Deliberately balancing technical and organizational levers, the GAME framework is designed to be both rigorous and operational, with a comprehensive evaluation of an organization.
Multiply the potential of my data
Transform your data into decisions and capabilities
Companies have never invested so much in their data. By 2024, nearly 88% of executives placed data and analytics at the top of their investment priorities (Wavestone, 2024). Yet, for most of them, this investment is not yet translating into value at scale.
The gap doesn't stem from a lack of tools or skills. The platforms are in place, the data is accumulating, dashboards are multiplying, and the first prototypes are emerging. What's missing is the connection between the business units that transform this data into decisions and capabilities.
Three areas of expertise are working with your data:
AI, which builds intelligence: prediction and automation.
Analytics, which makes the data speak and transforms it into decisions.
The data Product Owner, who manages projects and ensures their success.
Each one addresses a real need and can be used independently. Together, they multiply the value of your data.
Some figures
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The success of an AI transformation depends 70% on people and processes, 20% on technology and data, and 10% on algorithms (BCG).
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Only 39% of organizations report an impact of AI on their operating profit, most often less than 5% (McKinsey, 2025).
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5% of leading organizations have deployed generative AI in production at scale (Wavestone, 2024).
The three areas of expertise within the Data & AI practice
The three areas of expertise are not sequential steps. They are complementary skills, used together or separately depending on the organization's maturity and the nature of the project. We operate them on a time and materials basis or as a project manager, and we adapt our approach to your specific needs. Combined, they do more than simply add up: measured data feeds AI, and project management brings everything into production.
AI
Building Intelligence
AI transforms measured data into predictions and automation. Two categories, two governance models:
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Predictive ML. Scoring, forecasting, segmentation, anomaly detection: models trained on your data to anticipate and improve the reliability of your decisions. Governance = models.
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Agentic AI. Generative AI and multi-agent systems that act: co-pilots, task and workflow automation, agents in production. Governance = agents and multi-agent systems.
AI is neither a magic wand nor a threat: it is a tool that performs well in specific, well-defined, and monitored use cases.
Profiles involved: Data Scientists, ML Engineers, AI and Agentic Engineers.
Intervention model: managed services or project-based work, on defined use cases as well as on production systems.
Data Analytics
Making Data Speak
Analytics transforms raw data into actionable insights: modeling, measurement, dashboards, data products, and decision support. It makes business activity understandable and manageable, and provides the measurement foundation upon which AI relies.
Profiles involved: Data Analysts, Analytics Engineers, Analytics Managers.
Intervention model: managed services or project-based work, for one-off projects or ongoing monitoring.
Product Owner (Data Project)
Orchestrate, manage, and deliver results
The Data Product Owner maintains the roadmap, prioritizes projects based on value, aligns business and technical stakeholders, and drives quality gates. They lead projects from scoping to production and ensure timely decision-making.
Target profiles: Data Product Owners, Data Project Managers.
Work model: Time and materials or project-based assignment, depending on the project scope.
Case studies
Data Engineering & Cloud to automate the extraction of consumer data and structure the migration to a modern CRM.
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Data Engineering & Cloud to automate the extraction of consumer data and structure the migration to a modern CRM
Read a case study >
Digital transformation through process automation and UX redesign for a scalable and user-centric platform.
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