All the initiatives we offer as part of our support approach include one or more deliverable-based workshop services, generally structured around the following plan:

• • Workshop context and objectives
  • Recap of the previous workshop
  • Specific content of the workshop
  • Appendices

Our audit approach aims to help us understand your current Data & AI environment, gain better insight into your data organisation, identify key stakeholders, and highlight potential friction points.

This approach is typically carried out in four steps:

• • Preparation
  • Investigation
  • Advisory and Validation
  • Follow-up

To support the Data and AI stakeholders in your organisation, we offer tailored training sessions adapted to various audiences (e.g. Roles and responsibilities in Data Governance for executive committees, search engine usage for end users, etc.).

This service is organised into modules defined jointly with you:

• • Preparation of training materials
  • Training delivery
  • Sharing of materials and post-training Q&A

To ensure regular follow-up and validate progress and deliverables, we offer dedicated support and facilitate governance meetings for your Data and AI initiatives. These meetings can operate at three levels: strategic, tactical, and operational.

This service typically includes the following activities:

• • Preparation and early delivery of presentation materials
  • Facilitation of the meeting
  • Update of the presentation and minutes (included in the presentation)
  • Follow-up on action items between two meetings

Depending on the nature of the assignments entrusted to us, we work on various types of deliverables. The list below is not exhaustive and provides a few examples:

Strategy and governance

• • Identification of business priorities and roadmap for data management
  • Definition of the Data function within the IS, its role, and governance
  • Definition of data quality management principles
  • Definition of the GDPR compliance strategy to adopt

Use cases

• • Development of the multi-year usage backlog (portfolio, enablers, features, use cases…)
  • Facilitation of definition and ideation workshops for Data use cases
  • Innovation sessions focused on Data use cases
  • Complexity matrix, decision matrix, and use case eligibility assessment

Data

• • Data urbanisation
  • Mapping of data sources and datasets, and cataloguing
  • Macro-models and data models
  • Data flow orientation within the Information System
  • Identification and optimisation of the data lifecycle
  • Data security and protection

Data & AI Architecture

• • Definition of guiding principles
  • Definition of the functional, logical, and physical architecture of the Information System and data platforms
  • Data IT strategy and tooling for data platforms
  • “Move to Cloud” strategies
  • Best practices for developing and deploying Data projects

Operating Model

• • Activity mapping and identification of macro-processes within the operating model
  • Mapping of Data stakeholders
  • Definition of “Data Owners” / “Data Stewards” and their roles and responsibilities
  • Organisation of governance and steering bodies (executive committees, steering committees, etc.)
  • Agile and scaled project management

Roadmap and budget

• • High-level functional estimation (use case sizing) and technical estimation (technical enablers)
  • Infrastructure needs estimation and reference charts
  • Multi-year roadmapping and action plans
  • “Smart” phasing based on project synergies and adapted to the organisation’s available resources