Servitization: Turning Data into Customer Value
.jpg?v=638641913410302002 "Immagini sito (5)")
Goglio is a leading provider of packaging equipment and flexible packaging solutions. The company designs, develops and manufactures complete packaging systems.
It has anticipated market needs through innovative solutions since its inception in 1850.
Adopting a business model like Servitization enables data-driven user economy. Through the collection and analysis of production, operational, and process data, the company delivers smart services that improve maintenance and boost efficiency.
This new ecosystem allows clients to transform machine-generated data into valuable business insights, creating value through process optimization, increased efficiency, and reduced unforeseen events.
We are working on the English version.
IoT became essential for Goglio in 2014 when a customer requested a five-year efficiency guarantee for its packaging lines. The initial connection was established via VPN, but Goglio soon developed its own IoT platform - Goglio MIND - to provide the same services to all customers.
Our collaboration began in 2017 with the goal of optimizing system performance. By leveraging extensive process expertise, we expanded the system, improving its performance and connecting more than 100 machines worldwide.
The Servitization model benefits both machine manufacturers and technology users.
Manufacturers gain valuable insights into machine behavior after delivery, allowing them to refine future designs and provide more targeted service offerings. At the same time, customers can optimize maintenance strategies to maximize machine efficiency.
Over time, machine performance continues to improve. Rather than replacing equipment, customers can follow data-driven recommendations to maintain elevated levels of operational efficiency.
We are working on the English version.
Servitization provides precise cost transparency by linking service contract costs directly to actual production volumes, moving beyond traditional preventive maintenance.
With Condition Monitoring, connected machines automatically trigger interventions only when necessary, ensuring components are replaced only when they have reached the end of their lifecycle.
This selective, precision-based approach reduces operating costs by 10-20% compared to conventional maintenance models.
We are working on the English version.
We are working on the English version.
While machines collect vast amounts of raw data that requires Machine Learning or AI processing to become actionable insights, human expertise remains essential in interpreting that data and making strategic decisions.
Servitization places humans at the heart of the business, empowering them to refine their skills over time and drive continuous, long-term improvement.