The IT-OT convergence (part I): Syncing the Data Journey and the Digitization of Infrastructures

This is the first article of a new series we will be producing to cover the complexities of this journey towards the full IT-OT convergence in industrial companies.

Technology

The IT-OT Convergence: the quest for Industrial Companies

The digital transformation of any company, especially industrial companies, begins with a data-centric strategic approach. A “Data team” explores how to leverage the company’s data to solve specific problems, optimize processes, or create new revenue streams. This marks the start of what can be called their “Data Journey”. During this process, there will be a moment where the Data team must integrate their creations—apps and even AI algorithms—with the company's infrastructure to either extract data from their assets or trigger actions, or both. This is where friction begins.

This is the first article of a new series we will be producing to cover the complexities of this journey towards the full IT-OT convergence in industrial companies. Consider this first post a comprehensive overview of that journey. Let’s get to it!

The Data Journey: from Data to Insights

In the process of planning and implementing a data-centric strategy, companies start their journey by obtaining data and can culminate as far as in the creation of AI models from this data.

The Data team will typically spearhead these activities, focusing on specific problems or challenges according to the company’s needs. They will define a strategy that includes determining which data to collect and how to transform this data into actionable insights.

It all starts with the data.

Initially, Data teams might work with "offline" data—historical data previously collected and stored in CSV files or databases. They will use this data to create their first "business intelligence" applications, such as visual dashboards to present information or generate reports. Depending on the strategy, it’s likely they will evolve these applications into more intelligent ones, based on Artificial Intelligence.

However, during this journey, Data Teams will probably realize they need more than just offline data, which is only available intermittently. They need live data obtainable from the various assets and potential data sources the company has. They need the infrastructure guys.

The OT Infrastructure

Meanwhile, the companies' infrastructure teams have their own lives. In industrial settings, infrastructure has historically focused solely on operational aspects—the OT. Their evolution has been oriented towards process automation, not data exploitation, and they always try to separate the Operations (OT) network from the Information (IT) network.

This is the typical Automation Pyramid that the OT teams usually have in mind,  when thinking about evolving their infrastructure.

When OT teams plan the digitalization of their infrastructure, their thoughts are likely to focus on enhancing or adding SCADA systems and MES. Consequently, when Data Teams approach them with a strategy aimed at exploiting data, they encounter significant misalignment between the teams.

The Digital Infrastructure Journey

Implementing the data strategy envisioned by Data Teams implies that the infrastructure must evolve by converging the OT and IT networks. Changes are necessary so data can be directly obtained from company assets, and applications based on this data can be deployed and executed on-site.

The infrastructure needs to navigate their own “Digital Infrastructure” journey

Data must be captured from machinery and sensors distributed across the company’s facilities in a way that does not interfere with operations. 

Applications based on this data must be deployed and installed, often very near where the data is generated, at "the Edge." And, eventually, these applications will evolve into AI models and AI-based apps.

This journey to evolve Edge infrastructure into an “intelligent one” is filled with challenges that must be addressed step by step.

Barbara, a software to navigate along the IT-OT convergence journey

Data teams need tools to help them orchestrate all the applications and even AI algorithms that they will eventually deploy in distributed locations.

And Infrastructure teams need tools to help them transition their infrastructure from being isolated, to becoming truly intelligent.

This is exactly what Barbara does.

Barbara is software that empowers Data Teams to deploy, run, and monitor data-based applications and AI models on-site, simpler than the cloud, while providing OT teams the necessary tools to transform their infrastructure into an intelligent one. We do so,  with an Edge infrastructure, enabling companies to overcome the costs, privacy and latency challenges that the Cloud presents.

The best way to understand how Barbara works is with a quick demo, so take a look at this one  In the end, it’s clear that, to align the Data strategy with the infrastructure needs, companies need tools and software that help them navigate this complex journey.

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