About the client
Australia’s leading energy infrastructure business, manages and operates 15,000 kilometres of natural gas pipelines connecting sources of supply and markets across mainland Australia. Their portfolio includes assets (gas, electricity, solar and wind) worth around $26 billion with networks connecting 1.4 million Australian homes and businesses to the benefits of natural gas.
Understanding the Challenge
The Networks Asset Management Systems (NAMS) unit, managing a vast asset network and aspiring to leverage geospatial science for world-class energy solutions, faced significant challenges due to long-standing GIS data governance issues. Historical state-based GIS systems consolidation into a national GIS system inherited disparate data standards, quality gaps, and inconsistencies in data capture and currency, leading to inefficient reporting, higher operational risks, and low business confidence.
Recognising the critical need to address these challenges, NAMS engaged Codex to establish a structured approach to uplift their GIS data maturity and establish robust GIS data governance.
The initiative focused on:
- Performing a Data Maturity Assessment: A comprehensive evaluation of key categories – data governance, data quality, data management, GIS data & systems, supporting processes and data architecture was conducted, highlighting key deficiencies and prioritising areas for improvement.
- Implementing a Governance Framework: A tailored, organisation-wide data governance framework was designed and implemented, targeting business-wide alignment, visibility, and accountability for GIS data quality.
The lack of standardised GIS data quality frameworks across their Networks national GIS system has resulted in significant challenges.
Inconsistent Data Standards Across States
Historical state-based GIS systems operated independently with varying software versions, data standards, and practices. The consolidation into a single national system inherited these inconsistencies, leading to a lack of standardised data capture, formatting, and validation processes.Legacy Data Quality Issues
The national system incorporated unresolved historical data quality issues, such as missing, outdated, or incomplete records. Inconsistent data coverage and accuracy have made it difficult to trust the information for operational and reporting needs.Absence of Data Governance and Visibility
No formalised data governance framework exists to address the alignment of data standards, prioritization of issues, and tracking of remediation efforts. Teams lack clear accountability and visibility into data quality improvement initiatives, creating silos and inefficiencies in governance efforts.Manual Effort for Reporting and Transformation
GIS reporting requires extensive manual intervention to standardise and transform data to meet business and regulatory requirements. This results in inefficiencies, increased turnaround times, and higher chances of human error in critical reporting processes.Impacts on Operations and Regulatory Compliance
Data inconsistencies and inaccuracies directly affect key operational activities, such as BYDA (Before You Dig Australia) requests and engineering planning, increasing risk exposure. Regulatory reporting is hindered by data quality gaps, which pose risks of non-compliance and potential penalties.Low Business Confidence in GIS Data
The lack of a single source of truth and inconsistent data has eroded business users’ confidence, preventing the adoption of GIS as a strategic enabler. Self-service capabilities are underutilised as users cannot rely on data for decision-making or operational efficiency.These challenges underscored the need for a strategic uplift in data governance and quality management, paving the way for a structured approach to achieve the client’s vision of becoming world-class in energy solutions.
Solution
To address their challenges and support their vision, Codex proposed a comprehensive two-phase approach. This included conducting a Data Maturity Assessment and establishing a Data Governance Framework to uplift their GIS data governance and data quality practices.
Phase 1: Data Maturity Assessment
The Data Maturity Assessment provided a detailed understanding of the client’s current state of data governance and data quality, highlighting key gaps and opportunities for improvement.
Approach Taken:
Stakeholder Engagement
Engaged key business unit representatives across spatial & data services, operations, engineering & planning, capital delivery and GIS IT to identify pain points, challenges, and improvements expected in GIS data.
Maturity Scoring
Evaluated the client’s capabilities across five key data domains – Data Governance, Data Quality, Data Management, GIS Data & Systems, Supporting Processes and Data Architecture – against industry benchmarks and best practices.
Gap Analysis
Assessed gaps in people, processes and technology related to GIS data governance, focusing on challenges such as legacy data inconsistencies, operational inefficiencies, and lack of a single source of truth and documenting current state vs future state.
Prioritisation Framework
Created a roadmap highlighting critical focus areas, including governance, data standards, and data quality uplift activities.
Phase 2: Implementation of the Data Governance Framework
The Data Governance Framework was designed and implemented to address the identified gaps and enable a structured approach to managing GIS data.
Solution Provided:
Governance Structure
Established a multi-tier governance structure to define roles, responsibilities, and accountability, including:
- Group Data Council: Strategic oversight and decision-making body.
- Data Stewardship Council: Functional group responsible for implementing standards, prioritising issues, and driving improvements.
