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To understand the importance of technology within the scope and scale of Digital Transformation we have to understand that digital, within this context, refers to the rapid speed of change we are currently experiencing in manufacturing. The digital revolution is undoubtedly powered by technology – the internet (cloud), mobile technology (5G), computer processing (GPU), artificial intelligence, machine learning, nanotechnology, robotics, software robotic applications (RPA), and advanced information processors. These are just some of the multitude of tools that we can use to execute, optimise, and automate processes in different ways.
If we look at People (culture), Process and Technology, as being the three cogs in the Digital Transformation machine. Then the cohesion between the three cogs is undoubtedly strong, but it is worth examining the nature of this relationship to fully understand the part technology plays within a Digital Transformation system.
As strange as it may seem, technology is not the starting point or even the objective, instead it is the entity that empowers our processes, it is what drives them. Technology is what allows us to deliver our business objectives through three key stages; digitisation, digitalisation, and digital transformation. To understand the role that technology plays in Digital Transformation we must consider what it means for our business and organisations.
Initially, decades ago, back in the 1970’s we began by digitising our products and services, by adopting digital technology through mini and mainframe computers. Since then in the 1980’s we began to develop the adoption and integration of Personal Computers (IBM PC 1982) as we transformed our natural analogue world into the computer friendly digital world. At that time, analogue to digital conversion enabled integration between the ‘analogue’ real world sensors, actuators, and devices, with the latest powerful digital computers. This allowed us to ingest analogue ‘wave’ raw data signals from devices and sensors; (sound, light, temperature, and pressure), and convert them to digital computer readable numbers that could be read, analysed and processed by microprocessors. This was termed Digitisation, and heralded the dawn of the digital age in manufacturing.
The collection, transformation, and analysis of analogue signals to digital binary conversion was only the start, as a second stage was to follow that would transform these digital signals into a common format that could be shared and understood across diverse technical and business silos throughout the organisation. This is what is termed Digitalisation. This process allows us to share data across business (silos) domains and transform it into a common format as useful information which can be readily shared with others. This was always problematic as most systems have dedicated databases with disparate data schema, models and structures, which made extracting, aggregating and analysing data very difficult. Traditionally, data from disparate databases were extracted and stored in a central data warehouse using ETL technology, (Extract, Transform and Load), which is a process that extracts data from one system and converts it into another format to be loaded into a common schema, typically in a data warehouse.
This was difficult but well worth the effort as it allowed for rudimentary integration and automation of processes and workloads. However, the ultimate objective of aggregating and sharing information across business domains spanning the entirety of the organisation is to turn it into usable and valuable business knowledge.
The goal of digital transformation is, and has always been, to build a system where business knowledge is shared throughout the organisation and preferably even beyond organisational borders into the supply chain, via vendors, suppliers and customers. However, for that we need technology, to deliver, and enable our business processes.
A common trap is thinking the technology itself is the driver of change. It’s not. Technology provides the means by which processes/tasks can be carried out. Technology gives us new capabilities. Technology is just a tool, it enables processes to work more efficiently.
Often we don’t, so it is always best taking the time to contemplate the status quo, and our future requirements. Why do we need some new technology, what does it deliver, is it cost effective, and is it even viable?
To answer this, we need to ask a whole series of further questions:
Technology is changing the way that we go about our work, how we communicate, how we manufacture products, and nearly every aspect of our lives - but technology should not be the focus. The design and deployment focus should be on the automation of processes. The technology is a mechanism, technique or methodology, allowing us to execute the process faster, more effectively, more conveniently, often more affordably and with greater accuracy than if we did it manually. The goal is to increase business process automation so that we can gain a competitive advantage. Technology provides the solution, it is the enabler that defines and solves the problem for the business by surfacing and mitigating pain-points and delivering solutions, which improves our customers experience.
At the advent of any Digital Transformation journey we need at least a minimum of three voices around the conversation. The first and most important will be the executive who has the responsibility for defining the business problem, they will be asking the pertinent questions, giving direction and making the business decisions. Then there should be a marketer. Their task will be to communicate the desired solution and any value proposition. They will also have the important role in surveying and testing the marketplace, gathering the customer data to test out the ideas and assumptions. They will also need to find out if customers are actually searching for that proposed product/service and if they are, will they pay for it. Finally there is the technologist, who is the solution builder. They will understand and collate all the necessary criteria and design a solution, they are the solution architect.
Strategy and culture in digital transformation always comes first. Strategy comes from defining the problems, understanding the customer, the marketplace and the resources (people), which we can leverage to create a competitive advantage, which sets the direction of travel. Then the next change block is to address staff and customer engagement. Engaging customers is essential on the road to digital transformation. Engagement relies on the ability to provide a product or service that is valued by customers. But this requires technology.
Designing the overarching technology platform to automate processes and accelerate innovation is the next change block. This is about creating continuous cycles of innovation that fuels creativity and improvements. Hence, the internal culture must align to support the strategy that will over time sustain our competitive advantage.
Finally, we need to consider real-time data collection, storage and analytics. This is where we have to build learning exercises into our organisations. We need to measure our process inputs and our outputs, analyse our successes, benchmark our efforts, score our innovations and then collate this information to give us the evidence we need to determine future direction. In short we need to perpetually analyse our performance, marketplace and gather competition and customer data to understand their behaviour. But this is a hugely taxing endeavour without the integration and automation of the business and operational processes.
