apis briefing

22
Analytic Port Information System PARADIGMA, Vienna, August 7, 2012

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Page 1: APIS Briefing

Analytic Port Information System

PARADIGMA, Vienna, August 7, 2012

Page 2: APIS Briefing

Page 2

PARADIGMA & Transportation Sector

Market potential study for transport relations between the Eastern

Mediterranean and Central Europe (Venice/Italy)

Identify cargo, consigners/consignees, transportation service providers

Statistical production, marketing potential and business development

Feasibility studies to connect the Baltics with the Adriatic using rail

links (Venice/Italy, Szczecin/Poland, EU funded project)

Production of national road transportation statistics using ICT

(R&D project with freight forwarders, truckers and academic institutions)

Utilize existing transport management systems and onboard technology

Establish the empirical foundation for Austria's road transport model (Ministry of Transport and Infrastructure)

Combine different survey‟s and administrative data sets

Identify barriers to multimodality ( in Europe) and develop case

studies to test their economic and ecological impact (Bologna, EU

funded project)

Page 3: APIS Briefing

Page 3

PARADIGMA & Maritime Ports

Port of Livorno and its role in a multimodal transport process

Supply chain development of imports of Subaru cars from Japan to Italy, crossing the Alps and to the national car distributor.

Port of Ravenna and inland ports in the empty container movement cycle

Business process modeling and prototyping to manage the relocation of empty containers.

Port of Venice and monthly tracking of cargo movements (maritime, road and rail)

Combining data from APV‟s own port community system, with rail shunting data and traffic counts from the highway administration

Mediterranean ports

Page 4: APIS Briefing

… a set of methods and software components to support Port

Authorities in their the analytical, planning, monitoring, controlling

and publishing work.

Maritime ports are faced with a plethora of challenges that require

decisions founded on solid empirical evidence as opposed to

subjective experience only.

In spite of the considerable investment in information technology

made in the past, port communities are not satisfied with the quality

of the data nor with the decision support.

More often than not information is not current, lacks detail as well as

reliability making any analysis, no matter how sophisticated, which is

based on such data, dubious at best.

Page 5: APIS Briefing

Page 5

Managing

Complexity

Balanced

Scorecard

In-Depth

Analysis

Dissemination &

Publication

Integrating data from disparate sources (PCS, statistics, road counts, railroad systems, AIS, …) using ETL engines

Classification Management System

A comprehensive set of performance indicators

Visualizations tailored to highlight the information content

Easy definition and implementation of additional PPI„s

Analysing trends and deviations by means of reach statistics functions and visual data analysis tools (SuperCROSS, SuperWEB)

Interfaces for use of industrial analytical tools (SPSS, SAS, R, … )

Integration of demand driven reports and visualization using microdata (SuperVIEW) in existing web applications

SDMX interface to comply with statistical reporting requirements

Components of APIS

Page 6: APIS Briefing

Page 6

Different sources – different data – same business

Terminal operators Rail operators/carriers Road transport comp. Customs/officials Gov‘t/official statistics

By location of

origin,

destination

or transit

By cargo or

products

traded

By means of

transport or

transport

equipment

Page 7: APIS Briefing

Page 7

Managing

Complexity

Balanced

Scorecard

In-Depth

Analysis

Dissemination &

Publication

Integrating data from disparate sources (PCS, statistics, road counts, railroad systems, AIS, …) using ETL engines

Classification Management System

A comprehensive set of performance indicators

Visualizations tailored to highlight the information content

Easy definition and implementation of additional PPI„s

Analysing trends and deviations by means of reach statistics functions and visual data analysis tools (SuperCROSS, SuperWEB)

Interfaces for use of industrial analytical tools (SPSS, SAS, R, … )

Integration of demand driven reports and visualization using microdata (SuperVIEW) in existing web applications

SDMX interface to comply with statistical reporting requirements

Components of APIS

Page 8: APIS Briefing

SMART criteria

SMART

Specific

Measurable

AttainableRealistic

Time-sensitive

Page 8

SpecificLoose, broad or vague goals are not desirable. Specific

goals allow to hold someone to account for their

achievement.

MeasurableThe measure may be quantitative or qualitative, but

measurement should be against a standard of performance

and a standard of expectation.

AttainableGoals should not be out of reach but reasonable and

attainable. Setting goals is a balance between this degree

of “attainability” and challenge and aspiration.

RealisticA goal might be attainable, but not realistic in the

particular working environment. A realistic goal helps

examining the availability of resources and selecting PPIs.

Time-sensitiveGoals should have a time frame or completion date to

monitor progress. This is instrumental in developing a

realistic action plan including intermediate objectives.

