Using data in applications Digital Ship Hamburg 2015 What is big data The 5 Vs of Big Data Volume the vast size of the dataset Velocity speed data is generated and moved around ID: 473073
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Slide1
‘Big Data’ Panel Discussion
Using data in applicationsDigital Ship Hamburg 2015Slide2
What is ‘big data’?Slide3
The 5 V’s of Big DataVolume – the vast size of the datasetVelocity
- speed data is generated and moved aroundVariety – different types and formats of data you can useVeracity – the trustworthiness of the data Value - needs to add value and make business sense.Slide4
ShipServ in data numbers9,000 vessels putting 80% of their purchasing spend 7 million transactions per year
$3bn worth of spend per year35 million products and services purchased per yearAround 4 billion pieces of ‘purchasing information’55,000 suppliers Multiply by 15 years Slide5
How we use ‘big data’ to bring ValueSlide6
ShipServ Match and our Matching Engine’Ships
OfficeShipServSuppliers / Logistics Providers
On-board System or Excel Forms
Your Purchasing System
REQ
Supplier
Supplier
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
QOT
DEL
INV
Quotes from your usual suppliers and from ShipServ Match selected suppliers
In addition to your usual suppliers you send your RFQ to
ShipServ MatchSlide7
How our Matching Engine works
Apply 4,000 purchasing years to every purchase decision you make Slide8
Using ‘big data’ to produce Spend AnalyticsFocus on nine spend categories
And horizontal spend categories including Services, Tools, Valves, Electrical, etcSlide9
Spend on ShipServ by category
Source: ShipServ analysis based on TradeNet
data Slide10
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 averagesSlide11
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 Slide12
OSV Deck Stores & Machinery Spend
Source: ShipServ analysis based on
TradeNet
dataSlide13
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?