Automation has emerged as a cornerstone of business efficiency and competitiveness. The ability to streamline and automate processes has become a critical skill for professionals across industries. The promise of streamlined processes, reduced manual labor, and improved accuracy is alluring. Automation not only increases efficiency but also frees up valuable time and resources that can be better utilized for strategic initiatives. Yet, despite the undeniable benefits, many teams find themselves grappling with the challenges of successful automation implementation.

Here are 4 key reason you and your team are struggling to automate.

1. Your processes are too subjective.

The need for subjective decision-making within your processes leads to inconsistencies and errors, making automation a challenging endeavor, but more importantly most automation is dependent on definitive triggers. Processes that involve intricate decision-making requiring human judgment, creativity, and nuanced understanding are often challenging to automate. Automation excels at repetitive tasks with clear rules, but it struggles to replicate the depth of human intuition.

Automation thrives on consistency and predictability. Processes that lack standardization or have frequent variations can pose challenges for automation. If a process is executed differently each time, it becomes difficult for automation systems to handle the variability effectively. Removing subjectivity and standardizing your procedures with clearly defined and documented steps provides a standardized framework for automation. Make sure that each step is outlined in a precise and unambiguous manner.

Invest time in process documentation and analysis. Break down the process into its individual components and identify pain points that could benefit from automation. Clear process understanding lays the foundation for effective automation.

Be sure to quantify your parameters. Translate qualitative factors into quantitative ones. This might involve assigning numerical values to variables that were previously subjective. For example, instead of relying on vague terms like "high priority," assign a specific numerical value that indicates priority level.

Implement rule-based logic by creating a set of rules that govern decision-making within the process. These rules should be objective and based on quantifiable parameters. Rule-based logic forms the foundation for an automated system to make consistent choices.

2 Your processes have too many variables.

When you explain your process to someone who is new to the process, are there a lot of 'If this, then this, but if this then this...etc.' This could be a sign that your process has too many variables. Variables are another way to introduce complexities into your processes and complexities are the death of automation.

Simplify and streamline the process by removing unnecessary steps or components. The more complex the process, the harder it is to automate. Simplification reduces the likelihood of errors, increases the efficiency of automation, and makes it easier to identify automation triggers.

3 Your process lacks triggers.

Automation runs off triggers, or data that tells the system what to do next. and when to do it. Triggers can be events, conditions, or actions that signal the need for automation.

To identify triggers, map the process flow. Understand the sequence of events that lead to the process in question. Identify the key points where automation can be triggered. This could be a specific time, an input from another system, or the occurrence of a certain event.

Define triggers clearly and precisely and then document them. This ensures that the automated system knows when to kick off the process without ambiguity. Ambiguous triggers can lead to untimely or erroneous automation.

Continuously monitor the effectiveness of the triggers. and then adjust as needed. As business conditions change, triggers might need to be adjusted to maintain relevance and accuracy.

4 You have bad data.

Automation relies heavily on accurate and accessible data. If a process involves data that is incomplete, inaccurate, or spread across disparate systems, automation efforts can lead to errors and inefficiencies.

Each time human intervention is involved in managing data, the potential for incomplete or erroneous information grows, and in manual processes, all data inevitably passes through human hands. If you're considering automation, it's likely that your processes are currently manual. The #1 obstacle hindering the automation of these processes is often the integrity of your data.

The crux of the matter is this: You aspire to automate manual processes to enhance efficiency, yet the data underpinning these processes might be compromised due to their manual nature. It's a never ending cycle.

Prioritize data quality and accessibility. Implement data governance practices and integrate systems to ensure that the required data is available and reliable.

Recognizing the characteristics that make a process challenging to automate is essential for making informed decisions about where to invest your automation efforts. Before embarking on automation, carefully assess the nature of the process, its standardization, decision-making complexity, rate of change, level of personalization, and data quality. By doing so, you can strategically allocate your resources to areas where automation will truly shine and bring about transformative benefits to your business.

Rhonda Lea is a Certified Six Sigma Black Belt, business consultant, and process expert. She is on a mission to help organizations that are struggling to scale by transforming chaos into scalable systems. She is founder of Scale The Chaos, a business consulting boutique, and author of the soon to be released book 'Scale The Chaos: Organizational Dysfunctions Sabotaging Your Ability to Scale'.