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Title: Development of a Maturity Scale for Mining Performance and Maintenance Analytics
Organization

​Vale - The University of Queensland

Period

January 2019 - December 2021

Status

Completed

Est. Budget

USD 0.7M

Est. Business Benefit

USD 4.0M

Indicative Value-to-cost

5.7x

Keywords

Analytics maturity, maintenance analytics, governance, capability assessment, mining digital transformation

Benefit basis

Estimated value from improved analytics portfolio governance, reduced duplication of tools and models, and better prioritisation of maintenance/performance analytics investments.

Business Challenges 
Many mining organisations were investing in analytics while facing pressure to reduce operating cost, improve equipment performance, and lift maintenance productivity. However, analytics programs often failed to deliver expected value because sites lacked a consistent way to assess data readiness, process maturity, capability gaps, operating-model requirements, and benefit-realisation pathways. The challenge was to develop a mining-specific maturity scale that could objectively evaluate analytics capability and guide investment decisions.
Expanded Technical Solution
The project developed a maturity model specifically for mining performance and maintenance analytics. The model assessed maturity across data governance, data quality, system integration, analytics capability, operating-model ownership, maintenance-process alignment, benefit tracking, change management, and technology readiness. A structured questionnaire, interview protocol, scoring rubric, and benchmarking method were developed to compare maturity across sites and organisations. The framework converted qualitative responses into quantitative maturity scores and improvement roadmaps.
Technical Work Packages/Methods
  • Defined maturity dimensions for data, people, process, technology, governance, analytics use cases, operating model, and value realisation.
  • Developed a multi-level maturity scale ranging from ad-hoc reporting to optimised, embedded, predictive decision systems.
  • Designed survey and interview instruments for maintenance, operations, technology, reliability, data, and leadership stakeholders.
  • Created a scoring and weighting method to convert responses into maturity indices and gap analyses.
  • Produced roadmap logic linking maturity gaps to practical improvement actions, investment priorities, and governance changes.
Key Deliverables
  • Mining analytics maturity model and scoring framework.
  • Questionnaire, interview guide, and assessment methodology.
  • Benchmarking approach for Australian and Brazilian mining operations.
  • Roadmap template for analytics capability uplift and benefit realisation.
Results and Value Created
The project provided a structured way to identify why analytics initiatives succeed or fail in mining environments. It helped convert broad digital-transformation ambitions into practical capability gaps, prioritised investment actions, and clearer governance responsibilities. The estimated benefit reflects avoided misdirected analytics spend, improved portfolio prioritisation, and better conversion of analytics investments into operational value.
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