5 questions to...
Maurizio Pecori
Interview with the Head of Industry, Hospitality & Services of Engineering.
Maurizio Pecori boasts over thirty years of experience in the ICT sector, both in technical and commercial areas.
He joined the Engineering Group in 1996 and, after a few years in the Public Administration department, moved to the Industry and Services Department in 2000, where he holds roles of increasing responsibility.
In particular, he actively participates in the integration process of the acquisitions of Atos Origin and T-Systems, concretely fostering collaboration between colleagues, contributing to the development of customers and laying the foundations of the current Direction where we operate internationally.
AI can pervasively and radically transform manufacturing operations. Indeed, the intelligent use of data coming in from the factory, through IoT and machine learning solutions, enables Responsible AI solutions to optimize productivity by streamlining processes and improve efficiency by reducing costs.
From equipment maintenance to monitoring and optimizing production processes to controlling the supply chain, there are many ways in which a Manufacturing company can benefit from such solutions while adhering to the ethical principles guiding Responsible AI.
Additionally, there are complex scenarios where AI, combined with other solutions such as Digital Twin, Simulation, and Data Analytics, helps managers make critical business decisions when faced with various risk scenarios. This is known as Decision Science, which undoubtedly meets the need for transparency characteristic of the responsible use of Artificial Intelligence.
Engineering has always played an active role in making innovation responsible, and this applies to Artificial Intelligence as well. We collaborate with EU institutions to promote the responsible and ethical development of AI.
In the manufacturing sector, a company aiming for responsible production can also rely on other technologies alongside AI, such as the cloud, which offers flexibility and scalability, and data analytics, which is useful for identifying inefficiencies and developing strategies to optimize resources.
There is no doubt, then, that the words innovation and accountability go hand in hand.
Due in part to the large and rapid deployment of AI solutions, cybersecurity is an important trend in the manufacturing market for 2025: cyber attacks on companies are also coming through what criminals see as new opportunities, and manufacturing company managers are aware of this.
It should also be taken into account that the increasing convergence of OT and IT environments, with the latter being much more at risk, exposes industrial systems - plant, factory machinery and control systems, production lines -, to increasingly dangerous, sophisticated and targeted attacks.
Indeed, it should be kept in mind that the goals of cyber criminals are multiple: to damage systems, disrupt production or steal sensitive data. Inevitable, then, that even in this sector it is clear to everyone that preventive and reactive cybersecurity must be a priority, and must be so in every business environment.
Where to start? From a compliance gap assessment against specific cyber risk management standards and the identification of a risk mitigation strategy.
Just these days, we are launching a useful survey in this regard, which is the result of our experience in security management of manufacturing companies; it will certainly give us valuable insights into how to improve our ability to support customers and prospects in this area that is so crucial today.
Looking at the importance today of ESG issues also for the B2B world of Manufacturing, significant reduction of consumption in plants, and more generally energy management and energy saving, are certainly important, and, in times of energy crisis, they also mean a significant reduction in operating costs.
The first step to take here, too, is an assessment, an energy audit with consumption analysis, to understand the state of the art by prioritizing action.
Once one's situation is clear, in addition to a modernization or readiness of the infrastructure to be monitored that improves efficiency, investments in automation, through smart technologies and predictive maintenance monitoring platforms, are key.
Engineering brings relevant expertise and effective energy management solutions to the table, solutions that make business processes more energy efficient, maximize the use of company space, and facilitate the intelligent use of resources, thus stimulating proactive energy savings.
The centrality of the supply chain has been in the public eye for a number of years now, given the exceptional events that have occurred and those that are looming with the new international scenario.
It is no coincidence that Engineering has for a couple of years now started a specific Observatory on the Supply Chain and has for even longer adhered to Bisc3, an initiative for discussion among experts in the field that is intended to be an opportunity for stimulation and comparison among professionals who have to deal with such a crucial issue.
Among the actions that companies need to take not only to react to the market situation, but also to introduce an element of competitive advantage, we see initiatives such as improving strategic and operational planning capacity, increasing visibility on supply and distribution chains, seeking efficiency in their operations, as well as focusing on the sustainability of their supply chains.
Finally, to avoid being caught off guard by the sudden changes in international scenarios, it is crucial to prepare, including through Decision Science initiatives and solutions (which we mentioned earlier). Transformation projects and investments in Supply Chain digitization and innovation have already proven to be a differentiator by those who have embarked on this path.
To best respond to our clients' needs in this area, for years in Engineering there has been a consulting team specifically dedicated to Supply Chain, made up of experts in the subject (from simulation, forecasting, and planning to scheduling and logistics) and which has developed a maturity model that is very useful for understanding the situation from which a company starts, highlighting critical issues and defining a strategy for improving intervention.
The centrality of the tourism experience and its personalization are key elements that we see every day as more and more sought after by the realities of the sector: therefore, everything that has to do with the omnichannel customer experience is at the center of the strategies of those who operate in the sector and must be from the booking phase of the tourism experience.
In fact, it should be kept in mind that the tourist has evolved technologically and expects a smart experience from the tour operator, who therefore needs to invest in smart platforms, at this time highly devoted to the use of AI, so as to offer a customer journey that lives up to expectations, regardless of the touch point used by the user to interact.
It should also never be forgotten, but in an industry like this it is vital, the centrality of data, precisely with a view to personalizing the offer and improving efficiency.
This applies to new and loyal customers alike: for example, in our experience with major operators in the cruise market, we have learned how complex data management is for the hospitality sector, which includes entertainment and shipping issues, thus requiring a holistic approach in its registration and management. In this sense, we have gained enough experience to be a guide for operators in this market.
So everything that revolves around the analysis of such data is central, with AI coming in strongly here as well, to respond in an increasingly timely way to guest requests, from room preferences, to itinerary suggestions. Again, the focus on sustainability cannot be missed, which is why automation and technological innovation are crucial for managers to reduce waste and respond to new guest sensitivities.
Decision Science helps managers make business-critical decisions and meets the need for transparency typical of the responsible use of Artificial Intelligence.
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