Bots, discovery and doctors…

Imagine the following scenario:

A sudden pain in your leg strikes you while working. Despite your efforts to ignore the pain and concentrate on your tasks, the pain does not stop. Visiting the clinic was a smart decision. Thanks to the absence of a line (the story is made up…) you went straight to the doctor’s office. The doctor gazes at you, looks at the sore leg for about a minute, then looks at you again and says, “Well, I have a feeling that you have a fracture”. A few minutes later, you leave the clinic, plastered but mostly confused … 🤔

In the meantime, let us leave aside for a moment the doctor’s diagnosis and the method of treatment (I will return to it shortly) in favor of something entirely different …

The field of automation in organizations, or more specifically automation using robots (RPA — Robotic Process Automation), is one of the fastest growing technology industries in the world (annual growth of 40%) and allows businesses to utilize automated processes to streamline their operational, rules-based, and repetitive processes. With the use of bots, the organization is able to perform the same functions automatically, thus becoming more competitive, more profitable, and more efficient 🤖.

Now let’s go back to the beginning of the post:

As a result of looking at the source of the pain, the doctor decided to cast the leg. This is similar to an organization that implements an automation solution based on a “gut feel”, organizational anecdotes, or subjective beliefs. Could a fracture be diagnosed by looking? Is it possible to determine what type of treatment is needed without a thorough diagnosis? 🤨

Obviously not! Automation starts with a diagnostic stage, which in its professional lingo is called “Process Discovery”.

In contrast to the automation phase, in most organizations, the Process Discovery phase is performed as a manual project by external consultants or industrial and management engineers who map the processes within the organization, monitor them, observe how they operate, and submit a report to the organization listing the processes that should be automated.

Such a manual process is inefficient, expensive, and inaccurate:

💰 Costly — involves hiring external consultants and/or using the time of the organization’s engineers

🐌 Slow — This process usually takes months to complete. In terms of the Time-to-Market, this is very valuable time that hurts the competitiveness of the organization

🙈 Subjective — The lack of standardization of research tools and research methods leads to biased recommendations, influenced by observers’ biases

🤏 Limited — Identifying and mapping organizational processes are difficult since identifying bottlenecks, failure points, inefficiencies are limited by the testers’ professional abilities and capacities, their availability, as well as the available budget.

Considering the inaccuracy, the differing limitations and the appallingly long duration of RPA projects, it is not surprising that 70% of all resources allocated to RPA projects are actually wasted during the manual Discovery phase and only 8% (!) of all RPA projects cross the 50 robot threshold. 🤦‍♂️

The truth is, RPA offers tremendous value to organizations, but its success depends on an efficient, fast, and accurate process discovery.

To return to the original story that accompanied us at the beginning of the post, it is like an X-ray that was taken when the subject moved during it, and its results were sent to you only two months after it was taken. And what happened in between? The pain will keep occurring…

So what can be done?

In order to deal with this challenge, Kryon has developed a unique Artificial-Intelligence (AI) technology that can perform :

➡️ Automate the detection of workflows in an organization

➡️ Visual representation of workflow in each process

➡️ Identifying which processes can be automated

➡️ Calculating the potential savings in terms of time and costs

➡️ identifies additional processes that can be automated

The discovery process can be completed within a few days and the organization is due to implement the automation process in the shortest possible time, at a rate of up to 80% compared to the manual alternative.

I close by sharing a personal note:

Kryon, where I serve as CMO, is one of the most innovative companies in the field of RPA (according to the leading research companies).

Kryon was the first to offer AI-based automated Process Discovery technology, and in practice, we are the only vendor offering this kind of service. Kryon provides tremendous value to organizations and companies around the globe.