Analytics Maturity Self-Assessment (Lean Audit)

{ "Title": "Analytics Maturity Self-Assessment (Lean Audit)", "IntroductionHtml": "

Welcome

This lean audit helps teams quickly surface the highest-impact gaps in analytics maturity so you can prioritize improvements that reduce risk and accelerate value. It collects a scored rating and brief evidence for each dimension, stores your responses, and produces a concise one-page summary you can share with stakeholders.

How to use this form

For each dimension, choose the score that best matches your current state and paste or describe a short piece of evidence (systems, reports, examples, people, or metrics) that supports the score. Scores are on a 0–4 maturity scale (definitions below). Answer honestly — the assessment is most useful when it highlights meaningful constraints, not to make things look perfect.

Scoring rubric

• 0 — None: No capability, inconsistent or absent practices.
• 1 — Ad hoc: Occasional activity, individual heroic effort, limited repeatability.
• 2 — Repeatable: Basic processes and tooling exist; results are inconsistent across teams.
• 3 — Defined: Clear ownership, standardized processes, reliable data and tooling across most use cases.
• 4 — Optimized: Proactive, automated pipelines, governed metadata, integrated decision workflows, continuous improvement and measurement.

Outcome

After you submit, the assessment saves structured responses. Use the saved data to create a heatmap, export a one-page leadership summary, or generate prioritized next steps. (See Capability Notes for automated visualization and export improvements.)

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Use the platform Export function or the Analytics Maturity report to create a one-page summary for leadership.", "DataType": "AnalyticsMaturityAssessment", "SchemaVersion": "1.0", "Fields": [ { "Key": "organization_name", "FieldType": "text", "Label": "Organization / Team", "HelpText": "Name of the business unit, site, or team being assessed.", "Required": true }, { "Key": "assessor_name", "FieldType": "text", "Label": "Assessor name", "HelpText": "Person completing the assessment.", "Required": true }, { "Key": "assessment_date", "FieldType": "text", "Label": "Date (YYYY-MM-DD)", "HelpText": "Date of assessment in YYYY-MM-DD format.", "Required": true }, { "Key": "instrumentation_score", "FieldType": "scale", "Label": "Instrumentation & Data Capture — score", "HelpText": "Quality and coverage of measurement systems, sensorization, logging, event tracking. 0–4 where 4 = complete, reliable instrumentation driving decisions.", "Required": true }, { "Key": "instrumentation_evidence", "FieldType": "textarea", "Label": "Evidence: Instrumentation", "HelpText": "List key sources, example dashboards or logs, or a short note about gaps (e.g., 'only 2 lines instrumented; no timestamp sync').", "Required": false }, { "Key": "pipelines_score", "FieldType": "scale", "Label": "Data Pipelines & Processing — score", "HelpText": "Reliability, repeatability, and observability of ETL/ELT, streaming, and batch pipelines.", "Required": true }, { "Key": "pipelines_evidence", "FieldType": "textarea", "Label": "Evidence: Pipelines", "HelpText": "Examples of successful or failing pipelines, SLAs, failure rate, or monitoring alerts.", "Required": false }, { "Key": "catalogs_score", "FieldType": "scale", "Label": "Catalogs, Metadata & Discovery — score", "HelpText": "Presence of data catalog, lineage, clear dataset definitions, and discoverability for analysts and users.", "Required": true }, { "Key": "catalogs_evidence", "FieldType": "textarea", "Label": "Evidence: Catalogs & Metadata", "HelpText": "Link to catalog, examples of dataset documentation, or notes about missing/unclear datasets.", "Required": false }, { "Key": "governance_score", "FieldType": "scale", "Label": "Data Governance & Ownership — score", "HelpText": "Defined ownership, policies, access controls, data quality rules, and stewardship practices.", "Required": true }, { "Key": "governance_evidence", "FieldType": "textarea", "Label": "Evidence: Governance", "HelpText": "Examples of owners, policies, quality dashboards, or unresolved access issues.", "Required": false }, { "Key": "models_score", "FieldType": "scale", "Label": "Models & Advanced Analytics — score", "HelpText": "Use of statistical models, ML pipelines, model governance, and productionization of predictions.", "Required": true }, { "Key": "models_evidence", "FieldType": "textarea", "Label": "Evidence: Models", "HelpText": "List models in production, model ownership, validation practices, or gaps such as 'no model monitoring'.", "Required": false }, { "Key": "embedding_score", "FieldType": "scale", "Label": "Embedding Insights into Workflows — score", "HelpText": "How well analytics and models are integrated into operational or decision workflows (alerts, actions, automations).", "Required": true }, { "Key": "embedding_evidence", "FieldType": "textarea", "Label": "Evidence: Embedding", "HelpText": "Examples of alerts, decision rules, or teams that routinely use analytics outputs.", "Required": false }, { "Key": "culture_score", "FieldType": "scale", "Label": "Data Culture & Skills — score", "HelpText": "Data literacy, training, cross-functional collaboration, and leadership support for data-driven decisions.", "Required": true }, { "Key": "culture_evidence", "FieldType": "textarea", "Label": "Evidence: Culture & Skills", "HelpText": "Notes on training programs, examples of decisions using data, or barriers like 'analytics siloed in central team'.", "Required": false }, { "Key": "measurement_score", "FieldType": "scale", "Label": "Measurement & KPIs — score", "HelpText": "Quality and alignment of KPIs, review cadence, and how performance measurement drives improvement.", "Required": true }, { "Key": "measurement_evidence", "FieldType": "textarea", "Label": "Evidence: Measurement", "HelpText": "Link or list of core KPIs, dashboards used in reviews, or missing metrics that matter.", "Required": false }, { "Key": "overall_priority", "FieldType": "select", "Label": "Overall priority for improvement", "HelpText": "Choose how urgent it is for this team to invest in analytics maturity.", "Required": true, "Options": [ { "Value": "high", "Label": "High" }, { "Value": "medium", "Label": "Medium" }, { "Value": "low", "Label": "Low" } ] }, { "Key": "top_actions", "FieldType": "textarea", "Label": "Top 3 suggested next steps (brief)", "HelpText": "Based on the lowest-scoring dimensions, list up to three concrete next steps the team could take. Examples: 'Fix timestamp sync across sensors', 'Establish dataset owner', 'Add pipeline monitoring and retries'.", "Required": false }, { "Key": "notes", "FieldType": "textarea", "Label": "Additional notes", "HelpText": "Context, blockers, or links to supporting documents.", "Required": false } ] }