBA s research, strategy and business development initiatives. Tompkins has extensive experience valuing privately-held technology companies with a focus on the intersection of energy and technology. Prior to joining SVB, Tompkins provided strategic and financial advisory services to startups in the U.S. and Latin America. Rtompkins@SVB.com Contributing authors: Sean Lawson, Technology Senior Associate Amrit Sareen, Technology Associate 23

24 Glossary Term API CES COGS IoT M2M MDM Metcalfe's Law Moore's Law Organic Sales RFID ROI SaaS Step-up SVB WSN Definition Application Programming Interface Consumer Electronics Show Cost of Goods Sold Internet of Things Machine-to-machine Mobile Device Management The value of a network is equal to the square of the number of devices connected to it The number of transistors on integrated circuits doubles approximately every two years Growth that comes from existing customers, word of mouth, and viral sources, versus from increased sales and marketing efforts Radio-frequency identification Return on Investment Software-as-a-Service Refers to the percentage increase in the original issuance price of the preferred securities between two rounds of financing Silicon Valley Bank Wireless Sensor Network 24

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