Have you heard you can learn more from your mistakes than your successes? That’s the core concept behind the intelligent automation strategy I’ll share in this blog post.
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Table of contents:
- Intelligent Automation Meets the Pie Maker
- 3 Key Aspects for a Successful Intelligent Automation Strategy
- It's Time to Advance Your Process Management Skills
A modern intelligent automation strategy involves upgrading your robotic process automation (RPA) and artificial intelligence (AI) processes by learning from mistakes, learning by listening and evolving to higher levels of process optimization.
To put it another way, you learn to listen to the people who are relying on your RPA/AI processes and their outcomes. You keep listening to their concerns, and their inputs, to continuously improve your results. Using a cognitive, iterative approach and putting people first, you allow intelligent automation to quickly provide better solutions and improve workflows.
It’s not a complicated concept. Grandmothers have been following IA for decades—well before IA was even a term in the digital world. Turns out, the evolution of her cherry pie recipe is a result of intelligent automation principles. The IA process is as simple as wanting her family to love her pie when she serves it.
Intelligent Automation Meets the Pie Maker
Today, using intelligent automation, you can meet the demands to humanize the applications your company develops and rely on daily for successful operations and improved business processes. Uncovering modern methods to understand and improve how a user interacts with your artificial intelligence (AI) and robotic process automation (RPA) applications is achieved by applying an intelligent automation strategy.
You see, over time, Grandma learned to add the cinnamon that her son-in-law likes, and the cranberry raisins her grandchildren asked for. Her recipe changed to meet the changing tastes of her family. She applied the IA principle of putting people first to the process of baking her absolute best cherry pie. In addition, Grandma doesn’t rewrite her recipe every time she adds an ingredient; she simply iterates her existing recipe card.
That’s similar to how you can use low-code in your enterprise today. It enables you to quickly incorporate feedback and inputs, and quickly assess if the app you’ve made is good. Low-code is one of many automation tools that continues to be a powerful competitive weapon in the arsenal technology companies have to improve their application’s value to their organization.
Employing IA (not to be confused with AI—artificial intelligence) often revives a company’s AI/RPA initiatives by reinvigorating its previous efforts. AI/RPA was once perceived as the holy grail, and automated results were expected to create dramatic changes for organizations (and lower staffing levels).
That has proven to be a flawed expectation. It was missing the human qualities needed for people to interact and use the applications at higher productivity levels, while reducing anxiety and distrust. It was missing new ingredients to make the next versions even better.
The reality is many efforts fell short of their objectives because they did not recognize the importance of applying an intelligent approach that can enhance the value your employees deliver to your organization.
Grandma makes it look so easy. So, how can you implement an intelligent automation strategy in your company?
3 Key Aspects for a Successful Intelligent Automation Strategy
Here are three pillars for a successful intelligent automation strategy.
1. Adopt a People-First Mindset
The digital tasks and procedures that can be standardized and automated should be. That’s fine, but it's not an end-all solution. In practice, people are needed in the recipe and will continue to provide significant value as RPA and AI are implemented.
Plan to utilize pre-built best-of-breed UX/UI components that are proven to improve how people interact with automated software and systems. Improvements to how your staff interacts with their specialized departmental applications will result in process improvements across the organization.
2. Take an End-to-End Approach
We’ve heard it many times. A company’s inauguration to AI and RPA started as a test, often on a less-critical project. When results were below expectations, it was like a sour cherry in the previous pie, creating an assumption that all cherries would be sour. It’s not an accurate assessment. What was missing were the secret ingredients in Grandma’s recipe, a proven baking process, and heaps of desire to please her family.
Begin to look at your business processes in their entirety. Are the efforts you are responsible for resulting in improvements for the business? Make certain you are optimizing your coding techniques and sharing across the entire organization, and not just improving one department at the expense of another. You are responsible for the entire pie.
3. Rapidly Iterate
Grandma made subtle changes to her recipe over time. She made small changes to meet pertinent requests. Stop viewing AI and RPA projects as massive undertakings. Instead, attack them in small, manageable steps. It’s an intelligent and logical way to implement process automation. And for it to be practical, your change management processes must be agile and efficient.
It’s not enough to build apps fast. You need to quickly make modifications, assess their impacts, and then make more changes in a continuous improvement process.
It's Time to Advance Your Process Management Skills
Intelligent automation from OutSystems helps evolve your maker skills. Using the OutSystems high-performance low-code app dev platform and implementing an intelligent automation strategy for your IA and RPA projects will help you optimize your business processes while minimizing technical debt. Adapt your internal processes to be faster and more streamlined for greater productivity and operational efficiency.
OutSystems intelligent automation brings a fresh level of human interaction to how your company embraces and uses its applications. To learn more download the ebook Improving Process Automation with AI and RPA Humanization.