Slide 1: Full Year Results 2016
FULL YEAR RESULTS 2016 David Richards Chief Executive Officer Erik Miller Chief Financial Officer
Slide 2: Score Card
SCORE CARD PRIORITY IN FY 2016 RESULT Reduce cash consumption Cash overheads reduced by $11.2m to $23.4m without impact our ability to with significantly improved overall performance execute Traction in Big Data and Cloud Bookings increased by 184% with our Fusion technology Renewed focus on SCM (AL
Slide 3: Highlights: Operational
HIGHLIGHTS OPERATIONAL • Won 15 new Big Data and Cloud customers • Secured landmark OEM with IBM • Contract momentum through strategic partnerships with IBM, Amazon and Oracle. • $1m order for Fusion as part of Dubai’s Smart City project via HPE • $1.5m order for Fusion with a major US bank via Orac
Slide 4: WANdisco stands for Wide Area Network Distributed Computing
• WANdisco stands for: Wide Area Network Distributed Computing • World leader in Active Data Replication™ • IPO in 2012 on London Stock Exchange AIM, Symbol WAND • Dual headquartered in San Ramon, California and Sheffield, England • Our solutions are based on a mathematical proof developed by Co-Fou
Slide 5: Our Business Model
OUR BUSINESS MODEL • Pure software solutions / Intellectual property. • Very scalable, very high gross margin • WANdisco Fusion leverages burgeoning Big Data and Cloud markets • Customer base from the Global 2000 with recurring subscription revenue. • Operational leverage from strategic channel part
Slide 6: WANdisco Fusion
WANDISCO FUSION® • Created in 2015 • General purpose replication platform rather than a specific platform for Hadoop • Cloud, on-premises file systems, Hadoop • Fusion enables the replication of continuously changing data to the cloud and on-premises data centers with guaranteed consistency, no down
Slide 7: We Solve Active Data Replication to the Cloud
WE SOLVE ACTIVE DATA REPLICATION TO THE CLOUD WITHOUT WANDISCO FUSION WITH WANDISCO FUSION REPLICATION • Downtime • No downtime • Time-based one-way copy for low-volume ‘cold’ data • Moves data as it changes • Data movement always behind • Supports migration and hybrid use cases • Data consistency n
Slide 8: Computer science still says what we have done is impossible
“ COMPUTER SCIENCE STILL SAYS WHAT WE HAVE DONE IS IMPOSSIBLE BUT IT’S NOT.” Dr. Yeturu Aahlad Chief Scientist, Inventor & Co-Founder
Slide 9: The Big Data & Cloud Market
THE BIG DATA & CLOUD MARKET (Exabytes of Data) 1000 900 800 700 600 500 Cloud On-premises data centers 400 300 200 100 0 2015 2016 2017 2018 2019 2020 Source: Cisco Global Cloud Index: 2015-2020. Published 2016
Slide 10: Addressable Market for WANdisco Products
ADDRESSABLE MARKET FOR WANDISCO PRODUCTS (assuming 10% of all stored data requires continuous replication) $12 $10 $8 All else Billion $6 NFS Cloud Object Storage $4 Hadoop $2 $- 2015 2016 2017 2018 2019 2020 Non-Stop Fusion Fusion 3.0 Hadoop Source: Cisco Global Cloud Index: 2015-2020. Published 20
Slide 11: Progress with IBM
PROGRESS WITH IBM • April 2016 • Signed white label OEM agreement for “IBM Big Replicate” • June 2016 • IBM Big Replicate was generally available in the IBM price book. • August 2016 • WANdisco completed software engineering to integrate Fusion with IBM infrastructure. • September 2016 • Trained ~5,
Slide 12: Driving Car Technology Forward
USE CASE DRIVING CAR TECHNOLOGY FORWARD CHALLENGE • A major automotive manufacturer needed to ensure vehicle data moved seamlessly between data centers and the cloud to fulfill the growing demand in the sector for driverless technology and predictive maintenance. Current solution required an outage
Slide 13: Data Resilience for a Major US Bank
USE CASE DATA RESILIENCE FOR A MAJOR US BANK CHALLENGE • Implementing Oracle Big Data Appliances for key financial applications including fraud detection, regulatory compliance and customer retention. Required to have disaster recovery and recovery time point within a tolerable range. Systems could
Slide 14: Disaster Recovery and Efficient Use of Resources for a Major Retailer
