AssetFuture’s Asset Intelligence Services delivers tailored, practical solutions for organisations seeking to unlock real value from their asset data. Through a modular suite of data, modelling, and analytical services; combining deep expertise in the Asset Management space empowering companies in decision making and focusing on long term strategic growth.
Beyond the traditional SaaS platform, AssetFuture offers an extensive list of services to all our customers:
Actionable Information Request:
Rapid, custom data extracts and scenario modelling translate requirements into useful analysis and clear recommendations.
Responsive service levels for customer, internal, external, and ministerial requests ensure agility and reliability.
Flexible solutions that fit routine feedback or formal, audit-ready reporting as needed.
Precision Data Services:
Optimise the quality and structure of asset data through professional cleansing, validation, and setup.
Achieve seamless data integration with expert interfacing documentation for technology ecosystems of any scale.
Uncover actionable insights from health checks and extrapolation, even in challenging or incomplete datasets
Strategic Technical Papers:
Commission authoritative, compliance-driven white papers for projects like asset investment planning, maintenance optimisation, sustainability modelling, and resource allocation.
Showcase organisational leadership and fulfil demanding reporting standards with expert analysis and documentation.
Custom Asset Modelling:
Model creation and customisation services support advanced asset planning, operational refinement, and scenario generation, all matched to client requirements and existing frameworks.
Leverage proven methodologies for both low-touch and high-complexity portfolios.
AssetFuture Asset Intelligence Services Catalogue
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Data Setup
Configures customer data for ingestion into the AssetFuture Platform, including area hierarchy, model import, and item templates.
Complexity: Portfolio size, data quality, quality of floor plans.
Includes: Floor plan tabulation.
Excludes: Custom reference sets, special configuration.
Data Cleansing
Data management to improve quality: fixes inconsistencies, fills data gaps, troubleshooting.
Complexity: Volume of data and systematic nature of issues.
Includes: 1 follow-up query.
Excludes: Custom reference sets, model creation.
Data Validation
Quality checks to ensure data is accurate, complete, consistent, reliable, and timely for reporting and scenario generation.
Complexity: Depends on data source and team experience.
Includes: 2 follow-ups on data gaps and re-validation.
Excludes: Extensive backfilling, synthetic data for data gaps.
Data Health Check
Exploratory analysis for data quality and compatibility, with recommendations for improvement.
Complexity: Depends on required formality of the response.
Includes: Peer-review.
Excludes: Formal documentation in most cases.
Dataset Ingestion
Imports external datasets into the AssetFuture Platform, recommended alongside documentation.
Complexity: Dataset row/column count, data quality, number of unique items.
Includes: Model mapping, simple data assumptions documentation, 2 revisions after ingestion.
Excludes: Data validation, data cleansing.
Data Extrapolation
Populates data gaps within a customer’s database using existing data and documented assumptions.
Complexity: Size/complexity of data gaps, number of area types, quality assumptions.
Includes: Documentation, 1 peer review round, inclusion in assumptions documentation if tied to data ingestion.
Excludes: Enhancing extrapolated data quality.
Data Governance Framework
Establishes best-practice documentation for governing asset data, typically 30+ pages.
Complexity: Organisation size, technology environment, existing processes.
Includes: 1 major, 2 minor revisions.
Excludes: Execution of recommendations.
Data Interfacing Documentation
Documentation defining how AssetFuture Platform data structure interfaces with client systems.
Complexity: Number of systems, degree of customisation and stakeholders.
Includes: 2 customer workshops, 2 document revisions.
Excludes: Process execution, data transformations.
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Custom Data Extract and Analysis
Custom spreadsheet extracts with high-level insights via email, based on customer requirements.
Custom Scenario Modelling
Creation of custom scenarios using controls within AssetFuture Platform.
Customer Internal/External/Third-Party Request for Information
Analysis with written insights and data, tailored for auditors or internal/external departments.
Ministerial Request for Information
Immediate, priority response to custom data extract requests.
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Model Creation
Crafts new models using provided customer data or existing library models, includes research for missing inputs.
Complexity: Availability of customer information, uniqueness, number of models.
Includes: Basic research.
Excludes: Documentation of inputs, creation of full custom model library.
Model Customisation
Adjustments to existing models to fit customer needs (tasks, frequencies, inputs).
Complexity: Structured customer info, customisation scope, model quantity.
Includes: 2 minor revisions.
Excludes: Training/workshops on customisation options.
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Generic Technical Paper: Formal, audit-ready white papers (5–20 pages), deeper than platform outputs.
Includes: 1 presentation, 1 major revision, 2 minor revisions in 2 weeks.
Asset Investment Planning: Models and recommendations for investment planning and funding options.
Includes: Scenario/sensitivity analysis, extended feedback period.
Resource Optimisation Plan: Optimisation recommendations based on external EAMS data.
Complexity: Data quality, trades to be optimised.
Sustainability Modelling: NGER reporting compliance, scope 1 and 2 emissions baseline.
Complexity: Number of asset types analysed.
Maintenance Optimisation: Recommendations to improve maintenance reliability and efficiency using EAMS data.
Complexity: Data quality.
All technical paper types include relevant assumptions from the general technical paper provision, with exclusions applying to iterations beyond the support period.
Additional Notes:
Service levels are determined by low, medium, and high complexity, defined by data volume, quality, and custom requirements.
Documentation and revisions are included as specified, with exclusions for deep configuration, integration, or ongoing iterations outside agreed scope.
Designed for supplementing recurring services or SaaS contracts, subject to further agreement and clarification of project scope.