Modern AI observes a large number of workers to map real process flows. This "process genome" reveals hidden variations, ideal for improving efficiency, customer experience, and resource allocation. There's no need to force a one-size-fits-all approach. Now, AI tailors training, automates tasks, and optimizes workflows for better results. Observe, analyze, improve - the future of process optimization is here.
Skan Co-founder and CPO, Manish Garg unveils the importance of computer-vision based process observation as opposed to traditional methods of manual observation. “The modern method of computer-aided process discovery—the art and science of observing at scale, covering diverse geographies, teams and case logs—all done unobtrusively, is a game changer.”
"To acquire knowledge, one must study; but to acquire wisdom, one must observe." —Marilyn vos Savant
From the time of Frederick Winslow Taylor and the advent of scientific management, companies focused on standardization and automation (or mechanization) as the corporate nirvana. Don't get me wrong—they are worthy goals and have a time and place in operational optimization. However, there are many other considerations to satisfy the multistakeholder ecosystem in addition to worker productivity and throughput.
Indeed, Taylorists measured and observed workers doing their tasks to calculate and analyze to glean ways to eliminate waste in any process. But today, thanks to the advent of modern technologies such as computer vision and machine intelligence, observation at a vast scale and high precision is possible.
Manually observing or shadowing a worker or two working on a dozen cases is exciting, but it is just the tip of the iceberg. The sample size of what a couple of consultants observe and report does not extend to tens of thousands or sometimes millions of actions, interactions and transactions in a large corporation. Furthermore, when someone is watching, the subjects' behavior (the employees) will inevitably vary as they tend to be on their best behavior and follow the book. In addition, asking someone how they do their work does not always capture the subtleties and nuances, shortcuts and friction points, rework, and bottlenecks.
The discovery of the volume, velocity, variety and variability in processes is possible when one observes a large group of employees over an extended period. Hence, hiring consultants does not always translate into an accurate picture.
The modern method of computer-aided process discovery—the art and science of observing at scale, covering diverse geographies, teams and case logs—all done unobtrusively, is a game changer. Typically, most process discovery tools rely on a small probe that observes work in real time as knowledge workers interact with digital systems.
This process genome mapping provides visual evidence of how work happens as it happens. This treasure trove of process data can lead to strategic decisions and improvement interventions beyond conventional logic and cookie-cutter solutions.
In our work with several global corporations, here are some things the observed data has unveiled:
Of course, whenever someone mentions observing work, questions around personal privacy and information security come to the forefront. And of course, these are important considerations, but sophisticated process intelligence platforms protect information and privacy through various measures, including inclusion and exclusion lists of applications, selective redaction of information, anonymization and encryption, and retaining confidential information within the firewalls of the company.
The art and science of process discovery and intelligence are exciting new developments to understand the nature of work patterns drawn from a statistically valid sample size. In addition, the observed process data add visual evidence to the expertise of process owners/consultants and operational executives to make informed and intelligent decisions.
Read the original Article on Forbes.