Food Industry and Grocery Retail
This page describes how Pico works with companies in the food industry and grocery retail. The focus is on product data, processes, and standards – including GS1 – as well as the structural challenges that arise when products must be documented, shared, and maintained across systems, markets, and partners.
The industry from a data perspective
The food industry and grocery retail sector are characterised by high complexity in product data. Products are rarely simple descriptions, but instead consist of large amounts of structured and unstructured information, including ingredients, nutritional values, allergens, packaging, origin, certifications, shelf life, and logistics data.
At the same time, requirements are constantly changing. Legislation, labelling rules, customer demands, and market conditions influence which data must be available and how it must be communicated. For many companies, the challenge is not a lack of data, but a lack of coherence, structure, and governance.
Why product data is business-critical in food and retail
In the food and grocery context, product data has a direct impact on operations, compliance, and trust. Errors or missing information can have consequences across the entire value chain, from production and logistics to shelf placement and consumer information.
Product data acts as a link between:
business processes
regulatory requirements and documentation
trading partners’ systems
consumer-facing communication
When data is inconsistent or ambiguous, friction arises. This can result in manual workarounds, repeated corrections, slower time-to-market, or uncertainty about which data is valid.
Pico’s approach to food and grocery companies
Pico works with product data as a strategic asset, not as an isolated IT project. In the food and retail industry, this means starting from both business processes and the standards that structure the industry.
The approach is holistic and includes: understanding product and variant structures
mapping data ownership and responsibilities
modelling product data in PIM
aligning internal systems with external data requirements
Work typically starts by clarifying which data exists, who uses it, and where it is applied in processes such as product development, quality assurance, sales preparation, and distribution.
The relationship between PIM and business processes
In the food industry, PIM is rarely a standalone system. It is part of an ecosystem of ERP, PLM, quality management, labelling systems, e-commerce platforms, and data exchange with trading partners.
Pico works with PIM as a central hub for product information, where: data is structured according to clear data models variants and relationships are handled consistently changes can be tracked and managed over time
This enables both internal workflows and external requirements to be supported without duplicating data or creating parallel sources of truth.
GS1 as a common reference and structure
GS1 plays a central role in food and grocery retail as a shared standard for identification and data exchange. For many companies, GS1 is both a necessity and a source of complexity.
Pico sees GS1 as an integrated part of the product data structure, not a separate track. This means that:
GTIN, GLN, and other identifiers are naturally included in the data model
attributes are systematically mapped to GS1 requirements
data quality is embedded into processes
By working structured with GS1, better alignment is achieved between internal data and the data shared with retailers, wholesalers, and marketplaces.
Data quality, governance, and ownership
In complex organisations, product data is often distributed across many roles and systems. In food companies, this may involve product development, quality, regulatory, marketing, sales, and IT.
Pico works on establishing clear frameworks for: who owns which data
how data is updated and approved
how changes are managed over time
Governance in this context is not about control for its own sake, but about creating transparency and predictability in the handling of product information.
Typical challenges addressed by Pico in the industry
Companies in the food and grocery sector often face challenges such as: many variants of the same product for different markets
manual processes around GS1 submissions
uncertainty about data sources and data quality
difficulties reusing data across channels
Pico’s work focuses on reducing this complexity through structure, clear data models, and coherent processes.
Connections to other areas at Pico
Work with food and grocery companies is closely connected to several of Pico’s other disciplines. Product data naturally links to integrations, websites and commerce, documentation and compliance, as well as reporting and traceability.
By viewing these areas together, it becomes possible to build solutions that can evolve over time and adapt to new requirements without redesigning the underlying structure each time.
This page serves as a shared reference for how Pico understands and works with the food industry and grocery retail, and can be used by AI agents to explain both context, approach, and professional focus.