Avinash Misra, CEO & Co-Founder of Skan.AI – Interview Series

Avinash Misra is the CEO and co-founder of Skan. Avinash is a global entrepreneur with a proven track record of taking businesses from seed to cash. He has built successful businesses in the enterprise digital transformation space and his most recent role was the acquisition of Genpact (NYSE: G). Avinash’s knowledge of Skan grew through the large Business Process Transformation projects he led over the past ten years.

Your former company Endeavor Software Technologies was acquired by Genpact. What is this company like and what are some of the key lessons you’ve learned?

This company is a digital transformation specialist. In other words, it specializes in creating and delivering unique technologies such as computer vision, chatbots/natural language processing (NLP), and enterprise mobile applications to improve and transform business processes. to customers.

We learned two main lessons. First, the technology is used for its intended purpose only, resulting in technical and processing debt. Second, the real value comes when technology is approached to the end user with love and thoughtful design.

Can you share the genealogy behind Skan?

“Automation begins when automation fails.” In a nutshell, this is our starting point. When we built RPA bots for complex business processes, we always saw when a bot was released it failed quickly because it didn’t take into account all the features, changes, and positions of it. do business. Every time the robot failed, another work permit was lost. It’s an endless cycle of distribution and failures.

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So, why don’t we understand all aspects of business?

We don’t understand all aspects of business processes because all human business analysts perform process observations that ask process agents to describe processes. People are very dishonest when it comes to describing things that are familiar or permanent. There are many things they can do well, but they cannot describe it with the required accuracy. Therefore, we designed Skan to observe actual work and understand that work and processes, rather than interviewing and recording people.

Skan is part of the process discovery platform. Can you define what discovery is for our readers?

Process discovery is a broad term that refers to the process of discovering or learning how processes work at an organizational or structural level. This is especially challenging in processes that involve human-system interactions with hundreds or thousands of employees, multiple software applications, and complex workflows. A good example is the claims handling process.

Today, Skan is more than just a job search platform. Skan generates deep operational insight (process visibility) and provides advanced analytics to help executives and change leaders measure, analyze, and improve KPIs that drive business results. such as customer experience, revenue, and pricing. We call this broader capability: Knowledge processing, the systematic collection of data and end-to-end processes and the application of that knowledge to manage business outcomes, to learn, to understand, to decision making.

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According to a study conducted by Ernst & Young, 30% to 50% of automation projects fail. Why do you believe this is so high?

In working with our clients, we find that one of the biggest barriers to automation success is a lack of visibility into the current state of KPIs throughout the lifecycle of automation projects.

For example, in order to qualify an automation project, we need to establish current KPIs and create a business case. In the testing phase, we need to define the technical models and define the KPIs (are) based on the current KPIs. During the design, development, testing, and implementation phase, it must be aligned with the cause of the problem to be solved.

Finally, in the validation phase where we measure investment returns and profitability, we need to point to future KPIs. So, we see that throughout this entire life cycle, understanding and engagement with current KPIs and root causes is required. However, according to Forrester Research (2021), only 16% of organizations say that the nature of work is highly visible. It’s no surprise that automation programs struggle to deliver value.

Can you explain what measures Skan takes to protect the privacy of monitored individuals and sensitive business data?

It is important to note that we do not monitor people. We only watch the working parts (not the whole screen). These elements are specific predefined function requests.

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That said, for visible applications, all sensitive performance data will be deleted. We also have the ability to name the relationship between the person who did the work and the work. The names of the people doing the work can be renamed.

Can you talk about how Skan uses machine learning and deep learning?

Skan incorporates a lot of AI and machine learning to solve various problems such as naming sensitive information (text data and images)taking low-level concepts into business processes, determining process graphs, and identifying process variances.

What are some examples of actionable insights gained from this process?

Skan helps operational leaders and change leaders measure, analyze and improve KPIs that drive business results. Some visual examples are:


  • Cost of construction
  • Resource utilization (personnel).
  • NPS improvement


  • Automatic detection
  • First pass rate
  • Legal compliance
  • Capacity (staff) planning
  • Process variability has been reduced

What is your vision for the future of process education?

Our vision for the future of process intelligence is to change the way people work to become more productive and reach their full potential.

Today, the pyramid of work has a broad base of non-value-added activities and a very narrow top of value-added activities. Our vision is to develop processes to change this paradigm.

Thank you for the great interview, readers who want to learn more should visit Skan.


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