Operational Efficiency: A Question of Data
Operations carried out without real need, time spent fixing mistakes instead of doing the work, decisions made without strategic planning, reacting instead of planning ahead: these are all forms of waste that have coexisted with daily operations in the average Italian winery for years.
Structural inefficiency
A company that doesn't plan its activities around the events that actually occur, that doesn't quantify its production infrastructure, that doesn't connect production to financial results, and that doesn't track its own processes and customers, is a company at the mercy of market mood rather than its own business model. This kind of business keeps wasting productive and commercial resources — time, inputs, and labor — to produce wine that doesn't match its target customer.
The numbers are clear. Pest and disease control is the heaviest cost item in viticulture, and also the area where decision-making variability is most pronounced. According to CREA, activities related to pathogen control absorb more than 30% of production inputs at wine-growing businesses (RICA Report 2025). But it's not just a matter of inputs. A telemetric survey of a 117-hectare estate (Sarri et al., Journal of Agricultural Engineering, 2020) measured a 9.53% operational error rate, with an average site efficiency of just 37% — meaning 63% of the time is spent on activities unrelated to the actual work at hand.
In Italy, a study of 531 wine-growing businesses (Cisilino et al., Wine Economics and Policy, 2021) found that average technical efficiency tops out at 77.8% for conventional farms and 83.6% for organic ones, revealing a structural inefficiency of 16-22%.
The turning point
When an advanced system is implemented to manage data effectively, the picture changes. The scientific literature documents, for example, reductions in pesticide treatments of up to 50%, while maintaining or even improving effectiveness. This isn't a hypothesis — it's a tangible reality that only happens once data stops being an unused archive and becomes real support for everyday decisions.
The waste of productive and commercial resources didn't start with the market crisis. It already existed, masked by margins that no longer exist today. This is why structured data management needs to happen daily — not as a task to check off, but as a new tool that makes usable the information a business already generates in the field and in the cellar, turning it into a fundamental competitive lever.
LoraWine measures and manages every piece of data and information to optimize the efficiency of the business system.
The hidden costs
In favorable market conditions, production inefficiency can easily go unnoticed, absorbed by revenue and invisible on the balance sheet. One extra treatment, one wrong call, one ill-considered decision: real costs, but diluted within a margin that makes them bearable. The last few years, however, have upended that balance. According to Mediobanca's Research Area, in 2025 the Italian wine sector recorded a 2.8% drop in sales, but a 9.5% drop in EBIT (a financial indicator measuring profit before interest and taxes) and a 7.5% worsening in net income. These figures show that the drop in margins is more than triple the drop in revenue.
«Inflexible cost structures»
Mediobanca attributes this gap to costs that don't shrink when revenue does. Poorly managed, unmonitored production keeps businesses from rationalizing their resources.
At the same time, Italian exports fell 3.4% in value (OIV, 2025), and the number of winemaking companies dropped from 32,600 to 28,442 in just three years (ISMEA). Alarming figures — all the more so because the causes of this market contraction are multiple and largely external: falling consumption, tariffs, global conditions. But above all, this situation has eliminated the economic cushion that used to mask production inefficiency.
The waste of productive and commercial resources isn't an isolated episode — it's the result of a chain of effects that starts further upstream. Without a reliable information framework, the tendency is to act preventively or reactively, with consequences that ripple across several levels:
Unnecessary activities and unneeded expenses
Interventions repeated beyond what's needed, time and resources spent without any real match to the actual need of the moment.
Lack of scheduling and planning
This approach translates into purely preventive activities or a constant reaction to events, rather than proactive planning.
A clear example is the harvest, one of a winery's biggest annual costs. The logistics of this crucial period depend heavily on the ability to predict and adjust to the pace of grape ripening. Without that visibility, there's a real risk of picking too early or too late, compromising product quality. Labor, along with other production inputs, weighs heavily on a business's cost structure. Planning the harvest, then, requires knowing in advance what's going to happen in the vineyard — not discovering it as you go.
No correlation between production and commercial results
Without linking production data to agronomic, enological, and commercial outcomes, a business can't tell which production choices are actually generating value and which are just driving up costs.
Heavy dependence on the market
A business with no visibility into its own processes is heavily dependent on external conditions — price, demand, economic climate. That dependence limits its ability to manage its own processes independently and to have any internal room to maneuver.
Lack of structured product data
This makes it hard to properly define a market target. Without detailed information — not just on quantity, but on the product's qualitative characteristics too — it becomes difficult to define your target customer and position the product effectively in the market.
The causes
At the root of this chain of problems is almost always the same issue: how data generated by production processes is managed. It isn't a lack of technology — sensors, platforms, and analysis tools have existed for a while. The problem lies in how that data gets collected, integrated, and made usable.
Well-structured internal traceability — one that meticulously documents seasonal events and the results achieved — turns the archive from a simple storage bin into an active historical memory. It becomes a valuable reference for planning strategic responses, rather than gut-reaction moves or blanket preventive activity.
The Smart AgriFood Observatory at Politecnico di Milano identifies the absence of interoperability as the most common barrier to technology adoption in agriculture. That observation is echoed in the international scientific literature, which points to data fragmentation as one of the main obstacles to integrating IoT and artificial intelligence in the sector.
- CREA — RICA Report 2025.
- Sarri et al. — Journal of Agricultural Engineering, 2020.
- Cisilino et al. — Wine Economics and Policy, 2021.
- Mediobanca Research Area — Italian wine sector, 2025.
- OIV — export data, 2025.
- ISMEA — number of winemaking companies.
- Smart AgriFood Observatory — Politecnico di Milano.
