1. ‘Big Data’ Panel Discussion Using data in applications Digital Ship Hamburg 2015

2. What is ‘big data’?

3. The 5 V’s of Big Data Volume – the vast size of the dataset Velocity - speed data is generated and moved around Variety – different types and formats of data you can use Veracity – the trustworthiness of the data Value - needs to add value and make business sense.

4. ShipServ in data numbers 9,000 vessels putting 80% of their purchasing spend 7 million transactions per year $3bn worth of spend per year 35 million products and services purchased per year Around 4 billion pieces of ‘purchasing information’ 55,000 suppliers Multiply by 15 years

5. How we use ‘big data’ to bring Value

6. ShipServ Match and our Matching Engine’ ShipsOfficeShipServSuppliers / Logistics Providers On-board System or Excel Forms Your Purchasing System REQ Supplier ShipServ Integration Logistics Provider Integration Web App Integration “Matching Engine” RFQ Our Matching Engine will reduce unit costs through: Better prices Reduced freight costs Use from within your existing purchasing system No training required The RFQ is also sent to the Matching Engine which deduces the best possible alternative suppliers RFQ PO QOTDELINV Quotes from your usual suppliers and from ShipServ Match selected suppliers In addition to your usual suppliers you send your RFQ to ShipServ Match

7. How our Matching Engine works Apply 4,000 purchasing years to every purchase decision you make

8. Using ‘big data’ to produce Spend Analytics Focus on nine spend categories And horizontal spend categories including Services, Tools, Valves, Electrical, etc

9. Spend on ShipServ by category Source: ShipServ analysis based on TradeNet data

10. By vessel type: Cruise Ships Average Monthly Spend * 2013 Monthly Spend based on average of Jan-Dec Monthly averages ** 2014 Monthly Spend based on average of Jan-May Monthly averages

11. By vessel type: Offshore Supply Vessels ** 2014 Monthly Spend based on average of Jan-May Monthly averages * 2013 Monthly Spend based on average of Jan-Dec Monthly averages Average Monthly Spend

12. OSV Deck Stores & Machinery Spend Source: ShipServ analysis based on TradeNet data

13. Panel Discussion How does a shipping company create additional Business Intelligence tools from big datasets? How does a Class Society use ‘big data’ to monitor fleet performance? How is a Main Engine supplier using ‘Ship Intelligence data’? Will connectivity hinder the collection of ‘big data from the vessel?