But it doesn’t stop there, as we then start again – back to strategy and work through the processes to the next cycle of innovation. It is the choice of technology that allows us to do this through automation and process integration. Technology is the engine that keeps those cogs turning.
The deployment of new technologies are delivering improved changes to manufacturing, which have resulted in faster production, increased velocity to market and to profit, new efficiencies, reduced costs, and the ability to scale exponentially.
Deploying new technologies have improved the manufacturing process by using automated systems to track and categorise data that can further improve efficiency and productivity. Manufacturing automation has also given businesses more control over their entire operational system.
Basically, when we refer to manufacturing automation, it is the use of deploying advanced technology to integrate and automate production and business processes. This typically was a manual process but introducing automation is very important as it improves efficiency and productivity by removing any human intervention from the process. As such, manufacturing automation systems can include IoT devices (sensor and actuators), software, machine tools, robots, or even advanced enterprise systems. Machine monitoring is often the first step in any process automation initiative as this allows you to report on utilisation, set variable production times and schedules as well as track down-time.
Machine monitoring is about extracting, storing, organising, and utilising the machine data from equipment on the factory floor. It allows you to collect and collate information about the process automation as it’s happening. This process allows you to understand how each machine is operating as well as to evaluate the overall equipment effectiveness (OEE) of your machinery.
The thing to keep in mind is that the overarching goal of manufacturing automation is to drive efficiency, reduce costs, and increase production capacity. Hence, automation on the plant floor relies on machine-to-machine integration, software, autonomous machines and advanced robots to reduce the amount of human interaction required.
Manufacturing automation is a broad term, so there are different types of automation that deal with different aspects of manufacturing.
Fixed automation is a system of automation that is set up to produce specific products on individual machines. For example, a machine that exists only to create a single product is a fixed automation system.
Programmable automation systems have the capacity to change as you can simply create another program to instruct the system to follow new configurations. However, there is associated downtime with new product configurations and product sequences. One example of programmable automation is with programmable logic controllers (PLC).
Flexible automation is in a way similar to the programmable automation of the PLC but it adds another layer of flexibility as they are able to quickly respond to new production changes. This means they can rapidly adjust to variations in product specifications without the extensive downtime associated with programmable (PLC) automation. This makes it suitable for real-time remote, or on-demand production.
Intelligent automation (IA), is the use of automation technologies that have embedded artificial intelligence (AI) and machine Learning capabilities to streamline and scale decision-making across the organisation. Intelligent automation simplifies the automation of processes by intelligently interfacing and integrating with resources to improve operational efficiencies.
The most critical component of intelligent automation is its embedded artificial intelligence, or AI component. Effectively it is using machine learning and complex algorithms to analyse structured and unstructured data, and when deployed strategically and interfaced with a data warehouse it can formulate predictions based on that data. This is what is known as the decision engine of IA.
However, Intelligent Automation has a variety of applications throughout the organisation. For example, an automotive manufacturer may use intelligent automation to reduce costs and gain resource efficiencies where perhaps legacy or manual repetitive processes exist. Moreover, as Intelligent Automation systems also have inherent business process management (BPM), and robotic process automation (RPA) capabilities they could be used by enterprises for intelligent automation in the business domain such as when handling standard forms, making predictions used to calculate inventory needs, or addressing compliance requirements.
Intelligent automation platforms are the catalyst for process orchestration, which can deliver many benefits which can include:
Business processes are often complex and non-linear with a plethora of end-points making it especially challenging in microservices or API software architectures. Indeed some complex organisational-wide processes may require advanced workflow patterns, like dynamic parallel execution, termination/interruption of activities, waiting on events to happen, and much more to be taken into consideration. This is where process orchestration becomes critical as it is the ultimate form of automation, as it autonomously and seamlessly “conducts‘‘ the flow of processes between a multitude of people, machines, software APIs and device end-points.
When deploying end-to-end process orchestration you are ensuring that all of your processes will be operating seamlessly throughout the organisation. Indeed, process orchestration effectively breaks down silos between IT (business) and OT (production) systems, and helps enterprises achieve their digital transformation objectives. When planned and deployed diligently, it’s software and device-agnostic, so it will work effectively within an organisation’s existing tech stack.
Technology is simply the enabler for process automation. It’s what we do with it that determines success. Technology is the tool that enables us to run our business and operational processes effectively. Technology is an enabler for automation, which in turn is a delivery agent that can provide precision, accuracy and consistency as well as reduce costs when running business and operational processes. When implementing new technology for digital transformation in general or for process automation specifically, defining the problem and understanding the context, the purpose, and the desires around that problem is the key to success. When it comes to creating a digital business, automation technology, in all its forms from legacy to advanced intelligent automation is an important change block that must be diligently addressed to bring about a successful transformation.
About the Author
Written by Alasdair Gilchrist, a technology polymath that has spent 35 years in the field of technology spanning roles as a computer technician, data analyst, network engineer, security professional, OT data engineers, cloud native developer as well as serving as an IT Director.
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