#CIO, IT strategy for factory

We need to ask the following question: What is the strategy in this regard and the role of infrastructure teams in the #industry?

In most industrial settings, IT professionals have now entered the factories and workshops. First and foremost, this depends on a willingness of different departments to work together at all levels. IT is increasingly being approached by factories that want to connect their machines. However, the real catalyst that has materialized is cybersecurity. With attacks like Stuxnet, we must collectively recognize that production systems, connected to IT, are vulnerable and part of the company's IT ecosystem. This realization should push the General Management, #Plant’s Directors, IT professionals, and automation experts to take steps towards each other to build a protected and controlled ecosystem.

For IT professionals, the first step was to understand the working methods in factories. Factories operate 24/7, and an IT problem can bring an entire production chain to a halt. Therefore, humility is required to understand these constraints and identify the value that IT can bring, as well as the areas where autonomy should prevail in factories for responsiveness reasons.

With these foundations, you can define an initial program to converge factory IT. Primarily, this program should focus on the lower layers of infrastructure, while also considering productivity. This first cycle will place the lower layers of infrastructure under the responsibility of IT, as it is an area of expertise. Factories can then position themselves in a logic of expressing needs and consuming services. IT must converge networks, servers, and service catalogs offered to users.

The second phase brought about by this convergence program can focus on the rationalization of application portfolios, separating real-time functions handled by automation from everything else - data, reporting, performance, and quality - which belong to central IT. Concurrently, business units can focus on #Data and #AI experimentation to structure their data needs, relevant use cases, and competencies.