Digital Transformation Terms You Need to Know

Digital Transformation Terms You Need to Know

No business is left untouched by technology. Manufacturing, production, distribution and other industrial businesses have experienced a profound evolution over the last century. It started with Industry 1.0, characterized by the advent of steam power, and evolved to Industry 2.0, marked by the introduction of electricity and assembly line production. Then came Industry 3.0, where computing and programmable controls started to play a significant role in shaping production processes.

Now, with Industry 4.0, we’re automating entire business processes with real-time data from the plant floor. This is creating a significant shift in how industrial facilities are operating and how they can grow into the future. It paves their path to transforming into competitive, efficient, safe businesses which produce the highest quality products for customers. Existing technologies are leveraged in Industry 4.0, and disruptive systems and concepts are embraced that can optimize end-to-end processes by transmitting and using real-time data from across the organization to make faster and better-informed decisions.

This data comes from a variety of sources including sensors in machines on the plant floor, Enterprise Resource Planning (ERP) systems, Programmable Logic Controllers (PLCs), quality management systems, as well as a variety of devices that measure speed, output, and other operational data points.

What is Digital Transformation?

Digital transformation is the process of leveraging data and technology across all aspects of an organization to improve business processes. By enabling seamless accessibility, transmission, and management of data, digital transformation empowers businesses to gain deep insights into their operations and equip themselves to continuously monitor progress and activities. In many cases, the primary focus for digital transformation activities involve:

  • Improving efficiency by eliminating manual tasks and disconnected processes
  • Reducing downtime through predictive (and prescriptive) maintenance
  • Decreasing waste throughout the production process

All of this is dependent on data, connectivity of devices across the network, and consistent processes to collect, transmit, and contextualize data. In this environment you are empowered to make sense of all the data flowing through your facility, transforming it into information you can use to take real-time, data-driven action.

Key Digital Transformation Terms Defined

Today, you may find yourself preparing for your digital transformation. Or perhaps, you are already in the midst of your journey. Regardless, there are many pieces involved in digital transformation and each of them can help you make incremental progress. Once you understand each of the pieces, and their associated definitions, you’ll see that digital transformation doesn’t have to be a single, large-scale, daunting undertaking but rather a series of steps for ongoing, sustainable progress. That’s why we call it a journey, one in which the terms outlined below will all be present at various times along the way.

And now, let’s get to it. Following is the Tri Tech list of Digital Transformation terms that will help you get more comfortable with the process:

IT/OT Convergence: IT/OT convergence refers to the collaboration of Information Technology (IT) systems with Operational Technology (OT) systems. Traditionally, IT teams have been responsible for technology requirements for the office, including operating systems, networks, security, and the like. OT lives on the plant floor. Teams in this space are focused on the machines, devices, and connectivity required for the plant to run smoothly.

Digital transformation requires the expertise and perspective of both IT and OT. This ensures that digital transformation initiatives take an enterprise-wide approach rather than a siloed one.

Data Governance: Because digital transformation relies on the accessibility, transmission, and use of enterprise-wide data, it’s important that a standard structure, and standard processes and policies are in place to create a unified data layer. That’s what data governance is all about. It’s akin to establishing guidelines for consistency, such as deciding whether individuals named Timothy are referred to uniformly or if variations like Tim are permitted, along with considerations of capitalization, but done in a multi-dimensional structure (following ISA-95) as well as defined cadence.

Most importantly, it’s about establishing rules to facilitate harmonious interaction within the shared data environment, ensuring everyone plays by the same set of guidelines.

Agile Methodology: Defining exactly what your company’s digital transformation end game looks like is impossible. Everchanging technology and needs can make any scope that is initially defined deemed unnecessary, and plans can become quickly dated in the digital world. An agile approach can provide quick value to allow you to see benefits of your investment sooner, incorporate ongoing lessons learned while redirecting focus towards the more urgent tasks as time goes on. So it breaks this large initiative into phases (small sprints) and redirects based on continuous learning from previous activities or introduction of new technologies.

