Discover our brand new 2024
CPG Data & AI human capital report

  • Top 25 ranking of global leading CPG companies
  • Weight of Data & AI workforce within the industry
  • Zoom on French CPG leading companies

Report co-written with Alix Partners based on Darwin X Data & AI Index.               
See below for more details.

CPG Index

Data & AI workforce Index for CPG Leaders

Our Data & AI workforce index for CPG leaders measures the relative strength of Data & AI talent pools for 65 consumer packaged goods companies. The index follows a 100-points rating scale.

As of December 2023

65

Companies across Beauty, Beverage, Clothing, Food, Household, Luxury and Tabacco

3.3 M

Employees representing the total combined workforce of these companies

0.5 %

Share of all Data & AI talent pools among this total workforce

70

Companies across Beverage, Beauty, Clothing & Accessories, Food, Luxury…

0.5 %

Share of Data & AI talent pools within total worforce

3.3 M

Total workforce of the 70 companies

TALENT POOLS

Talents pools scanned

We are scanning talent pools across 4 categories :

DATA ANALYTICS

These jobs equip a company with the ability to make sense of data through performance dashboards, data visualisation and ad-hoc analysis to produce new insights and improve decision making across all business functions

DATA ENGINEERING

These jobs equip a company with the ability to build and operate a proper data infrastructure: feeding from internal systems and external data sources, refining raw data into quality data sets, storing and distributing clean “data products” to data consumers, i.e. data analysts, data scientists, AI/ML engineers

DATA SCIENCE

These jobs equip a company with the ability to produce new insights from data science, i.e. advanced analytics leveraging complex statistics and mathematics

ARTIFICIAL INTELLIGENCE

These jobs equip a company with the ability to build and operate Artificial Intelligence solutions. Fields of application include AI perception (e.g. Computer Vision, Speech Recognition), Language (e.g. Natural Language Processing, Large Language Models), Learning (e.g. Supervised, Reinforcement, Deep Learning)

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