Maximo Consulting and Data Quality

SAS-AM provides specialised IBM Maximo consulting focused on data quality, configuration optimisation, and maintenance strategy alignment. We help organisations maximise the value of their Maximo investment through better data, smarter workflows, and analytics-ready asset hierarchies.

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60
%
Of Maximo implementations have data quality issues that limit analytical capability
30
%
Average improvement in maintenance planning accuracy after data quality remediation
40
%
Reduction in duplicate and orphan records achieved through systematic data quality programs

Maximise Your Maximo Investment Through Data Excellence

Our Maximo consulting services focus on the intersection of system capability and asset management practice. We ensure your Maximo configuration supports your maintenance strategies, your data quality enables meaningful analytics, and your workflows drive operational efficiency.

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we work hard to deliver incredible value to our clients.

Asset Hierarchy and Data Quality Audit

We audit Maximo asset hierarchies for completeness, consistency, and alignment with physical asset configurations. Our reviews cover parent-child relationships, location hierarchies, failure codes, and classification structures to ensure data supports both operational and analytical requirements.

Maintenance Strategy Alignment

We review and align Maximo preventive maintenance programs with RCM-based maintenance strategies. This ensures PM tasks, intervals, and job plans reflect actual asset criticality and failure modes rather than arbitrary schedules.

Reporting and Analytics Enablement

We configure Maximo reporting structures and data extraction processes to support advanced analytics. Our work ensures that the data flowing from Maximo into dashboards and predictive models is clean, consistent, and contextually meaningful.

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Analytics-Ready Data

Clean, well-structured Maximo data enables accurate reporting, meaningful analytics, and maintenance strategies that reflect actual asset performance.

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Reliable Asset Information

Accurate hierarchies and consistent data standards ensure you can trust the information in your Maximo system for operational and strategic decisions.

Analytics-Ready Data

Data quality improvements enable advanced analytics, predictive modelling, and AI applications that require clean, structured input data.

Optimised Maintenance Execution

Aligned PM programs and accurate job plans reduce wasted maintenance effort and ensure critical tasks are not missed.

Reduced System Overhead

Streamlined configurations and cleaner data reduce system administration burden and improve user adoption across maintenance teams.

Where theory meets execution

See how we’ve applied our ideas to generate generational changes within our comunity.

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FAQs

Learn more about what our clients ask us.

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FMECA and RCM Engineering

SAS-AM delivers FMECA, RCM, and reliability engineering services that optimise maintenance strategies and reduce asset failure risk. Our data-driven approach combines traditional reliability methods with AI and machine learning to extend asset life and improve operational performance across Australian industries.

Asset Management Maturity Assessment

SAS-AM delivers IAM-endorsed asset management maturity assessments aligned with ISO 55001 and GFMAM. We benchmark your organisation's practices, identify capability gaps, and provide actionable roadmaps for continuous improvement across all asset classes.

Advanced Analytics for Smarter Asset Management

AMiPU is SAS-AM’s advanced AI and Machine Learning platform, designed for offline, high-performance analytics powered by NVIDIA GPUs. It delivers predictive insights, automation, and real-time decision-making without relying on cloud connectivity, ensuring security and efficiency in asset management.

Building your best future with Maximo Consulting and Data Quality

Shaping the conversations and future of nations, states and regions, we passionately guide stewards to think-well, act-smart and create life-changing impact. One asset at a time.

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