ŚWIĘTOKRZYSKIE, POLAND – 05/01/2026 – (SeaPRwire) – As fast-moving consumer goods companies navigate an increasingly competitive retail landscape, category management is evolving into a highly data-driven and strategic discipline. With shelf space finite and decision cycles shrinking, artificial intelligence is emerging as a critical enabler for category managers seeking clarity, speed, and measurable impact.
Lorenz, the snack manufacturer behind brands such as Crunchips, Wiejskie Ziemniaczki, and Monster Munch, offers a real-world example of how AI can reshape everyday category management. According to Sandra Lemańska, Category Manager at Lorenz, the role has expanded well beyond shelf planning to encompass strategic decision-making grounded in advanced data analysis.
Modern category management requires the continuous monitoring of key performance indicators, including distribution, sales rotation, margins, and market share. At the same time, managers must account for promotional calendars, marketing initiatives, and cross-functional collaboration. In a fragmented retail environment spanning discount outlets, convenience stores, and hypermarkets, building the right assortment for each channel has become increasingly complex.
Recognizing the limitations of traditional business intelligence tools, Lorenz partnered with AI and data analytics firm DS STREAM to elevate its analytical capabilities. The collaboration marked a shift from retrospective reporting to predictive and prescriptive insights designed to support faster, more confident decision-making.
Through the partnership, DS STREAM helped Lorenz establish a centralized data ecosystem by building a scalable Data Lake that integrated information from sales, marketing, supply chain, and external market sources. On top of this foundation, advanced analytical models and machine learning solutions were introduced to support demand forecasting, assortment optimization, and promotional effectiveness analysis. Custom dashboards provided teams with real-time visibility into critical metrics, enabling a more agile response to market dynamics.
The transformation highlighted a key inflection point for AI adoption: when organizations are rich in data but constrained by time and analytical capacity. As Lemańska noted, once foundational reporting was in place, the demand quickly shifted toward deeper insights and forward-looking recommendations that traditional tools could not deliver.
Importantly, the introduction of AI did not replace category managers—it redefined their work. Routine tasks such as manual data collection and report preparation were automated, freeing time for strategic analysis, partner collaboration, and scenario planning. AI-driven insights also enabled faster responses to retailers, more precise promotional strategies, and a stronger understanding of consumer behavior.
DS STREAM’s FMCG expertise played a critical role in the success of the initiative. Since 2017, the company has built a strong presence in AI and data analytics, supporting global CPG organizations with machine learning platforms, MLOps implementations, and modern data architectures. Its technology-agnostic, partnership-oriented approach ensured that solutions were not only advanced, but also practical and aligned with the daily workflows of category managers.
The Lorenz case demonstrates that AI adoption in category management is an evolutionary process rather than a sudden disruption. By starting with solid data foundations, focusing on specific business challenges, and preparing teams for a shift toward more strategic roles, FMCG companies can turn AI into a powerful support system rather than a source of uncertainty.
As competition intensifies and data volumes continue to grow, the collaboration between Lorenz and DS STREAM illustrates how combining domain expertise with advanced analytics can create sustainable competitive advantage—helping category managers move faster, think deeper, and make smarter decisions in an increasingly complex marketplace.