Perspective on the Enterprise Software Industry and New Venture Success Will Price September 6 th , 2005

Executive Summary Context and Assumptions The investing environment has fundamentally shifted, but also created great opportunities for savvy early stage investors Significant trends are creating great opportunities for new companies Scale-free profitability demands new business models and optimized business practices

Context and Assumptions

The investing environment has fundamentally shifted, but also created great opportunities for savvy early stage investors

Significant trends are creating great opportunities for new companies

Scale-free profitability demands new business models and optimized business practices

IT Venture Capital: Secular Not Cyclical Shift, Early Stage May Be Bastion of Extraordinary Returns Surplus capital in the industry appears to be a secular rather than a cyclical shift Ratio of IT VC $ Invested YTD to IT VC $ Raised YTD .50 If no new funds raised, current pace of investing suggests overhang will be put to work in 11.9 quarters $32.7bn/$2.747bn Where is the IT capital going Apparently not in early stage 2000 Early Stage $/Total $ 34% 2003 Early Stage $/Total $ 20% 2004 Early Stage $/Total $ 20% 1H2005 Early Stage $/Total $ 16% Early stage investing bastion of pricing discipline and IRR given barriers to entry Later stage deals largely won on share price alone Barriers: deal flow, syndication, optimized investment decisions, post-deal value add Source: Venture One

Surplus capital in the industry appears to be a secular rather than a cyclical shift

Ratio of IT VC $ Invested YTD to IT VC $ Raised YTD

.50

If no new funds raised, current pace of investing suggests overhang will be put to work in 11.9 quarters

$32.7bn/$2.747bn

Where is the IT capital going

Apparently not in early stage

2000 Early Stage $/Total $

34%

2003 Early Stage $/Total $

20%

2004 Early Stage $/Total $

20%

1H2005 Early Stage $/Total $

16%

Early stage investing bastion of pricing discipline and IRR given barriers to entry

Later stage deals largely won on share price alone

Barriers: deal flow, syndication, optimized investment decisions, post-deal value add

When It Goes Right, What Does It Cost to Build a Great Software Company? Median Capital Raised: $10.1m Median 1 st -4 th Year Revenue Ramp: $.1  $.8  $6.9  $21.6m Median Years to Exit: 4 Market Comps: Massive variance Lesson: Pricing discipline is critical as multiples at exit are impossible to forecast and may not be consistent with market multiples at time of funding With market pricing impossible to forecast, capital efficiency is critical Software model supports the creation of great companies on <$20m of capital

Median Capital Raised: $10.1m

Median 1 st -4 th Year Revenue Ramp: $.1  $.8  $6.9  $21.6m

Median Years to Exit: 4

Market Comps: Massive variance

Lesson:

Pricing discipline is critical as multiples at exit are impossible to forecast and may not be consistent with

market multiples at time of funding

With market pricing impossible to forecast, capital efficiency is critical

Software model supports the creation of great companies on <$20m of capital

Gains from Information Technology M&A Suggest Capital Efficiency is Critical Implications: Stage and Capital Efficiency Matter Invest early and avoid >$15-20m in a given deal

If I Were to Start Tomorrow… Goal Comprehensive, quality deal flow Comprehensive, quality deal flow Function of (top down appreciation of key trends + bottoms up coverage of superset of possible opportunities) Key Trends Function of (secular economic, technical, market, competitive drivers) Buyer power, regulation, consolidation, operating leverage concerns, off shoring, on demand, open source, virtualization, increased specialization of enterprise applications Bottoms up coverage Function of (law/service firms, M&A targets, university/corporate research, incumbents, IT community, start-up network, industry literature/blogs, conferences) Good deal identification Function of (filter that isolates signal from noise) Filter Technical Innovation Business models that support scale-free profitability Tailwind Leverage of ecosystem-based competition Strategy to align vendor and customer interests

Goal

Comprehensive, quality deal flow

Comprehensive, quality deal flow

Function of (top down appreciation of key trends + bottoms up coverage of superset of possible opportunities)

Key Trends

Function of (secular economic, technical, market, competitive drivers)