Agile methodology is an IT concept that can translate into tangible benefits for digital transformation. That’s because not only is digital transformation unique to every customer’s situation, but also because it’s a journey. Everyone starts in a different place. Agile allows the process to meet you where you are while making an impact in high priority areas and adjusting along the way. Traditional waterfall approaches to digital transformation often fail due to long timelines and rigid specifications. A waterfall approach often misses the mark and leads to a delay in tangible benefits that can be realized much earlier with an agile approach.

Unified Smart Manufacturing Architecture: Just as data governance sets the rules and processes around data entry and capture, the Smart Manufacturing Architecture provides the standardization for where data is collected and contextualized. Whether operations exist in one facility or across multiple plants in far-away regions, this ensures a reliable single source of truth for data.

Edge: In a digitalized plant environment, collecting and processing data as close to the action as possible is critical. And because much of the action, so to speak, happens far from a centralized data hub, edge devices are implemented at remote locations of the OT network so that data can be evaluated, analyzed, contextualized, processed, and acted upon more quickly. This eliminates any latency that would impact timely algorithms such as OEE.

Cloud: The Cloud refers to a network of servers, typically accessed over a network, that stores and manages data, runs applications, and delivers computing services on demand. The Cloud provides a space that is easily accessible to people and applications and is continuously maintained to reduce overall cost of ownership. In contrast, you might hear the term “on-prem,” which refers to hosting applications or storing data in assets physically located on your premises.

Data Ops: Data Ops is the set of practices, procedures, and technology that facilitate the transformation of raw data into usable information, primarily facilitated by edge components that transmit data. It requires establishing a structured data architecture in industrial companies so they can effectively navigate, comprehend, and leverage their data for various systems and processes.

Contextualize: Contextualizing data involves providing a systematic architecture and additional information to the data to enhance its purpose and origin. Take a temperature sensor for example: instead of just receiving temperature readings, contextualization associates the temperature with specific information about the temperature such as the location (area, line, system), manufacturer of the sensor, data or origin etc. Contextualization of data close to the edge can provide organic scalability of your digital transformation initiative leading you to a true smart factory.

SaaS: Software as a Service (SaaS) is a cloud computing model where software applications are hosted by a third-party provider and made available to customers over the internet rather than through the purchase of traditional software installed on individual computers. While it’s been around for quite some time, it has become more mainstream in recent years as the maintenance benefits it delivers make it a smarter investment choice. Technology and capabilities are evolving faster today than ever. SaaS ensures you have access to the latest capabilities as they become available.

Hidden Factory™: The Hidden Factory™ refers to the untapped potential in your current operation. It reveals various inefficiencies, data or technology gaps, hidden overhead, and other constraints that limit your production capacity and profitability. Unlocking the hidden factory is the primary goal of digital transformation activities. It entails using machine learning and other data processes to discover methods to enhance efficiency and uncover new revenue opportunities.

Doing so directly impacts your bottom line as any efficiencies uncovered through the process go directly to your profits. Why? Because your budget is likely based on whatever level of productivity your facility currently operates at. Think about the dollars associated with even just a 2%-5% increase in productivity. That’s the Hidden Factory™.

Digital Transformation Maturity Assessment: This is a valuable and proprietary service offered by Tri Tech that helps you define prerequisites for your specific digital transformation journey. This assessment provides a comprehensive gap analysis, highlighting the differences between your current state and desired future state. It also emphasizes the importance of identifying quick wins—addressing the most significant areas of concern and collecting relevant data promptly.

When in Doubt, Collect Data

Data is the lifeblood of any successful digital transformation endeavor. The underlying goal of digital transformation should always be to enhance profitability throughout the organization. This involves identifying business and production process inefficiencies to maximize output and uncover hidden revenue streams or minimize wasteful processes.

Unlock the full potential of your business with Tri Tech’s Digital Transformation Maturity Assessment. Our comprehensive assessment goes beyond surface-level evaluations, delving deep into your business’ digital infrastructure, processes, and culture to identify areas for improvement and growth. Don’t let uncertainty hold you back — reach out to Tri Tech today!

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