Before speaking about how to adopt Data Driven strategies thanks to IoT, the concept of Data Driven must be introduced. Behind the vague science fiction flavor of the expression “Data Driven” conceals a very simple concept: physical reality – and in the case of a company the machinery, structures and production processes – can be described in terms of data. Most importantly, it can be observed and modified starting from the information that are obtained by processing these inputs. In other words, a digitized representation of the components to be studied is created. The so-called “digital twin” is acted on, verifying how the insertion of new variables or the evolution of certain elements impacts on the ecosystem and on the final output.
In this way, you have the freedom to experiment, to evaluate hypotheses and also to correct in the race particularly delicate upgrade implementations, also monitoring energy consumption, with the possibility of optimizing it. Not to mention the possibility, taking advantage of the machine learning technologies, to slowly arrive at the start of real predictive maintenance procedures. Through them the applications themselves warn users of possible malfunctions or machine stoppages even before any signal occurs of criticality. Here, this is the adoption of a “Data Driven” strategy. But where do we start to get to all this?
Turning the information chaos into a systemized heritage
A “Data Driven”strategy by definition needs to be set up on the collection and analysis of data coming from company assets. Somehow it is necessary to allow objects to express themselves and to do it with a common language, a transversal communication standard that can be assimilated, understood and elaborated by the analytical platforms. In fact, many machines already send huge amounts of data that describe their operation, their performance and their state of health.
The problem is that most of this information is either dissipated or stored in different registers, often not in communication with each other. It is also true that many of these inputs are redundant, that is, they contain data that are not useful for analysis. This is why, first of all, it is necessary to adopt an IoT (Internet of Things) platform, which transforms the information chaos generated by sensors applied to objects into a systemized heritage that is easily accessible by analytical applications. Which will then translate the evidence into useful tips for business decision makers.
Generate new value and competitive advantage thanks to IoT
A network of objects capable of sharing and exchanging information, communicating it to the central system, revolutionizes the very way of conceiving the company. Company assets are no longer considered as simple machines and structures with operating times predefined by production cycles and ordinary maintenance operations. They are transformed into real services that define the company’s production capacity; services that can be managed according to customer needs and the actual workload to which the organization is called. It is clear that the objectives, strategies and business models of the company also take on a completely different physiognomy. Given that it becomes possible to offer customers differentiated offers based on the priorities assigned to certain production cycles. This generates added value for each batch to be created. .
You can also go further and eapply IoT to products that leave the assembly line. When the parent company receives the data that trace the entire life cycle of each reference, it has the right to process it to monitor or even predict breakages and malfunctions, so as to intervene in a timely manner or notify customers. A completely new approach to differentiate yourself on the marketand gain a competitive advantage over competitors who rely on traditional practices.
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