{"id":209793,"date":"2026-03-05T08:48:34","date_gmt":"2026-03-05T07:48:34","guid":{"rendered":"https:\/\/www.logisticsautomationmadrid.com\/?p=209793"},"modified":"2026-03-05T08:48:34","modified_gmt":"2026-03-05T07:48:34","slug":"the-industry-does-not-have-a-production-problem-it-has-a-synchronisation-problem","status":"publish","type":"post","link":"https:\/\/www.logisticsautomationmadrid.com\/en\/2026\/03\/05\/the-industry-does-not-have-a-production-problem-it-has-a-synchronisation-problem\/","title":{"rendered":"The industry does not have a production problem, it has a synchronisation problem."},"content":{"rendered":"\t\t
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The industry does not have a production problem, it has a synchronisation problem.<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Gabriel Ocio
Commercial Director, Supply Chain Solutions
Zucchetti Spain<\/strong><\/h6>\n

<\/p>\n

For years, the focus of the industry has been on improving production capacity: more automation, more information and greater control capability. However, many companies continue to face the same problems: delivery delays, logistics cost overruns, excess inventory or stockouts.<\/p>\n

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Paradoxically, this occurs even in organisations that have already invested in automation and operate with advanced management systems. If factories generate more information than ever before, why is it still so difficult to meet planned targets?<\/p>\n

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The answer often lies in a point that is not always obvious: the issue is not production, but synchronisation.<\/p>\n

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In many industrial companies, several \u201coperational realities\u201d coexist. The sales department commits to delivery dates, procurement sources materials based on forecasts, production organises manufacturing orders according to capacity, and the warehouse manages dispatch. Each department works correctly within its own scope, but does so with partial information.<\/p>\n

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When planning and execution do not share the same vision, an operational gap emerges. The company believes it knows what is happening, but in reality it is seeing an incomplete picture. This is when deviations arise: orders are delayed, materials do not arrive on time, shipments must be reorganised, or customers receive changes to agreed delivery dates.<\/p>\n

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Many operational incidents do not originate in the factory, but in the lack of coordination between planning and execution.<\/p>\n

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It is often assumed that a company is digitalised simply because it has connected machinery or automatically collects data from its processes. However, connecting machines does not necessarily mean managing operations better.<\/p>\n

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A parts counter shows how many units have been produced, but it does not explain whether a priority order is being fulfilled. A recorded stoppage indicates that a production line has halted, but does not clarify its real impact on planning. A speed indicator reflects instantaneous performance, but does not reveal whether production will be completed within the committed deadline.<\/p>\n

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Isolated data does not explain operational reality. Many companies operate sensor-equipped machinery that continuously generates information, yet they still lack a clear understanding of how production is progressing. They do not have full visibility of order progress, deadline compliance or, in many cases, actual production costs.<\/p>\n

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Value arises when data is contextualised within the production process: which order is being manufactured, with which operators, during which shift, with what incidents and at what performance level. Only then does data move beyond a technical record and become meaningful business information.<\/p>\n

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Digitalisation is not about having more data; it is about being able to decide with certainty what to do now.<\/p>\n

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Traditionally, many industrial decisions have been based on historical analysis. Daily reports or weekly indicators allowed companies to assess what had happened, but not necessarily to act in time. Today\u2019s production environment, however, is far more variable. Changes in demand, urgent customer requests, supplier disruptions or planning adjustments require reactions within hours.<\/p>\n

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This demands a shift from analysis to operational management.<\/p>\n

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At this point, Artificial Intelligence begins to play a significant role \u2014 not merely as a technological trend, but as a practical tool for interpreting large volumes of operational data and linking them to business planning. Its value lies not only in predicting scenarios, but in helping decide what action to take at any given moment: reschedule an order, adjust workloads, modify shifts or prioritise deliveries.<\/p>\n

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In this context, an increasingly evident need emerges: connecting business planning with real-time shop-floor execution.<\/p>\n

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To achieve this, industrial companies require more than isolated tools. It is not enough to have an enterprise management system on one side and automation or data capture solutions on the other. True operational improvement occurs when both layers operate in an integrated manner.<\/p>\n

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An industrial ERP structures the business: orders, procurement, planning, costs, inventory and delivery commitments. A Manufacturing Execution System (MES), meanwhile, provides something even more critical: real-time visibility of what is happening on the shop floor.<\/p>\n

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It enables companies to monitor the status of each production order at all times, detect deviations as soon as they occur, analyse performance, control actual timings and calculate effective production costs. It is not simply about recording what has happened, but about having the information necessary to make operational decisions at the right moment.<\/p>\n

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Without this connection, companies plan based on assumptions. With it, they plan based on facts.<\/p>\n

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Many organisations make decisions retrospectively, once an incident has already affected delivery performance or margins. The real-time visibility provided by MES systems allows action to be taken earlier: reorganising priorities, correcting deviations or adjusting resources while the order is still in progress. It is the difference between analysing what happened and managing the operation in motion.<\/p>\n

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The integration between ERP and MES transforms the way supply chains are managed. Production, warehousing and logistics shift from reacting to problems to anticipating them. Orders can be rescheduled before delays occur, workloads adjusted according to real plant capacity, or deliveries prioritised based on customer impact.<\/p>\n

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This is when Artificial Intelligence gains real meaning in daily operations. By jointly analysing business and shop-floor data, it enables deviations to be detected, planning adjustments to be proposed and available resources to be optimised.<\/p>\n

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This approach also requires a change in how digitalisation is addressed. Rather than implementing standalone solutions, industrial companies seek providers capable of supporting them across the entire process \u2014 from enterprise management to production execution and supply chain optimisation.<\/p>\n

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At Zucchetti Spain, we focus precisely on this integration, providing industrial ERP solutions, MES systems and WMS solutions connected within a single technological ecosystem. Our objective is not merely to digitalise processes, but to help companies manage their industrial operations with reliable real-time information, connecting business management with shop-floor reality.<\/p>\n

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Because in practice, industrial competitiveness no longer depends solely on producing faster, but on coordinating the entire operation. And that coordination is only possible when planning and production reality operate with the same information.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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