Requirements

rating

Page 9: APIS Briefing

Using AIS data to measure dwell times in port areas

Page 9

Page 10: APIS Briefing

Page 10

PPI catalog

Select suitable indicators

… based on best industry practice and research

Perspective Requirement Indicator Computation Unit type Unit Direction

Processes Productivity Dwell time Total no. of cargo tons x days

in port divided by Total

tonnage of cargo handled

time hours Minimize

Asset Throughput Berth

throughput

Total tonnage of cargo

handled at berths divided by

Total no. of berths

number tons Maximize

Finance Income Income per

GRT of shipping

Total income (expenditure)

divided by Total GRT (or NRT)

of shipping

number € Maximize

Processes Efficiency Average

tonnage per

vessel day

Total tonnage of cargo

handled divided by (hour)

Total no. of vessel days

(hours)

number tons Maximize

Processes Efficiency Average ship

turn-round

time

Total hours vessel stay in port

divided by Total no. of vesselstime hours Minimize

Page 11: APIS Briefing

Page 11

Managing

Complexity

Balanced

Scorecard

In-Depth

Analysis

Dissemination &

Publication

Integrating data from disparate sources (PCS, statistics, road counts, railroad systems, AIS, …) using ETL engines

Classification Management System

A comprehensive set of performance indicators

Visualizations tailored to highlight the information content

Easy definition and implementation of additional PPI„s

Analysing trends and deviations by means of reach statistics functions and visual data analysis tools (SuperCROSS, SuperWEB)

Interfaces for use of industrial analytical tools (SPSS, SAS, R, … )

Integration of demand driven reports and visualization using microdata (SuperVIEW) in existing web applications

SDMX interface to comply with statistical reporting requirements

Components of APIS

Page 12: APIS Briefing

Page 12

PPI Analysis

… control target achievement

Terminal turnover by

cargo typesBullet graph array

Page 13: APIS Briefing

Page 13

GTDS for Transportbased on SuperVIEW technology

Web analysis of transport & trade flows

Page 14: APIS Briefing

In-depth desktop analysis tool: SuperCROSS

Page 14

Page 15: APIS Briefing

Page 15

Managing

Complexity

Balanced

Scorecard

In-Depth

Analysis

Dissemination &

Publication

Integrating data from disparate sources (PCS, statistics, road counts, railroad systems, AIS, …) using ETL engines

Classification Management System

A comprehensive set of performance indicators

Visualizations tailored to highlight the information content

Easy definition and implementation of additional PPI„s

Analysing trends and deviations by means of reach statistics functions and visual data analysis tools (SuperCROSS, SuperWEB)

Interfaces for use of industrial analytical tools (SPSS, SAS, R, … )

Integration of demand driven reports and visualization using microdata (SuperVIEW) in existing web applications

SDMX interface to comply with statistical reporting requirements

Components of APIS

Page 16: APIS Briefing

Live monitoring web interface

Page 16

Page 17: APIS Briefing

Website integration of self-service charts

Page 17

Page 18: APIS Briefing

Page 18

Beneficiaries & benefits

Enhance the competitive position of ports

Improve the efficiency and visibility of supply chains (door-door)

Enhance the image of the port, provide meaningful information to the public and industry players.

Consolidated and aggregated statistics will serve as a benchmark for terminal operators and LSP’s

LSP’s will be able to increase the transparency and visibility of the Supply Chains

LSP’s will be able to develop innovative logistics concepts

Public Administration and transport planners will be able to guide public policy formulation.

Customs will be able to monitor and analyze the development of traffic and cargo movements, combining APIS with their own data to detect potential safety and security exposures.

Page 19: APIS Briefing

APIS Hallmarks & Differentiators

Page 19

Seamless integration with existing PCS and other datasources, without

impacting the performance of the operational systems

Enabling different user groups within the port community to develop their

own analysis from simple tables to advanced analytics without the

involvement of IT staff

Comprehensive set of predefined and extensible indicators which allow

the management of the port to plan, manage and monitor the execution

of strategies

Built in and customizable access control features, ensuring the

confidentiality and sensitivity of underlying microdata

1

2

3

4

5

A comprehensive and consolidated view of all essential aspects of a ports

business ready for analysis and reporting

Integrated mechanisms (SuperVIEW, SDMX) to support the publication and

dissemination of statistics, meeting stakeholder expectations and

complying with international reporting requirements6

Page 20: APIS Briefing

Backup

Page 20

Page 21: APIS Briefing

Page 21

APIS Architecture

Page 22: APIS Briefing

APIS Deployment phases

Page 22

Map local data sources

(PCS) to the

consolidated APIS data

model (using NLIP

standards)

Customization & training of customer personel

Adapt and calibrate

port performance

indicators to local

levels

Provide role

adequate training

for management,

analysts and system

administrators

Align APIS reporting

to the requirements

of the port.

Integrate in existing

INTRA – INTERNET

platforms.

Purchase licences for

productive usage

Interconnect APIS

with existing software

applications

Data

consolidation

Report

alignment

Calibrate

PPI„sIT integration Training