Buyer power, regulation, consolidation, operating leverage concerns, off shoring, on demand, open source, virtualization, increased specialization of enterprise applications

Bottoms up coverage

Function of (law/service firms, M&A targets, university/corporate research, incumbents, IT community, start-up network, industry literature/blogs, conferences)

Good deal identification

Function of (filter that isolates signal from noise)

Filter

Technical Innovation

Business models that support scale-free profitability

Tailwind

Leverage of ecosystem-based competition

Strategy to align vendor and customer interests

Enterprise Software Trends and Emerging Needs Real-time DSS (in-memory, frequent ETL) Query across DB, XML/XQuery, text, web, and voice Data mining/greater need for machine learning to deal with data deluge (Intel’s RMS) Industry DBs and scoring algorithms Analysis New Characteristics and Trends Usage Model and Category Dynamic data gathering from DBs, Web services AJAX and RSS Rendering large content using XSLT BPEL/BPML and composite applications Security to address concerns re: trust and privacy Federated ID to allow SSO Voice interaction Entitlements Collaboration Increased data volume, processing Scale out – apps deployed over sets of independent, networked resources Frequent DB syncs concurrent with OLTP – data integrity App/DB level security Messaging/XML acceleration eBiz/Web OLTP Autonomic management/server virtualization Decoupling of logical and physical Logic driven ILM Data Center Ops 64 bit computing – 2x memory per clock cycle Grids/clusters/dynamic provisioning Increased data volume/ XML Virtualization/Resource Pooling Technical Computing

Example Areas of Implementation Next Gen Infra Virtualization and resource pooling (Scalent) Grid interconnects (Pathscale) Application performance mgt (SEBL issues) Event archiving (KX Systems) Storage ILM logic to move data between tiers (Neopath) Backup and recovery (SysDM) Security Fine-grain entitlements (Citibank fiasco) Federated SSO (PingID) Virtual patch (Blue Lane) Secure email (Voltage) Analytics Event processing (Coral8) Natural language processing (Attensity) Scoring (Vindicia) RSS Syndication (Feedburner) XML OLAP (Skytide)

Next Gen Infra

Virtualization and resource pooling (Scalent)

Grid interconnects (Pathscale)

Application performance mgt (SEBL issues)

Event archiving (KX Systems)

Storage

ILM logic to move data between tiers (Neopath)

Backup and recovery (SysDM)

Security

Fine-grain entitlements (Citibank fiasco)

Federated SSO (PingID)

Virtual patch (Blue Lane)

Secure email (Voltage)

Analytics

Event processing (Coral8)

Natural language processing (Attensity)

Scoring (Vindicia)

RSS Syndication

(Feedburner)

XML OLAP (Skytide)

Applications Also Possible Bastion of Value Capture Applications “ Computer science” required to build applications increasingly subsumed into readily available components J2EE and .Net Business logic and domain specific solutions may be a bastion of value and margin Suggests application layer will compete more on product management than engineering Applications Criteria Deep domain/business knowledge World class product management Robust enterprise and data integration strategy Leverage of OSS and 3 rd Party Infrastructure Stack Leverage of low cost R&D human resources Examples Demandtec ACL

Applications

“ Computer science” required to build applications increasingly subsumed into readily available components

J2EE and .Net

Business logic and domain specific solutions may be a bastion of value and margin

Suggests application layer will compete more on product management than engineering

Applications Criteria

Deep domain/business knowledge

World class product management

Robust enterprise and data integration strategy

Leverage of OSS and 3 rd Party Infrastructure Stack

Leverage of low cost R&D human resources

Examples

Demandtec

ACL

9 Source FactSet Notes Companies with >$5Bn revenue run-rate include Microsoft, Oracle and SAP Companies with $1Bn - $5Bn revenue include Computer Associates, PeopleSoft, Intuit, Veritas, Symantec, Siebel, Compuware, Adobe, Novell, BEA and VeriSign Companies with $500MM - $1Bn revenue run-rate include McAfee, Sybase, Parametric, Hyperion and Mercury Companies with $300MM - $500MM revenue run-rate include Kronos, i2, Macromedia, Dendrite, FileNet, Lawson, Progress, Quest, TIBCO and Aspen $75MM - $300MM category includes a representative set of 50 software companies with annual revenue of $75MM - $300MM Scale is increasingly necessary to achieve competitive operating leverage in the software industry More efficient sales & marketing and R&D per dollar of revenue Sub-$75m revenue companies average <10% operating margins and SG&A represents > 40% of revenue. 2% 8% 12% 16% 32% Scale Matters for Sustained Profitability Source: Morgan Stanley % of Revenue

