Chicken or Egg What Came First: Process or Procedure?

By Thomas B. Cross - CEO TECHtionary.com

As an avid fan of business process automation working with companies on business process optimization, the idea of automating anything doesn't always come first. All too often automation and now robots, artificial intelligence (AI), machine learning or even quantum computing is used to justify anything. And, all too often it fails and when it fails, many run as if from a sinking ship seeking high ground distancing themselves from ever knowing about the project. Yet when asked especially in the area of AI I have a list of more than twenty reasons that I have found to explain why the project failed. RPA or robotics process automation sometimes gets grouped into with failed AI projects, so called guilt by association. RPA in my humble opinion, can provide insights before, during and after any AI project and can lead to more successful projects.  Here are some of the key AI failures not including malicious or pure fake/fraud AI efforts:

-      Too narrow - one SKU not others

-      Too wide - breadth not depth - can analyze ocean water but not what's in the ocean

-      Too complex - helps with auto but not truck claims

And, here's another common one

-      Dirty data – requiring human curation before machine analysis or just too old

This should give you an idea of how easy it is to fail. Yet, this article is not about failure, as from the famous saying from Gene Kranz of NASA on the ill-fated Apollo 13 mission which he supposed didn’t say but I will, "failure is not an option." Business cannot afford any more failures and better ways to design and build AI systems are needed. UiPath is bringing powerful tools that get business going in the right direction and in my opinion, can become core to AI, expert systems and other intelligent business operations. 

Beginning with understanding, how organizations operate via the vast maze of policies, processes and procedures, and then automating via robotic process automation, the means for then applying increased intelligent or AI comes into play. Yet when you breakdown this maze into its smallest elements you can then build new automated or even robotic automated processes. Let's start by looking at some ideas of how this works from some thoughts from UiPath:

A procedure explains:

- Who is responsible for each part of the process

- When each part of the process needs to occur

- How to handle exceptions 

- the specifications applicable to each part of the process.

A process is a set of interrelated or interacting activities that transforms inputs into outputs.

- Inputs - the data that goes in the process

- Process Flows - the sequences of sub-processes or activities undertaken in the process

- Source Applications - the applications or systems used to perform the sub-processes or activities of the process

- Outputs - the result generated by the process;

- Things to remember: The outputs of a process can serve as inputs for other processes.

As UiPath also noted, "Organizations use processes because planning and executing them under controlled conditions can, among other things, improve compliance, ensure that operational needs are met, help in managing risks and drive improvement."

The exciting results from this can yield both forward looking processes simplifying activities, backward-driven feedback and ideas for improving exciting and new policies. Here is an example of the results:

Summary - Robotic Process Automation is more than an exciting wave of technology. In the next article I will review Attended Robot and Unattended Robot Scenarios to dig deep into this exciting area of business to identify complex issues and bring viable solutions. I would like to thank UiPath for the opportunity to share some insights and ideas on their exciting solutions.

If you are interested in AI, consider getting MindMeld. Here are some reviews:

-- “Simply put, MindMeld is the best business book on AI ever as business leaders also need business-focused thought leadership before they make really bad decisions on AI development and delivery.” R.S.

— “As the CEO of an energy industrial company and actively involved in CEO Leadership Forums I have been following AI for more than a decade. Indeed the promises for improving many technical tasks are interesting yet in reality often prove more complex to manage than proposed.  MindMeld was very profound in proposing that AI starts not at the bottom of the organization but with CXO decision-making and worth reading by anyone in or rising to the boardroom.” George B.

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