Artificial intelligence (AI) and automation are terms that are frequently and incorrectly used interchangeably. Automation is a system of operating or controlling a process to accomplish tasks with little or no need for human intervention. AI is a horizontal technology that learns and mimics human intelligence over time by analyzing patterns in data. Sometimes the rules that drive automation are preprogrammed, and other times those rules are deduced by AI.
This muddying of the waters can have the negative effect of deterring many small and medium businesses from implementing automation (the importance of which I discussed in my previous article) because they believe their operations arent quite ready for this level of technology. They may be right, but only partially. While they may not be ready for AI, there are few businesses that would not benefit from some type of automation.
In my experience, the two most common types of automation found in enterprise IT environments are robotic process automation (RPA) and workload automation (WLA). RPA is software programmed to do basic tasks that mimic human users across applications. It is installed on the desktop and is operated directly by business users. WLA is software used to design, schedule, monitor and manage scripts and executables across the enterprise. It is installed on a companys servers and largely operated by IT users.
They are complementary solutions with distinctly different use cases, which means that depending on the need, many organizations might benefit from both. At their core, RPA and WLA enable businesses to focus on highest-value work, so if you are considering automation as part of your organizations digital transformation, there are several important factors to consider.
Identify exactly what headaches automation will solve for you.
Is your organization inundated with a large quantity of data that is time-intensive to organize and input? Is it eating up man-hours that could be better allocated elsewhere? If you answered yes, and there is no way to get this data programmatically, then RPA might be the appropriate remedy to your data-deluge-induced headache because data entry is what it does best. In addition to mimicking user inputs into the application user interface, RPA can also automatically download files from websites and autoformat documents.
Perhaps your organizations needs are slightly more complicated, and in addition to being inundated by data that requires filing, there are dozens, or maybe even hundreds, of processes that must be accomplished each day, often simultaneously, in order to simply function. Examples of such tasks include data processing, file transfers, service level agreement (SLA) monitoring, complex reporting, business day closing/opening process and many more. If your needs fall somewhere in this realm, WLA may be the ideal choice, potentially in addition to RPA.
Evaluate the risks.
Every process in place resists change and makes further adaptations challenging. But not all resist changes equally. Consider:
1. Manual processes resist change because people dont like to change. And the actual process being followed can be difficult to even know because the knowledge is spread among many individuals, often with no one person knowing the whole process. However, small changes tend to be adapted to easily.
2. RPA can automate the repetitive tasks of some of those people. But the specifics of what is being done continue to be hidden from the owner of the whole process. And worse than in the manual case, the RPA may fail when a small change is introduced to a website or screen that the RPA interacts with (e.g., the addition of a confirmation pop-up). Conversely, people can often easily adapt to these types of changes and recognize what needs to be done differently to keep the process working.
3. WLA resists change simply because it takes time and energy to redo steps of automation. However, in the case of WLA, the automation itself is self-documented such that you have a complete road map of your process. This makes adapting to change understandable and the timeline for doing so predictable much more so than processes run by people or robots.
I believe this distinction in risks makes WLA the compelling choice whenever possible, with RPA used for those steps that simply resist programmatic automation. When done this way, the WLA process documentation helps keep track of the RPA in use and minimizes the risk of using RPA.
Consider your budget.
Because installation and implementation are quick and easy, RPA is typically the least expensive upfront, especially if your needs are simple and you have a limited number of users. However, you will find that as your workforce and needs grow, so can the cost of RPA this in addition to the risks discussed above.
Conversely, WLA typically has a higher upfront cost due to the amount of work required to install and implement it. However, depending on the use case, WLA can end up being the least expensive option in the long run, due to its ease of scale and maintainability as your business evolves.
At the end of the day, its important to remember that automation isnt synonymous with artificial intelligence. Just because your business may not be ready for AI (and all of the expenses and intricacies that come with it), doesnt mean it isnt ready for RPA, WLA or maybe even both.
Each step you take toward automation preps more of your business to benefit from AI in the future. And by taking a proactive approach to automation, not only do you move your business forward; you can help keep it from sliding further into the traps of unknown and hidden processes.
Link:
How To Choose Automation That's Best For Your Business - Forbes
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