Clearly Blue collaborated with our Data Analytics partner Learning Tree Antz Labs to build a Data Science Maturity Engine – a research-based diagnostic tool to assess the competency of a modern-day enterprise in terms of its Data Analytics initiatives, its readiness to adopt analytics and the Data Analytics talent maturity of its employees.

The assessment engine, built using industry-standard frameworks and models, comprised two frameworks: the Analytics Enterprise Process Maturity Model (AEPMM) and the Analytics Talent Process Maturity Model (ATPMM).

The engine had the capability to:

• Profile the respondents based on their industry vertical, size, and revenue.
• Generate a score indicating the level of maturity on a 5-point scale for each model and all dimensions individually.
• Benchmark with respect to the industry segment of the enterprise based on revenue and size.
• Provide a synthesized comprehensive score of both models. This helps enterprises evaluate the current stage of maturity and get an insight into the areas for improvement.

The AEPMM measured the enterprise’s competency in terms of its analytics initiatives and its readiness to adopt Data Analytics. This model assessed the analytics maturity of the enterprise by asking 25 questions across five dimensions – Organisation, Infrastructure, Data Management, Analytics, and Governance.

The model defined five stages of maturity and included the characteristics of a typical enterprise in every stage of maturity.

The ATPMM was a people-focused model that evaluated human resource talent vis-à-vis the Data Analytics capabilities of B2B enterprises. This model assessed talent maturity by asking 25 questions across five dimensions – Talent Acquisition, Talent Assessment, Talent Assignment, Talent Development, and Talent Retention – and included the characteristics of a typical enterprise in every stage of maturity.

The model defined different stages of maturity of talent dimension of Analytics enterprises.

These insights helped the HR professionals and L&D leadership plan and transform the enterprise’s learning and talent management practices. The consolidated rating was benchmarked with respect to the enterprise’s industry segment based on revenue and size.