Slide 1: Interim Results
Interim Results 6 Months Ended June 30, 2012
Slide 2: WANdisco
• WANdisco • We’re talking about software for software people • Strong and growing customer base • Robust financial model 2
Slide 3: Admitted to AIM on 1 June 2012
• Admitted to AIM on 1 June 2012 • Our IPO commitments 3
Slide 4: H1 Highlights
H1 Highlights Progress in Sales, Product and Expansion
Slide 5: Strong sales progress
• Strong sales progress • Growth from new customers, existing customers and renewals 5
Slide 6: Number of Deals by Type
Type Number of Bookings Value Average Deal % Deals Size New customers 21 $1,056,000 $50,303 31% Add‐on deals 21 $560,000 $27,467 17% Renewals 41 $1,734,000 $42,309 52% Total 83 $3,367,871 $40,576 6
Slide 7: Enhancing our sales organisation
• Enhancing our sales organisation – – • Expanding our footprint into Asia – – – • Adding to our Software Development and Engineering capability • Making early progress on Big Data 7
Slide 8: Experienced sales hires for H2
Role H1 H2 Total Sales Total Sales • Experienced sales hires for H2 Headcount Headcount from IBM, Serena and MicroFocus (Est.) VP Sales 1 1 • Head of Sales Engineers Enterprise Sales 2 6 – – Inside Sales 2 4 Sales Engineer 3 5 • Head of Sales EMEA – Lead Generation 1 5 – eCommerce Sales 0 1 Renewals
Slide 9: Refining our approach
• Refining our approach • Purchased new systems for marketing automation: Marketo – – • Ensures sales team is ‘data-driven’ rather than hunting for a ‘needle in a haystack’ 9
Slide 10: China presence established
• China presence established • First employees hired in August • WOFE (incorporation in China expected November) • First deal signed with Huawei • Existing customers in China 10
Slide 11: Enhanced capability of core engineering team
Role H1 H2 Total Product & Total Product • H1 Key Hires: Engineering & Engineering Headcount Headcount (Est.) VP Prod Management 1 1 VP Engineering 1 1 Product Management 2 2 uberSVN Cloud 1 3 • H2 Key Hires: QA 5 5 uberSVN Dev 5 8 Enterprise Dev 6 5 OS Dev Subversion 3 5 OS Dev Bloodhound 2 4 Train
Slide 12: Product development timeframe
Product Time‐Frame • Development sequential rather Enterprise ($$) than parallel due to team size. Subversion February 2012 MultiSite 4.0 Subversion March 2012 Access Control 4.1 SME ($) uberSVN ‘Blake’ January 2012 uberSVN July 2012 ‘Chimney House Open Source Subversion 1.7.3 April 2012 update 12
Slide 13: H1 Financials
navis CKROCK amt Ril nture we) ene HONDA a JOHN DEERE DS ake TELEN VOM y Im antec, & atat BL H1 Financials Key Data
Slide 14: Six months to 30 June Key Data
Six months to 30 June 2012 2011 Change Cash Bookings $3.39m $2.16m +57% Accrued Revenue $4.94m $3.98m +24% Revenue $2.92m $1.91m +53% Adjusted EBITDA $0.35m $(0.02)m Net Cash $22.0m $0.12m 14
Slide 15: Bookings
Bookings 4000 3500 3000 2500 2000 1500 1000 500 0 H1 09 H2 09 H1 10 H2 10 H1 11 H2 11 H1 12 BOOKINGS 15
Slide 16: Summary and Outlook
Summary and Outlook Future developments and FY views
Slide 17: Product roadmap
Product Enterprise ($$) • Greater capacity and velocity from Subversion MultiSite 5.0 (big data ready) parallel development Subversion MultiSite 5.1 • Key milestones: Big Data prototype SmartSVN (Integrated with MultiSite) SME ($) Training Videos e‐commerce Platform / Appstore uberSVN Empire (Team
Slide 18: Feasibility study completed 'in the lab'
• Feasibility study completed ‘in the lab’ • Phased approach 18
Slide 19: WANdisco Technology
Traditional Approach WANdisco Technology Hadoop Approach 19
Slide 20: Life Cycle: Four Basic Stages
~” ® i. =) _ © = oe. \e) ‘e) xe) © v8 Life Cycle: Four Basic Stages Maturity Introduction Growth 20
Slide 21: smartSVN asset purchase
• User Interface (client) for Subversion. • Very popular Subversion client application • Asset purchase 21
Slide 22: Our AIM scorecard so far
Our AIM scorecard so far ¢ Build out the offer — Big Datav — Expansion of current product set ¥ — Opened new (cost effective) development center in Belfast ¥ — Purchased smartSVN technologyY * Build out the sales team - Key hires from established players such as IBM ¥ ¢ Expand into Asian market, esp
Slide 23: Good progress made, confident in outlook
• Good progress made • Confident in our Outlook 23
Slide 24: Appendix
navis CKROCK amt hk EMC: =a =A § py B ® Feo OW Jol . fohmonafohneon ace ep vane . symantec. ]atat y Jord a Appendix
Slide 25: Key Drivers for Big Data
Key Drivers for Big Data BIG DATA Sensors / RFID / Devices <i User Generated Content | Mobile Web Sentiment Social Interactions & Feeds User Click Stream Spatial & GPS Coordinates f details Customer Touches Support Contacts Increasing Data V. 25
Slide 26: Data collected and stored continues to grow exponentially
• Business • Data collected and stored continues to grow exponentially • Financial 26
Slide 27: Hadoop master and slave nodes
Master node Name Job Node Tracker Slave / Data nodes Data Data Data Data Node Node Node Node Task Task Task Task Tracker Tracker Tracker Tracker 27
Slide 28: Name node single point of failure
- yet If name node fails, the whole cluster is in- operable ¢ Because Name-Node (Master) has the ‘meta data’ (block locations) 28