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.

Attending the Safety Data Collection and Analysis (Initial)

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.
• Types of analysis.
• Descriptive Analysis.
• Inferential analysis.
• Predictive analysis.
• Combined analysis.
• Reporting of analysis results.

Day 2

• 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
• 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.
• 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