Safety Data Collection and Analysis (Initial)

Safety Data Collection and Analysis Course for Safety Managers and Safety Specialists

Level: Initial

Duration: 12 HRS (3 Days)

Who Should Attend

  • Safety Managers
  • Safety Specialists

Prerequisites

  • High Academic Degree
  • Good Command In English
  • Attending the Safety Fundamentals and Culture (Initial) course - click here
  • Attending the Safety Risk Management (Initial) - click here
  • Attending the SMS Implementation and Control Course (Initial) - click here
  • Attending the Safety Performance Management (Initial) Course - click here

Objectives

By the end of this course participants will be able to:

  • Develop and maintain the means to verify their safety performance by means of SDCPS
  • Ensure that it has personnel competent to collect and store the safety data.
  • Select the appropriate safety data collection methods.
  • Share safety information with appropriate levels.
  • Determine what to collect of safety data.
  • Apply mandatory safety reporting system.
  • Categorize safety data ideally be using taxonomies and supporting definitions.
  • Determine aspects of data quality.
  • Apply safety data processing methods.
  • Analyze the safety data and safety information from the SDCPS and associated safety databases.
  • Identify of systemic and cross-cutting hazards that might not otherwise be identified by the safety data analysis.
  • Establish effective safety metrics.
  • Establish safety presentation capabilities (e.g. safety dashboard.
  • Monitor safety performance of a given sector, organization, system or process.

Contents

  • Day 1
    • Safety data collection and processing systems.
    • Introduction.
    • Safety data and safety information collection.
    • Effective Management of Safety.
    • Regulations
    • SDCPS Safety Data Collections Processing System
    • Personnel Qualifications
    • Taxonomies.
    • Sharing Safety Information.
    • Determining what to collect.
    • Safety data processing.
    • Safety data and safety information management.
    • Safety analysis.
    • Introduction.
    • Analysis Requirements.
  • Day 2
    • Types of analysis.
    • Descriptive Analysis.
    • Inferential analysis.
    • Predictive analysis.
    • Combined analysis.
    • Reporting of analysis results.
    • Data Driven Decision Making (D3M).
    • Safety analysis results Example.
    • Safety dashboards.
    • Data Driven Decision Making (D3M).
    • Safety information sharing and exchange.
    • Sharing within the State.
    • Level of Protection.
  • Day 3
    • Data-driven decision-making
    • Good decisions
    • Advantages of data-driven decision-making
    • Common challenges with data-driven decision-making
    • Avoiding “Analysis Paralysis
    • Data-driven decision-making process.
    • Step 1 – Defining the problem or objective
    • Step 2 – Access to data to support the decision-making
    • Step 3 – Request data to support the decision-making
    • Step 4 – Interpret results of data analysis and make data-driven decision
    • Step 5 – Communicate the decision.
    • Decision-making models.
  • Day 4
    • Protection of safety data, safety information and related sources.
    • Objectives and content
    • Fundamental principles
    • Scope of protection
    • Level of protection
    • Principles of protection
    • Principles of exception
    • Public disclosure
    • Protection of recorded data
    • Safety information sharing and exchange
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