USING BIG DATA & ANALYTICS TO MAKE SMARTER DECISIONS Capt Rohit Talwar
Big Data Frontier for Analytics & Smarter Decisions COMPLEXITY: Big Data refers to datasets whose size is beyond the ability of a typical database software tools to capture, store, manage & analyze. SIZE : Big Data is not defined in terms of larger than certain number of terabytes, as it is assumed that as technology advances over time, the size of datasets which qualify as Big Data would also increase. VELOCITY: There was a time when we used to believe that data of yesterday is recent. The data movement is now almost real time and the update window has reduced to fractions of the seconds. This high velocity data represent Big Data. FORMATS : Data can be stored in multiple format. For example database, excel, csv, access or form of video, SMS, pdf or something we might have not thought about it. It is the need of the organization to arrange it and make it meaningful. This variety of the data represent Big Data
Big Data at Big Companies
Big Data in Shipping Building on the incumbent SVISTM platform, RightShip Qi harnesses big data, predictive analytics and real-time risk assessments. It has the ability to instantaneously analyse, compare and integrate data such as port state control inspections, casualty history, satellite data and terminal feedback to identify anomalies and trends. CargoSmart plans to use TIBCO technology to gain visibility into port status. Using current port conditions including vessels waiting and in berth, departures times at the loading port, arrival times at the discharging port, real-time ocean traffic conditions, sailing directions, and speeds real-time intelligence on vessel arrival and port congestion can be obtained. Daewoo Shipbuilding & Marine Engineering (DSME), one of the world s largest shipbuilding and offshore companies, has engaged IBM to help the company better manage its Big Data challenges
Big Data Production on Ships Vessel & Voyage Vessel Performance & Tracking Voyage Reporting Bunkering Quality & Safety Incidents, accidents, near miss Audits & Inspection Defect Tracking & Reporting SEEMP Compliance Monitoring MARPOL Compliance Monitoring Planned Maintenance Equipment Catalogue Overdue/Postponed/Drydock Job management Job Execution with parameters for PTW & Risk Assessment Job deferment with approval from shore Job History Crewing Crew data maintenance Relief Planning & Planning Matrix Contracts
Big Data Production on Ships Procurement Requisition from vessel Vendor Quote Comparison Purchase Order & Inventory Integration with Shipserver Ship board Admin Document Control Record Control ISM/ ISPS Compliance Contingency Planning Work & Rest Hour Damage Stability Salvage Management Crisis management Commercial Compliance Charter party reporting Charter party speed Port Papers
Value in Big Data Move from traditional management through alerts and reports to Dashboards Analytics Visualization Infographics Predictive / Machine Learning
Smart Decisions Some Examples where Big data can help in making Smarter Decisions Reduce injuries and increase workplace safety predictive Improving Audit & Inspection Performance - No deficiencies Cargo safe handling Route optimization Fuel Efficiency Crew competency and psychology
Analytics Case Study PSC Performance Monitoring Performance
Analytics Case Study PSC Performance Using Analytics to Enhance Priority Preparation
Predictive Case Study Probability of Navigation Accident
Predictive Case Study Probability of Navigation Accident *This preliminary model is built based on the model by DNV and covers factors of different nature like technical factors, human factors, organizational factors and environmental factors etc.
Predictive Case Study Reducing Workplace Injuries As per a study, carried out by Predictive Solutions in 2012, by the application of following four Safety Truths, we can reduce workplace injuries
Predictive Case Study Reducing Workplace Injuries Application of the Safety Truths would require Analytics 1. All Inspections needs to be evaluated. Weak Areas / Processes assessed. Corrective Actions implemented. Success of Corrective Actions Verified. 2. More Inspectors would allow the variety in the inspections & hence variety of data processing 3. Too Many Safe inspections to raise an alert 4. Too Many Unsafe inspections to raise an alert
Big data - Challenges (How to capture value in big data what needs to be done) Business leaders need to do Build inventory of existing data sets (propriety), use public data or purchase Identify value creation opportunities Address shortage of talent / deep analytical talent / Address talent gap in managers and analyst need to consume big data Address needs for technology and deployment Address privacy, legal and contractual issues
Big data Leverage over other Companies (How to leverage Big Data) Making Big Data more accessible to relevant Stakeholders in a timely manner can create tremendous value. Better Management Decisions use the ability to collect and analyse big data to conduct controlled experiments to make better management decisions. Segmenation - segmentation of customers/stakeholders and therefore much more precisely tailored products or services. Sophisticated analytics improve decision-making, minimise risks, and unearth valuable insights that would otherwise remain hidden.
Contact Information Rohit Talwar Group HSSEQ Manager Email: Rohit.Talwar@thome.com.sg Mobile:+65 9179 2788 Rajan Vasudevan CEO, OceanManager Email : rrajanv@oceanmanager.com Mobile : +65 8363 7040 (SG) / +1 801 809 8671 (US) 25