The Data Challenge in the Food Industry: A Real Opportunity for Innovation
- Futuro Imperfecto
- Jul 16
- 2 min read
Today I want to share a recurring issue I often encounter when working with clients in the food industry: the lack of structured data, disorganized information, and inconsistent records. It’s a much more common situation than you might think — across companies of all sizes and stages of development.
When we begin a new project, we frequently come across data that is:
- Scattered across multiple sources
- Lacking any consistent format
- And in some cases, simply nonexistent
Some of the most frequent issues include:
- Incomplete information: essential fields have not been filled out.
- Duplicate records: the same data appears multiple times.
- Diverse and non-standardized formats: physical documents, unstructured spreadsheets, handwritten notes — making data consolidation a real challenge.
- Lack of traceability: it’s difficult to reconstruct the history and context of the data — who recorded it, when, and under what conditions.
This isn’t a barrier — it’s an opportunity
While this situation may initially seem like an obstacle to implementing Artificial Intelligence (AI) or Machine Learning (ML) solutions, in reality, it presents a powerful opportunity for transformation.
With proper data management, these technologies can make a real difference: predicting outcomes, optimizing formulations, reducing trial and error, and accelerating product development.
Where to begin? ... With an ELN
My first recommendation is simple: implement an ELN (Electronic Laboratory Notebook).
Whether it’s a solution like the one we’re building at Elytra Biomaterials, or another available tool, the key is to adopt a system that allows you to standardize and digitize all experiments. Making the hashtag#ELN the official and only channel for data entry is essential to move beyond manual methods.
It may seem like extra effort at first, but the long-term benefits far outweigh the initial investment.
What are the tangible benefits for companies and R&D teams?
- More efficient and traceable processes.
- Less time spent searching for information.
- Faster, more informed decision-making.
- Better focus on core tasks.
- No more lost or fragmented data.
- Lower barriers to implementing AI-powered optimization.
- And most importantly, happier researchers — with organized, secure, and accessible data.
In short: if you’re thinking about innovating, start by organizing and digitizing your data. It’s not just recommended — it’s essential. The future of innovation in the food industry through R&D depends on it.
What about you?
What tools do you rely on to digitize and manage your R&D data — are they truly helping you move faster? And what challenges are you still facing?
Have a nice day.
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