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Data Strategy

At a glance

Symphonic Management Consulting was engaged to support a leading Australian soil carbon project developer through the development of a comprehensive data strategy. The engagement focused on establishing a clear roadmap across data governance, classification, access, and advanced analytics to support long-term operational and strategic objectives. 


Data-driven decision-making is becoming increasingly important in agriculture and environmental sectors, particularly for organisations managing large-scale soil carbon projects. These environments involve complex data sources, regulatory requirements, and operational variability, making it critical to establish structured data governance, integration, and analytics capabilities.  

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client's overview and story icon

Client Overview

DNX Solutions is an Australian cloud-native focused company and an Amazon Web Services (AWS) Premier Consulting Partner. To ensure the successful DNX engagement with a leading soil carbon project developer, Symphonic Management Consulting took the initiative to develop and document a comprehensive data strategy for their client. The DNX client required a strategy that would address critical aspects of data governance, taxonomy, data access, data classification, Geographic Information Systems (GIS) and satellite imagery integration, business intelligence (BI), and artificial intelligence (AI) implementation. 

Challenges

The client faced a range of challenges in developing and implementing a comprehensive data strategy within a complex agricultural and environmental context. These included fragmented data sources, evolving regulatory requirements, and the need to manage diverse datasets across soil, climate, and supply chain systems.


There was also a need to improve data visibility, consistency, and governance to support more reliable decision-making and long-term operational scalability.

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Solutions

Symphonic developed a structured data strategy designed to address immediate operational needs while establishing a foundation for long-term capability. The approach focused on strengthening data governance, improving accessibility and classification, and enabling advanced analytics aligned with the client’s strategic objectives. 

Assessment

Stakeholder Interviews

Stakeholder Interviews

Conducted a thorough assessment of the client's existing data landscape, including data sources, storage, and management practices. 

Stakeholder Interviews

Stakeholder Interviews

Stakeholder Interviews

Engaged key stakeholders within the organisation to gather insights into data requirements, pain points, and strategic goals. 

Data Classification

Stakeholder Interviews

Access Control Design

 Implemented data classification policies and tools, assigning sensitivity labels to data assets. 

Access Control Design

Stakeholder Interviews

Access Control Design

Designed a data access control framework to ensure secure and efficient data access, involving role-based access controls (RBAC) and encryption mechanisms. 

Regulatory Compliance

Business Intelligence framwork

Business Intelligence framwork

Conducted a compliance audit to identify areas of improvement regarding data governance and data protection. 

Business Intelligence framwork

Business Intelligence framwork

Business Intelligence framwork

 Deployed BI tools and platforms to enable data-driven decision-making, dashboards, and reporting. 

AI and ML Integration Roadmap

Business Intelligence framwork

AI and ML Integration Roadmap

 Created a roadmap for the phased implementation of AI and ML solutions to address specific agricultural challenges, such as predictive yield modelling and pest control. 

Data Taxonomy Development

Business Intelligence framwork

AI and ML Integration Roadmap

 Collaborated with domain experts to design a comprehensive data taxonomy that aligns with the client's business processes. 

GIS and Satellite Imagery Integration

GIS and Satellite Imagery Integration

GIS and Satellite Imagery Integration

 Worked with geospatial experts to integrate GIS and satellite imagery data into the data infrastructure. 

Outcomes

The data strategy provided the foundation for improved governance, enhanced data utilisation, and more informed decision-making across the organisation: 

  • Improved Data Governance: The client now has a well-defined data governance framework in place, ensuring data quality, security, and compliance.
  • Enhanced Data Organisation: The implemented data taxonomy has improved data discoverability and usability, making it easier for employees to find and use data effectively.
  • Secured Data Access: Robust access controls and authentication mechanisms ensure that only authorised personnel access sensitive data, reducing security risks.
  • Data Classification: The data classification system helps the client prioritise data protection measures and allocate resources more effectively.

  • Business Intelligence: The BI framework provides actionable insights, helping the leading soil carbon project developer optimise crop management, supply chain logistics, and marketing strategies.
  • GIS and Satellite Imagery Integration: Integration of geospatial data has enhanced the client's crop monitoring capabilities, leading to more informed decisions and optimised resource allocation.
  • AI Integration: The client is now on a path to implementing AI and ML solutions that will further improve crop yields, reduce operational costs, and mitigate risks.

What This Case Illustrates

This case demonstrates how organisations operating in data-intensive environments require more than isolated technology solutions. A structured data strategy that addresses governance, accessibility, and long-term capability is essential to unlocking value and supporting scalable growth.

Benefits

Symphonic Management Consulting supported the development of a comprehensive data strategy that strengthened governance, improved data accessibility, and enabled more effective use of data across the organisation. The engagement helped establish a structured foundation for future analytics, including AI-driven capabilities, while supporting more consistent and informed decision-making.

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Date Published: 30 November 2023

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