Data Convergence to Insight

Transcription

1 Data Convergence to Insight G R E G WI L K I N S V I C E P R E S I D E N T, G L O B A L C O M M E R C I A L S O L U T I O N S V E S O N N A U T I C A L

2 Agenda Introduction Why Are We Discussing Big Data? General Example of Big Data Shipping Examples of Big Data Conclusion

3 Integrated Maritime Operations System (IMOS) and Veslink PLATFORMS FOR COMMERCIAL SHIPPING DATA Charterers Counterparties Operators Service Providers Finance Voyage Partners Traders Vessels

4 Today s Challenging Shipping Market 8 years of market volatility No clear indication it is going to improve Low rates Baltic rates vary around the globe Global supply and demand changing dramatically Bunker costs vary greatly Freight rates and secondhand values are expected to remain low during the next two to three years, while newbuilding prices are expected to return to the lower levels seen in early Danish Ship Finance (Danmarks Skibskredit A/S) Shipping Market Review, May 2015

5 Data Analytics to Make Decisions In a rapidly changing global business environment, the pressure on organizations to make accurate and timely decisions has never been greater. The ability to identify challenges, spot opportunities, and adapt with agility is not just a competitive advantage but also a requirement for survival. Harvard Business Review 2012: The Evolution of Decision Making: How Leading Organization Are Adopting a Data-Driven Culture

6 How Are You Making Decisions? In good markets, only the most disciplined will ask themselves how they can improve. In difficult markets, everyone needs to ask themselves how they can improve.

7 In good markets only the most disciplined will ask themselves how they improve. In difficult markets you are challenged to make your self better to Adapt or Die

8 What Credit is an example Score of Big Data? MORTGAGE 725

9 What is the Conclusion? USA Credit Score Excellent Credit 750+ Good Credit Fair Credit Poor Credit Bad Credit Below 600

10 The Data Volume Collect lots of and ensure it s comprehensive Veracity Assess sources of information and validate it s correct Variety Capture from diverse scenarios, representing a broad view Velocity Efficiently collect in near real time Source: IBM

11 Ask Insightful Questions What could happen? Predictive analytics What action should I take? Decision management 1 2 What happened? Discovery Why did it happen? Reporting and analysis

12 Four Shipping Examples 1. Examples of Key KPIs Forecast vs. Budget for the year Profitability of a particular contract 2. Client Example of Hull Cleaning 3. Integration with Business Intelligence Tools 4. Sharing Data with Partners

13 Example 1 Integration with Other Data to predict price and exposures

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16 Example 2 Hull Cleaning & Efficiency

17 Example 3 Integration with BI Tools (Tableau)

18 Tableau Software

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22 Example 4. Sharing Data with Partners

23 Sharing Data with Partners International global materials company Hires vessels in on spot or short TC basis

24 Sharing Data with Partners Wanted to Share ETA and Change information with: Customers Internal Traders Management Manage port costs and agent information International global materials company effectively Ensure visibility to loading and off-loading in a usable format Hires vessels in on spot or short TC basis

25 Sharing Data with Partners International global materials company Prior to Veslink All done via Not standard nor recorded Not associated with any context No standard process of delivering information to other constituents

26 The Solution International global materials company With Veslink Automate the process of gathering Standardize the flow of information Store that information in a standard format that could be easily utilized Visualize and report on the information to all the recipients Automate the process of delivering the information

27 Questions our Customers Use Data to Answer For Operators: What is the profitability of a contract? How is budget performing against forecast? What is the profitability of a particular route? How is a vessel performing? Should I slow steam? For Owners: Where is my vessel? How is it preforming vis-à-vis the contract? Cash flow vs. budget vs. market? For Charterers: Are my estimates right? Where are my exposures to the market? Can I do it more profitably vs. the market? What is available in the market today?

28 Conclusion Research to understand the variables that affect your business. Compile and integrate from your sources to achieve visibility. Ask insightful, predictive questions that your can answer. Monitor and adjust the questions you are answering as-needed. Visualization will help to make your more readable and usable to a broader audience.

29 Thank you! For more information, please contact or