Automation is no longer a futuristic concept. It’s something we see in everyday business settings. Companies are leveraging the power of advanced technologies to automate tasks that previously required manual processes. Automation is easier to implement in some industries than others; think technology and industrial businesses.
In technology-focused businesses, automation usually involves using special software, often powered by artificial intelligence (AI), to handle repetitive tasks. Automation is much easier to implement in these settings because the primary objective is to develop capable systems and applications that can handle the required tasks. The use of hardware components is minimal.
Things are a lot different in industrial businesses. Think of a vehicle assembly line and what it will take to achieve complete automation in that setting. Gigantic hardware solutions such as robotics coupled with advanced manufacturing systems and control rooms are needed to increase the output and efficiency of production lines.
This article gives a detailed analysis on why automation is more accessible and easier to implement for technology businesses compared to their industrial counterparts.
Most technology-based businesses already have an existing digital framework that supports automation. All they have to do is to find or develop a software application that addresses their specific needs and integrate it. For example, software as a service (SaaS) companies integrating chatbots on their websites to address customer enquiries.
Testing and deployment is easier and takes significantly less time in technological businesses. This is because the process rarely requires physical installations or upgrades. Setting up automation systems takes just days or a few weeks, and once operational, these systems can run autonomously and sync data using internet connectivity. Also, thanks to cloud computing, these companies have easy access to the tools and resources that they need to scale.
Automation in technology businesses often involves software tools, which are usually more affordable than specialized hardware solutions. A perfect example is a technology business using machine learning to analyze consumer behavior. This requires a relatively small capital compared to venturing into robotics or industrial automation systems.
Many people who work in tech companies are tech-savvy and have prior experience with automation, reducing the learning curve associated with the introduction of new tools and software. Consequently, the time and effort spent on training team members is minimal.
Effectively adopting the directions from a control room is easier.
Unlike technology businesses who can operate remotely, industrial companies rely on physical infrastructure for their day to day operations. Installation of automation hardware such as robotic arms, conveyor belts, and sensors take a considerable amount of time and require making changes to existing setups.
Due to the fact that industrial businesses require both hardware equipment and specialized software for automation, the cost is often prohibitive. Sometimes the hardware components have to be designed from scratch and brought to life by diverse teams of professionals. In addition to that, maintenance costs are much higher compared to exclusively software-based automation.
Industrial businesses must adhere to stringent safety standards and regulations to avoid being shut down or fined huge amounts of money. These regulatory and safety bottlenecks add an extra layer of complexity to automation and lead to more delays and expenses.
A good number of industrial businesses rely on manual or legacy systems and human labor. This makes the shift to automation more difficult and cost-intensive than it should be. The cost and time required to retrain workers who may have no previous experience with automation systems can span from months to years.
Automation is without a doubt the present and the future and businesses need to embrace it to stay competitive. Unfortunately, industrial businesses will always face more significant automation challenges tied to high financial costs and infrastructural limitations. However, in the near future the gap is expected to get narrower with advancements in robotics, AI, and internet of things (IoT). These advancements are expected to reduce costs and other associated challenges preventing widespread adoption of automation in industrial settings.