Top 3 Trends along with some insights from our club members.
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Today, we will look that the top 3 Trends in Intelligent automation along with some of the insights from our club discussions.

The Intelligent Automation space is expanding rapidly and so it is hard to keep up with the trends, tools, and frameworks. It’s awesome to have a peer group to discuss and make sense of the evolving space. Here are a few trends we discussed (from our Digital wall):

We voted on these trends and here are the top 3 and key insights from the members.

Process mining/discovery/intelligence:

  • Processes captured from interviews are usually not complete. Deciphering complete processes and variations using data and AI is what Process Mining enables.
  • Process Mining is not just for Automation as some marketers may want you to believe. Its main value is in understanding the processes so that you can eliminate, standardize, optimize and then automate as needed.
  • Process mining captures data from system committed states (logs, transactions, etc.) while Task mining captures the unstructured data between these states where people are involved e.g. clicks, data inputs, etc.
  • When you are implementing big systems like ERP or even upgrading them, Process mining is the best. Intelligent Automation is usually used for automating tasks between states and so Task Mining may be better.

🎁 Bonus: Here is a complete guide to Process Mining / Discovery

Intelligent Document Processing (IDP)

  • Current solutions are not 100% accurate for most unstructured data. So, you have to accept that it would have limitations and start from there.
  • Set expectations with stakeholders right from the beginning. IDP is a continuous and evolving initiative to improve unstructured data capture. (it is a Marathon, not a sprint)
  • Unstructured data capture is an asymptotic problem. We will get closer and closer but not to 100% accuracy for all doc types.
  • What you can get to - 80% or even 50% is much better than manual data entry which results in bad data that costs businesses $3Trillion per year.
  • We can use a combination of RPA bots and people to verify data output from AI to ensure the best accuracy.

🎁 Bonus: Here is a complete guide to Intelligent Document Processing

Process Orchestration

  • As the Intelligent Automation ecosystem is being formed with diverse tools (using the right tool for the right job), there is a need to manage core operational processes across a hybrid human and digital workforce.
  • Process orchestrators support the management of different classes of Digital Tools (such as RPA, NLP, Virtual assistants, API tools, etc.) from different specialist vendors.
  • These management and governance tools coordinate activity, transport data, and act as a combination of an enterprise bus and support layer.

🎁 Bonus: Here is a demo of Process Orchestration with Turbotic


Top trends you should know about:

  1. Process mining/discovery is not just for Automation. It gives you insights to eliminate, standardize, optimize and automate processes.
  2. Intelligent Document Processing is very useful to ingest unstructured data though no tool is or will be 100%. Set expectations accordingly.
  3. Process Orchestration orchestrates across your digital workforce (RPA, Process Mining, AI, etc.) and People workforce.

That's all for today. In the next email, we will look at Process identification and building a Business Case.

Hope to see you at the club!

See you again soon.

Kind Regards, Nandan