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Three Considerations before you Automate

When setting out of Robotic Process Automation, the first obvious step is to jump in and educate yourself about the current marketplace. This is a good thing so still do it, but it can overlook three considerations that are much closer to home, basically

  • Are there options with your existing technologies?

  • What are your immediate goals?

  • Where do you want to get to?

These are basically questions of architecture, lets look at examples of each:

1. The advancement of other (non-automation) technologies

The increased performance of rapid application development tools, the wider application of API's and the valid desire to avoid increasing technical debt by adding extra layers of technology to legacy systems all point to considering whether replacing your legacy systems is actually a better choice than adding automation. The benefits achieved from the rapid deployment of key applications at a greatly accelerated pace using low code development environments for example are a reasonable alternative option. RPA tools have undoubtedly evolved significantly over the last few years but it is important to remember that the same is also true of other development tools in our software arsenal that may provide a beneficial alternative.

2. The need for data before you begin

The quality of your existing data can make it very difficult to get started. Low quality, or missing, information will prevent you from moving forward until you have a way to capture the information in the first case. Using some of the accelerated delivery options mentioned in the previous point, it is possible to quickly build and deploy solutions that will give you the opportunity to collate the data needed for future automation. A terrific example of this we have seen is the development of a Q&A knowledge base that now is a source of information for future chatbot development.

3. The gateway to intelligent applications

The combination of rapid development tools and good quality data also paves the way for the development of Intelligent Applications. The same tools that allow rapid development are now beginning to provide simple connectors into machine learning tools. It's early days but already we are finding multiple new entrants finding innovative new ways to apply machine learning your development toolset. Existing low code solutions that paved the way for rapid application development are now applying the same thinking to Intelligent, Learning Automation.

In conclusion, it's highly likely that Robotic Automation has its place in your technology stack, it's just a case that you should take a moment to consider the wider architecture before leaping in.

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