Notes

Companies with >$5Bn revenue run-rate include Microsoft, Oracle and SAP

Companies with $1Bn - $5Bn revenue include Computer Associates, PeopleSoft, Intuit, Veritas, Symantec, Siebel, Compuware, Adobe, Novell, BEA and VeriSign

Companies with $500MM - $1Bn revenue run-rate include McAfee, Sybase, Parametric, Hyperion and Mercury

Companies with $300MM - $500MM revenue run-rate include Kronos, i2, Macromedia, Dendrite, FileNet, Lawson, Progress, Quest, TIBCO and Aspen

$75MM - $300MM category includes a representative set of 50 software companies with annual revenue of $75MM - $300MM

Scale is increasingly necessary to achieve competitive operating leverage in the software industry

More efficient sales & marketing and R&D per dollar of revenue

Sub-$75m revenue companies average <10% operating margins and SG&A represents > 40% of revenue.

Scale Free Profitability Requires New Approaches and KPIs Start-up companies must innovate their business models and strategies in order to reach attractive profitability metrics independent of scale R&D R&D expense as a percentage of revenue can be dramatically reduced via ecosystem pooling of resources and labor arbitrage Track cost per R&D head, Rev/component and cost/component Marketing Marketing must become more KPI driven and quantitative with CEO’s demanding detailed activity-based cost analysis of marketing programs. Internet savvy marketing Track cost per lead, cost per close Sales Cost of direct sales is crippling and the variability of reps (see Mark Leslie’s Sales Life Cycle Analysis) makes direct selling very challenging MySQL’s “try before you buy approach” Distribution channels (ex. VMWare) Track sales as % of revenue, sales resource op margin contribution Operations and Delivery A hosted/ratable revenue model should be considered early on Customer benefits: lower risk and cost, faster go live and payback, lower upgrade costs, broader access to complex functionality Vendor benefits: higher adoption rates, lower development and support costs, recurring revenue Track GM Vendor’s delivery, pricing, and product strategies must not be orthogonal to IT buyer’s interests and counter to the dominant trends in the industry

Start-up companies must innovate their business models and strategies in order to reach attractive profitability metrics independent of scale

R&D

R&D expense as a percentage of revenue can be dramatically reduced via ecosystem pooling of resources and labor arbitrage

Track cost per R&D head, Rev/component and cost/component

Marketing

Marketing must become more KPI driven and quantitative with CEO’s demanding detailed activity-based cost analysis of marketing programs. Internet savvy marketing

Track cost per lead, cost per close

Sales

Cost of direct sales is crippling and the variability of reps (see Mark Leslie’s Sales Life Cycle Analysis) makes direct selling very challenging

MySQL’s “try before you buy approach”

Distribution channels (ex. VMWare)

Track sales as % of revenue, sales resource op margin contribution

Operations and Delivery

A hosted/ratable revenue model should be considered early on

Customer benefits: lower risk and cost, faster go live and payback, lower upgrade costs, broader access to complex functionality

Vendor benefits: higher adoption rates, lower development and support costs, recurring revenue

Track GM

Vendor’s delivery, pricing, and product strategies must not be orthogonal to IT buyer’s interests and counter to the dominant trends in the industry

Executive Summary The investing environment has fundamentally shifted, but also created great opportunities for savvy early stage investors Significant trends are creating great opportunities for new companies Scale-free profitability demands new business models and optimized business practices

The investing environment has fundamentally shifted, but also created great opportunities for savvy early stage investors

Significant trends are creating great opportunities for new companies

Scale-free profitability demands new business models and optimized business practices