The Trade-Offs Companies Face with Automation

Nowadays, automation technologies are an indispensable part of our daily lives—the impact of AI, ML, and robotic process automation (RPA) in business is clear with labor productivity in a sector such as manufacturing set to increase to 37% by 2025, according to Deloitte. Innovations in automation are also allowing us to be more streamlined and efficient with employees free from the burden of mundane tasks, but the prospect of going fully automated is a completely different story altogether.

Let’s dive into what the factors are that might be holding companies back from advancing automation processes, how businesses can identify areas that need to be automated, and what the best practices are for developing a strategic plan for successful automation.

What Is Holding Companies Back from Fully Advancing Automation Processes?

Despite the obvious benefits, several factors in play prevent companies from fully biting the automation bullet. Unfortunately, everyone’s wallets are tight at the moment and high initial costs and budget constraints are not easy to get over, particularly for small businesses.

Implementing advanced automation technologies often requires substantial upfront investment in software, hardware, and training. The latter is a pressing issue, given that81% of IT professionals think that they can use AI, but only 12% have the skills to do so. And 70% of workers likely need to upgrade their AI skills.

Automation technologies demand a workforce skilled in AI, ML, and data analytics, but there is a widespread skills gap, with many employees lacking the necessary expertise to implement and manage these technologies effectively. On top of that, even after identifying the automation to go with, integration can be really difficult. Trying to incorporate new systems in something that might be out-of-date can lead to compatibility issues and, in turn, security issues that might crop up as a result of sensitive data being leaked.

The final issue to mention is one that is harder to address than any other—resistance to change within the organization, which though it may seem something trivial, can have a huge impact on the ability to transition. Many people in management positions will continue to see automation as a threat and unnecessary distraction.

How to Identify Where Automation Can Take Effect

One of the crucial first steps that companies can take is with process mapping and analysis. This allows you to be abreast of existing workflows and identify tasks that are clearly repetitive, time-consuming tasks that can be automated, such as some data entry, payroll and customer service. Process mining and AI-driven process discovery can uncover some valuable insights into these workflows. And don’t forget to speak to frontline workers, as they often know exactly what inefficiencies exist in their daily tasks and can suggest areas where automation could have a significant impact.

It’s also a good idea to use the concept of a pilot program whereby you test out AI in a specific department. This involves several crucial steps such as optimizing the model parameters of the AI, deciding on the length of time you are going to take with the pilot, and picking employees who are keen to take on the challenge. For example, say there is a consumer goods company that wants to implement automation in their supply chain. In order to do this, they would have to identify repetitive tasks and start a pilot program in a low-risk area of their operation. Something like inventory management would be perfect in this case, as it can have very clear rules surrounding stock levels.

The Best Practices for a Strategic Automation Plan

Companies need to first define some goals for what they aim to achieve with automation, this might be reducing operational costs, improving productivity, or even enhancing customer service. Whichever priority it is, you need to include all the relevant stakeholders, including IT and the aforementioned workers who are on the frontline.

Investing in training and development is another critical component. You need to look both internally and externally for this, there is plenty of official documentation from platforms such as TensorFlow or PyTorch that offer tutorials and examples you can use. Additionally, open-source AI projects can allow employees to learn from the community and get real-life practical experience.

Ultimately choosing the right form of automation is not just a numbers game, you need to consider your team’s capabilities and the ease of use. You should also think about what upgrades might be necessary for your tech stack , how easy the product is to maintain and what compatibility there is with existing technologies so as to prevent security issues mentioned earlier. Lastly, you need to ensure that the data you are using is valid to prevent inaccurate results that might require you to redo automation tests.

Final Thoughts

Transitioning to an entirely automated future is a complex process and one that is not fool-proof by any means. However, it is on the horizon and approaching fast so we have to face it sooner or later—Gartner predicts that 70% of organizations are set to apply automation in processes by 2025. Additionally, given that 30% of expenses have already been reduced as a result of automation technology in business, the trend is only going to continue.

Companies that look to embrace automation and develop strategic plans for its implementation will be more successful. They will be able to maintain and grow their customer base while simply completing more straightforward tasks in a faster time frame. The future of automation is promising, but companies need to make sure that they allocate their resources wisely and train their staff properly to make the transition one that doesn’t disrupt operations.