Gen AI Pulse | Augmented people Aug 16, 2024 Get into the PULSE of Gen AI with real-world data, actionable insights, and the transformative impact of this ongoing revolution. This is our quarterly paper written by CI&T specialists who are implementing AI solutions at the forefront with our clients. Learn more
2021 - The Year of the Digital Revolution Apr 16, 2021 Recently, Bob Wolheim, our CSO, interviewed Sérgio Vezza, Vice President of BEES, the startup behind Ambev and AB InBev, owners of brands like Budweiser and Stella Artois. Learn more
Business Impact: The Beginning of Transformation Apr 23, 2019 Named as the biggest challenge by C-Levels today, achieving success in the process of transforming companies into digital has a secret: the generation of business results from the beginning. Learn more
Five years in five months: the leap from traditional to digital operations Aug 07, 2020 With a 45-year history in Brazil, the Carrefour chain has built a solid operation that today has 72,000 employees and 498 stores distributed in 26 states. Learn more
Solving CPG and Retailer Demand Forecasting Dilemmas Download The retailer-supplier relationship isn’t arranged in the way most conducive to confident demand forecasting. In this new report CI&T examines the demand forecasting relationship between retailers and suppliers. The report highlights pain points and opportunities for both parties, revealing a misalignment of data strategies causing ineffective forecasting. DOWNLOAD THE FULL REPORT Key findings from the report include: Suppliers’ highest ranking challenge related to forecasting demand was visibility and access to data. Retailers’ highest ranking challenge related to demand forecasting was scaling the data platformSuppliers reported they were most likely to break demand forecasting down by geography, while retailers were most likely to report breaking down demand forecasting by channel The majority of suppliers reported looking at sales data from the same month over years prior as their predictive approach, while the majority of retailers reported referencing the previous month’s sales to predict the following monthBoth suppliers and retailers overwhelmingly reported that consumer-level data (gender, age, household size) is the most likely type of data leveraged for demand forecasting