- Working Groups: Tasked with data capture, validation, and quality assurance.
Data Standards
Developed national-level GIS data standards to ensure consistency in data capture, formatting, reporting and compliance with industry standards.
Processes and Policies
Defined process for data quality issue management, including issue logging, prioritisation, and remediation tracking. Developed workflows for cross-state data alignment and validation to resolve inconsistencies.
Implementation
To address their GIS data challenges and support their vision of becoming world-class in energy solutions, Codex followed a structured implementation approach, focusing on:
1. Data Maturity Assessment
A comprehensive Data Maturity Assessment was conducted to evaluate the current state of GIS data governance and quality management. Key steps and methodologies included:
a. Structured Maturity Framework: Leveraged industry-standard CMMI data maturity model to assess capabilities across six core dimensions: data governance, data quality, data management, GIS data & systems, data architecture, & supporting processes.
b. Stakeholder Workshops and Interviews: Engaged with cross-functional teams, including GIS, Business & IT SMEs to understand pain points, current practices, and desired future state.
c. Data Profiling and Analysis: Reviewed sample datasets to identify critical issues such as inconsistencies, gaps, and compliance with FAIR principles (Findable, Accessible, Interoperable, Reusable).
d. Maturity Scoring and Gap Analysis: Scored the client’s GIS data maturity against benchmarks, identifying governance and quality management as the lowest scoring areas requiring immediate attention.
2. Data Governance Framework
Building on the maturity assessment, a Data Governance Framework was designed and implemented to address gaps and establish sustainable governance practices. Unique approaches included:a. Tailored Governance Model: ISACA governance model was tailored to develop their governance structure specific to GIS needs, defining roles such as Data Stewards, Data Owners & Data Custodians to drive accountability and oversight.
b. National Data Standards: Defined and documented GIS data standards to harmonise data capture, formatting, and validation processes across all states, enabling a unified national system.
c. Prioritised Data Quality Uplift: Established a data quality issue management process to focus on remediation efforts and governance levels involved in high-impact issues, such as regulatory reporting data and operational datasets.
d. Change Management and Training: Delivered workshops and training sessions to promote a culture of governance and ensure business users adopt and adhere to new processes.
Results
1. Data Maturity Assessment Conducted
Baseline Established
A comprehensive assessment provided a clear view of the client’s GIS data governance and quality maturity, highlighting gaps and opportunities across governance, data quality, and operational processes.
Key Data Initiatives & Prioritised Roadmap
Delivered a structured roadmap to address key gaps, including the need for standardised data governance practices and quality uplift initiatives, aligned with the client’s strategic vision. Breakdown of each initiative on the roadmap was provided elaborating key objective, envisaged value and detailed activities involved.
Improved Awareness
Enabled leadership and teams to better understand the impacts of data inconsistencies on operations, reporting, and regulatory compliance, fostering buy-in for governance improvements.
2. Data Governance Framework Implemented
Standardised Data Practices
Developed and rolled out a GIS Data Governance Framework with clearly defined roles, responsibilities, and accountabilities, ensuring cross-state alignment on data standards and processes.
Enhanced Data Quality Management
Introduced processes for systematic identification, prioritisation, and remediation of data quality issues, reducing manual effort for reporting and operational activities.
Regulatory Readiness with Data Standards
Established data standards enabled improved consistency and accuracy of GIS data, streamlining compliance with government-advised standards and reducing risk exposure in regulatory reporting.
Cultural Shift
Fostered a culture of data accountability and governance, with better visibility into data health and a collaborative approach to continuous improvement.
These outcomes have not only addressed their immediate challenges but also positioned them for long-term success in leveraging GIS as a strategic enabler for energy solutions.
In summary, a strong foundation was set up to address their GIS data governance and quality challenges, including inconsistent data standards, legacy data quality issues, and inefficient reporting processes. Through a comprehensive Data Maturity Assessment and the implementation of a robust GIS Data Governance Framework, the client successfully aligned their state-based data to a national standard which enabled mitigation of critical data inconsistencies.
This partnership underscores the importance of strategic data governance and quality management in fostering operational efficiency, regulatory compliance, and business confidence. With improved data alignment, established data standards & streamlined data quality processes, the client is now positioned to leverage this foundation in implementation of other processes & initiatives in this direction. This success highlights the transformative impact of structured data governance and quality initiatives on driving sustainable business growth.
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We would love the opportunity to connect and understand more about the problems you are trying to solve.
Abhinav Sharma
Partner
Shalini Kainthla
Senior Consultant
Get in touch to coordinate a meeting with one of our technical experts.
Australia: +61 7 3132 3002.
