There is a silent form of knowledge that takes shape in every winery, and it cannot be found in any enology or agronomy textbook. It builds over time, through observation, touch, and taste — an experiential, qualitative understanding that embodies the style, vision, and identity of those who have tended that vineyard for decades. In scientific literature, it is called tacit knowledge: it is not codified, it does not travel through documents or procedures, it exists in the minds of those who carry it.
The concept was formalised by the economist and philosopher Michael Polanyi in the 1960s with a phrase that speaks for itself: we can know more than we can tell. Decades later, researchers Ikujiro Nonaka and Hirotaka Takeuchi demonstrated, through analysis of companies such as Honda and Canon, that converting tacit knowledge into explicit, shareable knowledge is one of the primary drivers of competitive advantage. It holds true in industry. It holds even more true in wine.
We can know more than we can tell.
Michael Polanyi
Beyond the number: all the data a winery produces without knowing it
When people talk about data, the first instinct is usually to think of weather stations, spreadsheets, sensors, numbers, or analytical parameters. These are numerical data points, and they are fundamental — they carry information with them. But they are not the only kind.
Every observation in the vineyard is a data point. Every winemaker annotation is a data point. A photograph taken of a suspicious leaf, the decision to halt a maceration, the organoleptic evaluation of a wine before and after ageing: all data, even when non-numerical, even when not required by any fiscal register. Each data point is a piece of the puzzle that allows us to see the complete picture of a wine — a picture that forms gradually, step by step, observation by observation, from pruning to bottling. Knowing this picture becomes a strategic reference point, making it possible to compare decisions and outcomes across different vintages. Those data points, numerical and qualitative alike, are the only trace left to understand how a particular result was achieved.
Why a single data point is never enough
An isolated data point communicates very little on its own. A single observation, equally, remains isolated information. Value only emerges when the two are combined and meaning is extracted.
The decision of when to harvest is never made on sugar content alone — phenolic maturity, organic acid levels, and aromatic maturity all need to be taken into account. Assessing these qualitative aspects leads to a technical observation and decision that in turn depends on the environmental factors that determined the sugar, polyphenol, acid, and aroma content of the grape. The same mechanism applies during the maceration of red wines. Polyphenolic extraction is analytically measurable. But the decision of when to halt maceration also depends on the tactile quality of the tannins, evaluated through tasting.
Agro-climatic data without the agronomic or enological interpretation remains a sterile number. An observation without the data remains an isolated impression, difficult to compare. The encounter between the two is what makes it possible to understand the cause-and-effect relationship and extract actionable knowledge.
Connecting the dots
For qualitative information to meet numerical data, they must first share the same space and the same moment. An observation written in a paper notebook, without coordinates and without a precise timestamp linked to a system, remains an island. Using a system capable of ensuring that every data point and piece of information is collected and archived systematically — across every parcel, every batch of wine, every vintage — represents the minimum necessary condition for data correlation.
Returning to where we started: the wine sector is the perfect embodiment of tacit knowledge. Great winemakers define the style of a wine, inspire trends, and leave a lasting mark. The value they generate cannot remain locked inside a single individual. Wineries must be able to extract and understand the knowledge that has, until now, remained silent within their most experienced people.
