Digital & AI Readiness Methodology

Core operations (finance, sales, operations, HR) are run on documented systems rather than spreadsheets or informal processes.

Improvement: Map every core process to a single system of record and retire shadow spreadsheets.

Business data is backed up automatically, stored securely, and recoverable in a disaster scenario.

Improvement: Implement automated, encrypted, off-site backup with a tested recovery plan.

Key systems are connected or share data through integrations, APIs or a central data store.

Improvement: Prioritise integrations between CRM, finance and operations to remove manual re-entry.

User access to systems is controlled by role-based permissions and regularly reviewed.

Improvement: Introduce role-based access control and schedule quarterly access reviews.

There is a single source of truth for customer, product and financial data.

Improvement: Designate one system of record per entity and sync changes through integrations only.

Data quality rules (deduplication, validation, completeness checks) are in place and monitored.

Improvement: Add validation at the point of entry and run monthly data-quality reports.

Data ownership and accountability are assigned to named roles or owners.

Improvement: Assign a data owner for each core dataset and include data quality in their objectives.

Data privacy, consent and retention policies are documented and followed.

Improvement: Document your privacy policy, consent model and retention schedule, then train staff.

A documented set of KPIs is used to run the business and is reviewed at least monthly.

Improvement: Define a small balanced scorecard of KPIs and review them in a monthly leadership rhythm.

Management reports are produced automatically from live data rather than rebuilt manually.

Improvement: Replace manual report packs with automated dashboards refreshed from live data.

Metrics are linked to actions — underperformance triggers a known response plan.

Improvement: For each KPI define the threshold and the action taken when it is missed.

Relevant performance data is accessible to the people who need it to make decisions.

Improvement: Give frontline and functional teams self-service access to the metrics they own.

There is a documented policy for AI use, including approved tools and prohibited data inputs.

Improvement: Publish a short AI acceptable-use policy and communicate it to all staff.

Data is clean, structured and accessible enough to be used safely with AI models or analytics.

Improvement: Complete a data-readiness audit and fix the three highest-risk quality gaps.

AI outputs that affect customers, finance or compliance are reviewed by a human before use.

Improvement: Define human-in-the-loop checkpoints for any AI-assisted customer or financial decision.

Staff who use AI tools are trained on risks, hallucinations, confidentiality and verification.

Improvement: Run a short AI literacy and safety session for all users and record attendance.

A digital or data strategy is documented and reviewed at leadership or board level.

Improvement: Write a one-page digital strategy with three-year outcomes and review it annually.

Cybersecurity essentials are in place: MFA, endpoint protection, patching and incident response.

Improvement: Enforce MFA on all business systems, patch critical vulnerabilities within 14 days and document incident response.

Digital and data risks are recorded in a risk register with owners and mitigations.

Improvement: Add digital, data and AI risks to your risk register and assign owners.

There is a plan for building or buying the digital skills the business needs.

Improvement: Map current vs. required digital skills and create a 12-month training or hiring plan.