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Diagnostic Offers

Find the highest-value starting point for governed AI and analytics

Before launching a platform implementation, StratLytics helps enterprise teams assess data readiness, governance gaps, model performance risks, and business-value opportunities through focused two-week diagnostics.

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Why diagnostics first?

Most enterprise AI and analytics initiatives do not fail because of algorithms. They fail because of unclear business ownership, fragmented data, weak governance, missing monitoring, and poor integration into operational workflows. StratLytics diagnostics are designed to identify these issues early and turn them into a practical implementation roadmap.

Financial Services

Credit Model Governance Assessment

Best for

Banks, credit unions, fintech lenders, consumer lenders, SMB lenders

Typical buyers

CRO, Head of Credit Risk, Model Risk Manager, Chief Data Officer, Head of Analytics

What we review
  • Model inventory and ownership
  • Monitoring coverage
  • Validation and documentation workflows
  • Regulatory and audit readiness
  • Model performance and drift indicators
  • Evidence and issue-management processes
Outputs
  • Model governance maturity score
  • Key gaps and risk areas
  • Monitoring and validation roadmap
  • Recommended SLERA implementation path
Book Credit Governance Assessment
Utilities & Energy

Utility Forecasting Readiness Assessment

Best for

Electric utilities, distribution companies, smart-metering programmes, grid analytics teams

Typical buyers

CTO, Grid Operations Head, Demand Forecasting Lead, Smart Metering Program Lead, Data/Analytics Head

What we review
  • AMI and smart-meter data availability
  • Historical load and weather data
  • Forecasting granularity and accuracy needs
  • Demand-response use cases
  • Data quality and telemetry gaps
  • Integration with operational workflows
Outputs
  • Forecasting readiness score
  • Data and integration gap analysis
  • Demand-response analytics opportunity map
  • Recommended SLIQ implementation path
Book Utility Forecasting Assessment
Supply Chain

Supply Chain Forecasting Diagnostic

Best for

Manufacturers, distributors, retail/CPG businesses, industrial supply chains

Typical buyers

COO, Supply Chain Head, Planning Head, Inventory Optimisation Lead, Data/Analytics Head

What we review
  • Demand history and SKU behaviour
  • Forecast accuracy by product/location
  • Inventory and service-level leakage
  • Replenishment rules and planning cycles
  • Supplier/network risk indicators
  • Data availability across ERP, WMS, TMS, and planning systems
Outputs
  • Forecasting maturity score
  • SKU segmentation and opportunity areas
  • Inventory/service-level improvement hypotheses
  • Recommended SLICE implementation path
Book Supply Chain Diagnostic
Process

How the diagnostic works

01
Discovery and scope alignment

Clarify business problem, decision workflow, data landscape, and success metrics.

02
Data and workflow review

Review available data, reports, models, governance artefacts, and operational processes.

03
Gap and opportunity analysis

Identify value leakage, data gaps, governance gaps, and practical implementation priorities.

04
Roadmap and executive readout

Deliver a concise findings report with prioritised next steps, platform fit, and implementation roadmap.

Deliverables

What clients receive

  • Executive summary
  • Data-readiness assessment
  • Governance and workflow gap analysis
  • Opportunity sizing hypotheses
  • Platform-fit recommendation
  • 30/60/90-day implementation roadmap

Start with the right problem before investing in the platform

Book a Diagnostic Call