USE CASE DISASTER RECOVERY AND EFFICIENT USE OF RESOURCES FOR A MAJOR RETAILER CHALLENGE • Implementing Hadoop and cloud (Microsoft Azure) to replace existing legacy storage. Economics of Hadoop didn’t work (vs. legacy) so needed to utilize second DR datacenter for compute workloads. Replication sol
Slide 15: Financial Results
Financial Results Erik Miller Chief Financial Officer
Slide 16: Highlights: Financial
HIGHLIGHTS FINANCIAL • Total bookings for the year up 72% to $15.5m (2015: $9.0m) • Big Data & Cloud bookings rose 184% to $7.1m (2015: $2.5m) • SCM bookings rose 29% to $8.4m (2015: $6.5m) • Revenue for the year up 4% to $11.4m (2015: $11.0m) • Operating expenses were reduced by $11.2m to $23.4m (2
Slide 17: Big Data and SCM Sales
BIG DATA AND SCM SALES BIG DATA Big Data sales metrics (averages) • 15 new Fusion customers Value $286k Mix of large rollouts and per contract smaller-scale projects • 8 scale-up and renewal deals Range of pricing • New sales bookings $7.1m Price $1,300 per node per year (2015: $2.5m) Volume pricing
Slide 18: Recognized Revenue
RECOGNIZED REVENUE • Revenue increased $400k to $11.4m Bookings to revenue ($m) 2016 2015 from $11m in 2015 Sales Bookings 15.5 9.0 • SCM average subscription term New deferred revenue (12.0) (6.5) length of over 2 years New recognised revenue 3.5 2.5 • Deferred revenue of $12.5m, $5.8m o which will
Slide 19: Profit & Loss
PROFIT & LOSS $m $m 2016 2015 change SCM refocus and ramping Big Data New sales bookings 15.5 9.0 6.5 significantly improved bookings Revenue 11.4 11.0 0.4 New sales + deferrals Cost of sales (1.4) (0.8) (0.6) Sales commissions Gross profit 10.0 10.2 (0.2) Headcount reduced from 143 to 118 at 31 ‘CA
Slide 20: Cash Flow
CASH FLOW Working capital ($m) 2016 2015 Cash flow ($m) 2016 2015 Receivables 4.7 5.1 Payables (3.5) (2.7) Adjusted EBITDA (7.5) (16.0) Deferred revenue (12.5) (9.8) Net working capital (11.3) (7.4) Net working capital change 3.9 (1.7) Currency, interest, tax 1.3 0.1 Cash flow from operations (2.3)
Slide 21: Summary and Outlook
SUMMARY AND OUTLOOK THE ONLY VIABLE SOLUTION FOR ACTIVE DATA REPLICATION AT SCALE SOFTWARE LEVERAGED TO BURGEONING CLOUD COMPUTING MARKET GLOBAL 2000 CUSTOMER BASE WITH RECURRING REVENUE ACCELERATING TOP-LINE GROWTH AND NARROWING LOSSES IMPROVED BALANCE SHEET NEARING POSITIVE CASH FLOW EXPERIENCED,
Slide 22: Thank You
> WONDISCO The World Leader in Active Data Replication™ THANK YOU ae? a» ns on Se —-,_ 2 eam wandisco.com
Slide 23: Go to Market
GO TO MARKET DIRECT: OEM INDIRECT : STRATEGIC PARTNERS SOURCE CODE MANAGEMENT DIVERSE AND GROWING CUSTOMER BASE Financial Services Automotive Healthcare Government Major US Bank Multinational Auto Manufacturer Fighting Dementia Dubai
Slide 24: Using Big Data to Fight Dementia
USE CASE USING BIG DATA TO FIGHT DEMENTIA CHALLENGE • An EU funded initiative which could make it easier for doctors to spot the early signs of dementia needed to move big data between eight different cloud providers for analysis so it could be analysed by over 950 different applications. SOLUTION •
Slide 25: Financial Highlights
FINANCIAL HIGHLIGHTS 2016 2015 Strong growth in bookings Big Data ramping $15.5m $9.0m Growth in revenue Recognized Revenue $11.4m $11.0m Significantly reduced cost base ‘Cash’ Operating Costs $23.4m $34.6m EBITDA loss more than halved Adjusted EBITDA* ($7.5m) ($16.0m) Cash position Cash, no debt $7
Slide 26: Total Addressable Market (TAM) for Continuous Replication
TOTAL ADDRESSABLE MARKET (TAM) FOR CONTINUOUS REPLICATION (if all stored data is continuously replicated) $120,000,000,000 $100,000,000,000 $80,000,000,000 $60,000,000,000 Cloud On-premises data centers $40,000,000,000 $20,000,000,000 $- 2015 2016 2017 2018 2019 2020 Source: Cisco Global Cloud Index
Slide 27: Total Addressable Market (TAM) for Continuous Replication
TOTAL ADDRESSABLE MARKET (TAM) FOR CONTINUOUS REPLICATION (assuming 10% of all stored data requires continuous replication) $12,000,000,000 $10,000,000,000 $8,000,000,000 $6,000,000,000 Cloud On-premises Data Center $4,000,000,000 $2,000,000,000 $- 2015 2016 2017 2018 2019 2020 Source: Cisco Global